--- title: "API testing, mocking and development answers | Speedscale" description: "Find answers from the Speedscale blog on API testing, mocks, traffic replay, AI development and Kubernetes. Jump to the original explanation and examples." canonical: "https://speedscale.com/answers/" --- # API testing and development answers Search 293 articles and 292 question sections. Each answer links to its original explanation and examples. Search the library TopicAll topicsAI developmentAPI mockingAPI testingEngineering and company newsKubernetes and observabilityPerformance testingTraffic capture and replay 293 articles No matches. Try a broader term or choose all topics. Performance testing · Published 2026-09-24 ## [$4.48 a Gallon: Your Holiday Checkout Is the New Mall](https://speedscale.com/blog/holiday-checkout-is-the-new-mall/) Prepare your checkout for Black Friday with production traffic replay, peak-load tests, and partner API failure rehearsals before the holiday code freeze. Performance testing · Published 2026-02-02 ## [10 Benefits of automated testing](https://speedscale.com/blog/benefits-of-automated-testing/) After spending hours or even days manually testing your software, you may be wondering whether or not there's a better way. The good news? There is. Questions answered in this article (3) * [What is test automation?](https://speedscale.com/blog/benefits-of-automated-testing/#what-is-test-automation) Automated software testing is the practice of creating, running, and analyzing tests automatically (typically with specialized tooling and testing frameworks), with the goal of minimizing time-consuming and repetitive tasks experienced by manual testers. While using a software test automation… * [Why Do You Need Automated Testing?](https://speedscale.com/blog/benefits-of-automated-testing/#why-do-you-need-automated-testing) Knowing the benefits of software test automation is only one piece of the puzzle. Arguably, it is more important to know where to implement it. In many development workflows, such as CI/CD pipelines, it is common to require tests to be run automatically before code is merged or deployed to ensure… * [Why Is Automation Testing Crucial?](https://speedscale.com/blog/benefits-of-automated-testing/#why-is-automation-testing-crucial) Automated testing allows for the shifting of process development, test automation framework development, test maintenance, and more away from active development. Testing is an ongoing and critical function of any software development process, and this is especially true of the application… AI development · Published 2025-04-15 ## [4 Tips for Developing Model Context Protocol Server](https://speedscale.com/blog/4-tips-for-developing-model-context-protocol-server/) The Model Context Protocol (MCP) is rapidly becoming the connective tissue for agentic AI systems and IDE tooling. Performance testing · Published 2024-08-23 ## [5 Strategies for Decreasing API Latency and Improving App Performance](https://speedscale.com/blog/decrease-api-latency/) Application performance can make the difference between retaining or losing customers, with delays beyond a few seconds leading to dropped conversions. Questions answered in this article (2) * [Why Is Keeping Track of Your App’s Performance Important?](https://speedscale.com/blog/decrease-api-latency/#why-is-keeping-track-of-your-apps-performance-important) With users expecting quick, reliable, and efficient interactions, your app’s performance directly influences their experience and your app’s overall reputation. It’s not just about functionality; it’s about delivering that functionality swiftly and smoothly. Tracking and optimizing overall app… * [How Can You Measure Your App’s Performance Efficiently?](https://speedscale.com/blog/decrease-api-latency/#how-can-you-measure-your-apps-performance-efficiently) Regular testing and monitoring are essential to identify and improve overall app performance. Start by defining and tracking essential Key Performance Indicators (KPIs) such as load times and error rates. These app performance metrics will help you establish benchmarks, pinpoint bottlenecks, and… AI development · Published 2025-05-30 ## [5 Tips for Agent-to-Model Mocking](https://speedscale.com/blog/5-tips-for-agent-to-model-mocking/) The near-ubiquity of LLM systems in 2025 has changed the game in many ways. While Large Language Models have been around for some time... Performance testing · Published 2026-02-07 ## [6 Golang Testing Frameworks for Every Type of Test](https://speedscale.com/blog/golang-testing-frameworks-for-every-type-of-test/) What do good tests look like, and do you even need a Golang testing framework? It’s a loaded question with an open answer. Questions answered in this article (2) * [What are Golang Testing Frameworks?](https://speedscale.com/blog/golang-testing-frameworks-for-every-type-of-test/#what-are-golang-testing-frameworks) Golang testing frameworks are essential tools that streamline the testing process, making it more efficient and effective. These frameworks provide a suite of features designed to help developers write and run tests, ensuring that their code functions as intended and catching bugs early in the… * [How to Choose the right Golang testing framework](https://speedscale.com/blog/golang-testing-frameworks-for-every-type-of-test/#how-to-choose-the-right-golang-testing-framework) It’s always important to use the right tool for the job. You can get far with the basic testing capabilities provided by the testing package and go test command. However, it falls short when it comes to larger tests and assertions, which is where test frameworks come in. In this post, you’ve seen a… API mocking · Published 2026-03-27 ## [7 Best Service Virtualization Tools in 2026](https://speedscale.com/blog/service-virtualization-tools/) Compare the 7 best service virtualization tools of 2026 including Speedscale, WireMock, Hoverfly, and Parasoft. Features, pros, cons, and use cases. Questions answered in this article (6) * [What is Service Virtualization?](https://speedscale.com/blog/service-virtualization-tools/#what-is-service-virtualization) Service virtualization is a technique used in software development to simulate the behavior of specific software components or systems that are otherwise unavailable or difficult to access during development and testing. By using a virtualization solution in your testing environment, you can mimic… * [How Do Service Virtualization Tools Work?](https://speedscale.com/blog/service-virtualization-tools/#how-do-service-virtualization-tools-work) Service virtualization utilizes several approaches to create realistic simulations of software components and structures. This is broadly separated into four distinct categories, with product offerings specializing in each domain. The tooling is designed to capture traffic and behavior between… * [What is the difference between service virtualization and API mocking?](https://speedscale.com/blog/service-virtualization-tools/#what-is-the-difference-between-service-virtualization-and-api-mocking) API mocking creates simple request/response stubs, typically hand-written by developers. Service virtualization goes further — it captures real traffic patterns, simulates stateful behavior, and models performance characteristics like latency and throughput. Service virtualization tools are… * [Is service virtualization only for microservices?](https://speedscale.com/blog/service-virtualization-tools/#is-service-virtualization-only-for-microservices) No. Service virtualization works with any architecture that has external dependencies — monoliths calling third-party APIs, mainframe systems communicating over MQ, or microservices calling each other. The technique is architecture-agnostic. * [How does service virtualization fit into CI/CD pipelines?](https://speedscale.com/blog/service-virtualization-tools/#how-does-service-virtualization-fit-into-cicd-pipelines) Service virtualization tools like Speedscale and Proxymock integrate directly into CI/CD pipelines. Instead of spinning up real dependencies for every test run, your pipeline uses virtualized services that respond with production-realistic data, making tests faster, cheaper, and more reliable. * [What is the difference between Hoverfly and Speedscale?](https://speedscale.com/blog/service-virtualization-tools/#what-is-the-difference-between-hoverfly-and-speedscale) Hoverfly is an open-source API simulation tool focused on capture-and-replay for lightweight testing. Speedscale is an enterprise platform that adds production traffic replay, load testing, and automatic mock generation from real Kubernetes traffic. Hoverfly works well for individual developers;… Performance testing · Published 2024-11-21 ## [A Developer's Guide to Continuous Performance Testing](https://speedscale.com/blog/a-developers-guide-to-continuous-performance-testing/) Today’s fast-paced development environments require new approaches to testing. Enter continuous performance testing. Questions answered in this article (5) * [What is continuous performance testing?](https://speedscale.com/blog/a-developers-guide-to-continuous-performance-testing/#what-is-continuous-performance-testing) Continuous performance testing, also known as a continuous performance test, is the continuous monitoring of the performance of an application under increased load. It’s typically done on every code commit, eliminating the need for manual performance tests that can be time-consuming and expensive.… * [Are there different types of performance tests?](https://speedscale.com/blog/a-developers-guide-to-continuous-performance-testing/#are-there-different-types-of-performance-tests) There are several types of performance testing, but one that is often used is load testing. Load tests are designed to simulate the activity of multiple users accessing software simultaneously. Similar to stress testing, the goal is to test the limits of how many requests the application can… * [Who can benefit from continuous performance testing?](https://speedscale.com/blog/a-developers-guide-to-continuous-performance-testing/#who-can-benefit-from-continuous-performance-testing) This depends upon the company’s needs, but generally speaking, some companies will find continuous performance tests more valuable than others. These companies typically have: A large user base High volumes of regular interaction and/or seasonal spikes in traffic Invested a lot of time or money… * [Why you need continuous performance testing?](https://speedscale.com/blog/a-developers-guide-to-continuous-performance-testing/#why-you-need-continuous-performance-testing) According to the Akamai Performance report, 49% of customers expect webpages to fully load within two seconds. 18% of customers expect instant page load. In this day and age, users believe that waiting more than two to three seconds for a page to load is unacceptable. When they encounter issues,… * [How to start continuous performance testing](https://speedscale.com/blog/a-developers-guide-to-continuous-performance-testing/#how-to-start-continuous-performance-testing) To begin continuous performance testing, first make sure that you have a continuous integration pipeline, or CI pipeline, in place. Integrating continuous performance testing is crucial for enhancing software performance and user experience. Start by setting up a structured approach that includes… AI development · Published 2025-10-03 ## [A Developer's Guide to Improving AI Code Reliability](https://speedscale.com/blog/a-developers-guide-to-improving-ai-code-reliability/) AI code reliability explained for developers using LLMs to write faster while keeping their code safe and maintainable Questions answered in this article (4) * [Can I trust AI to write code for production?](https://speedscale.com/blog/a-developers-guide-to-improving-ai-code-reliability/#can-i-trust-ai-to-write-code-for-production) AI-generated code can indeed be deployed to production, but it requires validation first. Treat it like code from a capable but junior developer, requiring review and testing before deployment, rather than a “rubber stamp”. The key is building validation processes that catch AI-specific issues,… * [How do I stop AI from generating unreliable code?](https://speedscale.com/blog/a-developers-guide-to-improving-ai-code-reliability/#how-do-i-stop-ai-from-generating-unreliable-code) Better prompting helps significantly. Be specific about libraries and versions, provide context about your architecture and constraints, include example inputs and expected outputs, and explicitly ask for error handling. Provide documentation or examples to guide the AI’s approach. * [What is ‘hallucinated code’ and how do I catch it?](https://speedscale.com/blog/a-developers-guide-to-improving-ai-code-reliability/#what-is-hallucinated-code-and-how-do-i-catch-it) Hallucinated code occurs when AI generates functions, methods, or APIs that appear plausible but don’t actually exist. You can catch it by systematically verifying that every function call references real library methods, using IDE error checking, and validating against official documentation.… * [Are there risks associated with copying and pasting AI code from platforms like ChatGPT?](https://speedscale.com/blog/a-developers-guide-to-improving-ai-code-reliability/#are-there-risks-associated-with-copying-and-pasting-ai-code-from-platforms-like-chatgpt) Yes, several significant risks. The code might contain hallucinated functions, security vulnerabilities, outdated patterns, or logic that doesn’t align with your specific requirements. AI code from chat platforms also lacks context about your application architecture. Always validate, test, and… Kubernetes and observability · Published 2024-05-02 ## [A Guide to Kubernetes Visibility: Best Practices and Tools](https://speedscale.com/blog/a-guide-to-kubernetes-visibility-best-practices-and-tools/) Kubernetes (k8s) is becoming the go-to solution for managing containerized applications. Effectively managing and understanding what happens within a... Questions answered in this article (4) * [What does Kubernetes visibility mean?](https://speedscale.com/blog/a-guide-to-kubernetes-visibility-best-practices-and-tools/#what-does-kubernetes-visibility-mean) Kubernetes visibility refers to the ability to monitor and understand the state and behavior of all aspects of a Kubernetes environment. This includes underlying infrastructure as well as application traffic. * [How does Kubernetes visibility improve performance?](https://speedscale.com/blog/a-guide-to-kubernetes-visibility-best-practices-and-tools/#how-does-kubernetes-visibility-improve-performance) Visibility into your Kubernetes deployment can improve performance in several aspects: Proactive Monitoring: Continuously monitoring pods, nodes, and services helps teams detect and address potential issues before they impact application performance metrics. Resource Allocation: Visibility tools… * [Why is Kubernetes visibility difficult?](https://speedscale.com/blog/a-guide-to-kubernetes-visibility-best-practices-and-tools/#why-is-kubernetes-visibility-difficult) However, achieving full visibility in Kubernetes can be extra challenging. For starters this is because: Complexity of Architecture: Kubernetes environments are highly dynamic and distributed. There are also differences between your own application versus Kubernetes overhead such as Kubernetes… * [Why do we need 3rd party tools for Kubernetes visibility?](https://speedscale.com/blog/a-guide-to-kubernetes-visibility-best-practices-and-tools/#why-do-we-need-3rd-party-tools-for-kubernetes-visibility) While vanilla Kubernetes offers basic monitoring tools via the Kubernetes API (this powers tools like kubectl and the Kubernetes dashboard), these are often insufficient for comprehensive visibility. Additional tools are used for: Extended Capabilities: Specialized tools can capture more detailed… Kubernetes and observability · Published 2024-12-20 ## [A Guide to Optimizing Kubernetes Clusters with Karpenter](https://speedscale.com/blog/optimize-kubernetes-karpenter/) With the promise of auto-provisioning and self-healing, Kubernetes environments can be an attractive option for hosting your application platform. Questions answered in this article (3) * [How Does Kubernetes Work?](https://speedscale.com/blog/optimize-kubernetes-karpenter/#how-does-kubernetes-work) At its core, Kubernetes uses a master-worker architecture, consisting of: Control Plane - this system manages the cluster’s state and orchestrates operations. Key components include the API server, scheduler, and other orchestration systems. Nodes (Worker Nodes) - nodes run the containerized… * [How Does Karpenter Work?](https://speedscale.com/blog/optimize-kubernetes-karpenter/#how-does-karpenter-work) In essence, Karpenter combines Kubernetes cluster awareness with instance provisioning and auto-scaling solutions. Karpenter is monitoring the Kubernetes API server for pods that cannot be scheduled based on resource demands that are unmet. When these demands are discovered, it figures out what the… * [How to Optimize Kubernetes Clusters with Karpenter](https://speedscale.com/blog/optimize-kubernetes-karpenter/#how-to-optimize-kubernetes-clusters-with-karpenter) With all of this in mind, let’s take a structured look at how you can optimize Kubernetes clusters with Karpenter in practice. To do this, we’ll explore the concept of rightsizing, a process by which you can maximize efficiency and performance, and the cloud infrastructure underpinning it all. Engineering and company news · Published 2025-09-19 ## [Accelerating Cloudnative Development & DevOps](https://speedscale.com/blog/accelerating-cloudnative-development-devops/) Cloud-native development and DevOps accelerate delivery—but add complexity. Move fast safely with Speedscale: key patterns and pitfalls. Learn more. API mocking · Published 2023-12-27 ## [Advantages of Service Virtualization Over Service Mocking](https://speedscale.com/blog/service-virtualization-vs-mocking/) Service mocking, API mocking, stubs, test doubles, fake APIs, service virtualization tools…the list goes on for testing tools with the purpose of. Questions answered in this article (5) * [When to use stubs, service mocks, and service virtualization?](https://speedscale.com/blog/service-virtualization-vs-mocking/#when-to-use-stubs-service-mocks-and-service-virtualization) The degree of mimicking real software components depends on your test scenarios. * [When to use stubs?](https://speedscale.com/blog/service-virtualization-vs-mocking/#when-to-use-stubs) A stub or test double is often used as simple, consistent returns to method calls, and are commonly used by an individual developer for unit testing (vs. shared with a team). Stubs typically return static test data and do not dynamically contain state. For example, let’s say one of your dependent… * [When to use service mocks?](https://speedscale.com/blog/service-virtualization-vs-mocking/#when-to-use-service-mocks) API mocking or service mocks usually happen over a network and have a more varied library of responses. But service mocks still have trouble keeping track of state beyond a simple unit test scenario. For example, eCommerce web services could have dependent components for the shopping cart. Real… * [When to use service virtualization?](https://speedscale.com/blog/service-virtualization-vs-mocking/#when-to-use-service-virtualization) API service virtualization usually addresses this by “learning” as much behavior about specific software components by recording the network traffic. Service virtualization is more commonly used during functional tests, integration tests, and acceptance tests. For a refresher on service… * [What’s next on the horizon: auto generated service virtualization with Speedscale?](https://speedscale.com/blog/service-virtualization-vs-mocking/#whats-next-on-the-horizon-auto-generated-service-virtualization-with-speedscale) Future solutions will require virtual services to be cheap and quick to build. As the complexity of microservices increases, it becomes virtually impossible for humans to reason about. This is why platform engineering espouses the need for internal developer platforms (IDPs), and reduces cognitive… AI development · Published 2026-05-18 ## [Agile is dead. AI is the culprit.](https://speedscale.com/blog/sdlc-shift-ai-agile/) Discover why AI coding agents are breaking Agile workflows and driving the shift to an intent-based AI Software Factory. AI development · Published 2025-08-01 ## [AI Agent Is Hitting Your APIs - Are You Ready?](https://speedscale.com/blog/ai-agent-is-hitting-your-apis-are-you-ready/) It’s no longer theoretical - artificial intelligence has left research labs and entered production systems, generating a new breed of consumers. Questions answered in this article (3) * [What Are AI Agents – And How Do AI Agents Work?](https://speedscale.com/blog/ai-agent-is-hitting-your-apis-are-you-ready/#what-are-ai-agents--and-how-do-ai-agents-work) AI agents are at the forefront of modern software systems, designed to operate autonomously or semi-autonomously in a variety of environments. These agents leverage advanced technologies such as natural language processing and machine learning to interpret user input, analyze data, and adapt their… * [What Are AI Agents - And How Do AI Agents Work?](https://speedscale.com/blog/ai-agent-is-hitting-your-apis-are-you-ready/#what-are-ai-agents---and-how-do-ai-agents-work) AI agents are software systems that use artificial intelligence and machine learning to perform tasks autonomously. They range from simple reflex agents, which are driven by predefined rules to perform a particular and limited function, to advanced goal-based and utility-based agents that maintain… * [Why APIs Are Attractive Targets for AI Agents?](https://speedscale.com/blog/ai-agent-is-hitting-your-apis-are-you-ready/#why-apis-are-attractive-targets-for-ai-agents) APIs are particularly appealing to AI agents because they offer a standardized, programmatic way to interact with software systems and services. Through APIs, AI agents can capture traffic, analyze real world conditions, and replay traffic to test how systems respond under various scenarios. This… AI development · Published 2025-05-16 ## [AI Code: How AI Is Changing How We Write and Test It](https://speedscale.com/blog/ai-code-how-ai-is-changing-how-we-write-and-test-it/) As a software engineer, I’ve always leaned on a solid foundation of code reviews, unit tests, and CI pipelines to ensure quality. AI development · Published 2026-03-30 ## [AI Coding Agents Break What Works](https://speedscale.com/blog/ai-coding-agents-break-what-works/) AI agents silently modify working systems to force changes through. Three real patterns and the guardrails that catch them. AI development · Published 2026-03-11 ## [AI Coding Agents Have a UX Problem Nobody Wants to Talk About](https://speedscale.com/blog/ai-coding-agents-ux-problem/) Fast mode or deep mode? Haiku or Opus? Cursor or Claude Code? The decision fatigue from AI coding tools is killing the productivity they promised. AI development · Published 2025-12-19 ## [AI Prediction for 2026](https://speedscale.com/blog/ai-prediction-for-2026/) Explore 5 bold AI predictions for 2026. From the burst of the AI bubble to the rise of 'vibe coding' and agentic workflows, discover why the future of. AI development · Published 2026-07-09 ## [AI writes code in seconds, but delivery still takes days](https://speedscale.com/blog/ai-delivery-bottleneck/) AI pushed throughput up 59%, yet median delivery got worse. The bottleneck moved to validation. How replaying production traffic in CI closes the gap. AI development · Published 2026-05-18 ## [Anatomy of the AI Software Factory: The Context Layer](https://speedscale.com/blog/ai-software-factory-context-layer/) Explore the technical architecture of the AI Software Factory, focusing on tool convergence and the Unified Context Layer. API testing · Published 2021-08-17 ## [API for Beginners – Frequently Asked Questions](https://speedscale.com/blog/api-for-beginners-faqs/) Are you looking to benefit from automation but lack the experience to leverage an API? To equip you with the tools you need to start utilizing APIs and... Questions answered in this article (7) * [What is an API?](https://speedscale.com/blog/api-for-beginners-faqs/#what-is-an-api) API stands for Application Programming Interface. An API is a set of programming code that enables data transmission between one software product and another. * [How does an API Work?](https://speedscale.com/blog/api-for-beginners-faqs/#how-does-an-api-work) APIs sit between an application and the web server, acting as an intermediary layer that processes data transfer between systems. Here’s how an API works: A client application initiates an API call to retrieve information—also known as a request. This request is processed from an application to the… * [What is API Testing?](https://speedscale.com/blog/api-for-beginners-faqs/#what-is-api-testing) While there are many aspects of API testing, it generally consists of making requests to a single or sometimes multiple API endpoints and validating the response. The purpose of API testing is to determine if the API meets expectations for functionality, performance, and security. * [What is the most popular API?](https://speedscale.com/blog/api-for-beginners-faqs/#what-is-the-most-popular-api) The most used API is a RESTful API (Representational State Transfer API). RESTful APIs allow for interoperability between different types of applications and devices on the internet. * [What is a REST API?](https://speedscale.com/blog/api-for-beginners-faqs/#what-is-a-rest-api) A REST API conforms to the design principles of the REST, or representational state transfer architectural style. Restful APIs are extremely simple when it comes to building and scaling as compared to other types of APIs. When these types of APIs are put into action, they help facilitate… * [What is REST API Testing?](https://speedscale.com/blog/api-for-beginners-faqs/#what-is-rest-api-testing) REST API Testing is a web automation testing technique for testing REST-based APIs for web applications without using the user interface. The purpose of REST API testing is to record the response of REST API by sending various HTTP requests to check if REST API is working correctly. You can test a… * [What is the most Popular Response Data Format?](https://speedscale.com/blog/api-for-beginners-faqs/#what-is-the-most-popular-response-data-format) JSON is the most popular response data format amongst developers. JSON (JavaScript Object Notation) is a lightweight >Learn how Speedscale’s solutions can help improve your API testing & performance. Stay tuned for our upcoming post: REST API & Testing Terminology Everyone Should Know. AI development · Published 2025-07-18 ## [API Security: Validating Auth and Access with Traffic Simulation Starts with Behavior](https://speedscale.com/blog/api-security-validating-auth-and-access-with-traffic-simulation-starts-with-behavior/) Security breaches rarely begin with a hidden zero-day exploit or a complex web of escalated hacks. Questions answered in this article (2) * [Why Static API Security Testing Falls Short?](https://speedscale.com/blog/api-security-validating-auth-and-access-with-traffic-simulation-starts-with-behavior/#why-static-api-security-testing-falls-short) Traditional security tools have their place. Linters and description validators, such as Spectral and LintGPT, are excellent at enforcing consistency and design quality pre-deployment, and they’re also fairly effective at flagging common issues, including those identified in the OWASP API Security… * [What Traffic Simulation Looks Like in Practice?](https://speedscale.com/blog/api-security-validating-auth-and-access-with-traffic-simulation-starts-with-behavior/#what-traffic-simulation-looks-like-in-practice) Simulating traffic isn’t about blasting endpoints with noise. It’s about reproducing the way legitimate API users, as well as malicious threat actors, interact with your web APIs. This can be done by capturing actual API usage via logging middleware or gateways and replaying it in test… AI development · Published 2025-07-14 ## [API Staging Is Not Production - But Speedscale Makes It Close](https://speedscale.com/blog/api-staging-is-not-production-but-speedscale-makes-it-close/) Staging environments are often looked at as the testing ground ahead of the “real” production environment. Questions answered in this article (2) * [Why API Testing Tools Need to Be Realistic?](https://speedscale.com/blog/api-staging-is-not-production-but-speedscale-makes-it-close/#why-api-testing-tools-need-to-be-realistic) Automated API testing is only effective when it reflects how your APIs are actually used. Unfortunately, too many API test suites focus on ideal, expected scenarios. They validate status codes, check for expected responses, and verify schema compliance, but often overlook the importance of… * [Why API Testing Is Critical in 2025?](https://speedscale.com/blog/api-staging-is-not-production-but-speedscale-makes-it-close/#why-api-testing-is-critical-in-2025) Let’s be clear here - API testing isn’t optional. APIs are Application Programming Interfaces - they are the Rosetta Stone that interfaces your system with every other system, and getting this right is the difference between universal understanding and absolute bedlam. It’s one of the most… API testing · Published 2025-07-02 ## [API Test Automation for Zero Trust Model](https://speedscale.com/blog/api-test-automation-for-zero-trust-model/) Security isn’t just about keeping threats outside a well-defined perimeter. In fact, it’s as much about accepting that there is no perimeter. Performance testing · Published 2026-02-06 ## [API Testing Tools Best Practices Guide](https://speedscale.com/blog/api-testing-tools/) Today’s software testing trends show the growing demand for more efficient and automated API testing. Questions answered in this article (2) * [What is API Testing?](https://speedscale.com/blog/api-testing-tools/#what-is-api-testing) API testing involves a provider employing various tests to confirm their Application Programming Interfaces (APIs) function correctly, perform efficiently, are reliable, and maintain stringent security standards. API tests often focus on a wide range of specific domains, including tests that… * [What Are the Types of API Testing?](https://speedscale.com/blog/api-testing-tools/#what-are-the-types-of-api-testing) There are different types of API testing, each of which have their own benefits and drawbacks. Often, multiple types can be combined to make for more comprehensive API testing, ensuring comprehensive coverage of the entire API. Traffic capture and replay · Published 2026-03-24 ## [API Traffic Replay Testing: The Definitive Guide (2026)](https://speedscale.com/blog/definitive-guide-to-traffic-replay/) What is API traffic replay testing? Capture, sanitize, and replay production traffic. Compare GoReplay vs WireMock vs Speedscale vs proxymock. Questions answered in this article (6) * [Why use traffic replay instead of scripted tests?](https://speedscale.com/blog/definitive-guide-to-traffic-replay/#why-use-traffic-replay-instead-of-scripted-tests) With the number of microservices, containers, and dependencies in modern applications, manually scripting test cases for every scenario is impractical. Traffic replay solves this by turning real production behavior into your test suite: Realistic coverage. Tests reflect actual user behavior, not… * [What is API replay?](https://speedscale.com/blog/definitive-guide-to-traffic-replay/#what-is-api-replay) API replay is the process of recording real API requests and responses from a live environment and playing them back against a different environment (staging, QA, or development) to validate that the application behaves correctly. It replaces manually scripted API tests with realistic production… * [What is replay traffic?](https://speedscale.com/blog/definitive-guide-to-traffic-replay/#what-is-replay-traffic) Replay traffic refers to the recorded HTTP requests, responses, headers, and metadata captured from a production or staging environment that are stored and subsequently sent to a target system for testing. The traffic is typically sanitized (PII removed, tokens refreshed) before replay. * [What is replay testing?](https://speedscale.com/blog/definitive-guide-to-traffic-replay/#what-is-replay-testing) Replay testing is a software testing approach where previously captured production interactions are replayed against a system under test to verify behavior, performance, and correctness. It is used for regression testing, load testing, contract validation, chaos testing, migration validation, and… * [What are the different types of API testing that use traffic replay?](https://speedscale.com/blog/definitive-guide-to-traffic-replay/#what-are-the-different-types-of-api-testing-that-use-traffic-replay) Traffic replay supports multiple API testing types: regression testing (replay old traffic against new code to catch behavioral changes), load testing (multiply captured traffic to simulate peak load), contract testing (verify API responses match expected schemas), migration testing (compare… * [How does API traffic replay differ from API mocking?](https://speedscale.com/blog/definitive-guide-to-traffic-replay/#how-does-api-traffic-replay-differ-from-api-mocking) API mocking simulates external service responses using hand-crafted or recorded stubs. Traffic replay is broader: it captures and replays the full request/response cycle, including inbound client traffic and outbound dependency calls. In practice, the two are complementary — replay tools like… API testing · Published 2025-09-26 ## [API World 2025: Growth, Memories, and Next Steps](https://speedscale.com/blog/api-world-2025-growth-memories-and-next-steps/) A couple of weeks ago, our team returned from API World. API testing · Published 2025-08-22 ## [API World 2025: Learning, Growing, and Showcasing Proxymock](https://speedscale.com/blog/pre-api-world/) Join us as we get ready for API World 2025! This blog post is all about our pre-conference excitement, the goals we hope to achieve. API testing · Published 2026-08-26 ## [Application Level Dependency Chaos Testing](https://speedscale.com/blog/application-level-dependency-chaos-testing/) A scoped chaos rule takes one dependency down and nothing else, so the fallback branch in your code executes on demand instead of during an outage. Traffic capture and replay · Published 2022-02-08 ## [Auto-generate Postman Collections from traffic](https://speedscale.com/blog/auto-generate-postman-collections/) Postman is a great tool for API testing during development. It's GUI is simple to learn and ubiquitous. However, manually writing test cases for local... Traffic capture and replay · Published 2025-06-30 ## [Automated API Governance with Traffic Snapshots](https://speedscale.com/blog/automated-api-governance-with-traffic-snapshots/) API governance often gets a bad rap. It’s painted as the bottleneck - why new APIs (application programming interfaces, are standardized protocols that... API mocking · Published 2025-07-22 ## [Automating API Mocks in Your CI Pipeline with proxymock](https://speedscale.com/blog/automating-api-mocks-in-your-ci-pipeline-with-proxymock/) Capture API responses once with proxymock and replay them in CI. Eliminate flaky tests from rate limits, downtime, and slow external dependencies. Questions answered in this article (1) * [Why Use proxymock in CI Pipelines?](https://speedscale.com/blog/automating-api-mocks-in-your-ci-pipeline-with-proxymock/#why-use-proxymock-in-ci-pipelines) When running tests in CI/CD, external API dependencies can be problematic: Unreliable availability: The API might be down or rate-limited. Slow performance: API calls introduce latency into test runs. Inconsistent data: Live APIs may return different responses over time. Using proxymock in CI… Engineering and company news · Published 2025-08-15 ## [Back in India for KubeCon 2025: Connections, Conversations, and a Sprint Through Delhi — Part 1](https://speedscale.com/blog/back-in-india-for-kubecon-2025-connections-conversations-and-a-sprint-through-delhi-part-1/) Last week, I returned to India for the first time since the beginning of COVID — and what a journey it was! API testing · Published 2025-08-29 ## [Back in India for KubeCon 2025: Highlights from Hyderabad — Part 2](https://speedscale.com/blog/back-in-india-for-kubecon-2025-highlights-from-hyderabad-part-2/) After an eventful week of customer visits and reconnecting with partners, the centerpiece of my trip was KubeCon in Hyderabad. Walking into the venue... AI development · Published 2025-11-19 ## [Better integration tests in Cursor using proxymock](https://speedscale.com/blog/better-integration-tests-in-cursor-using-proxymock/) Cursor can scaffold new API calls, proxymock traffic snapshots give me the integration tests, replays. API testing · Published 2026-06-19 ## [Beware of PII in Testing Data: The Security Iceberg and Where PII Actually Hides](https://speedscale.com/blog/beware-of-production-similar-data-the-security-iceberg-and-where-pii-actually-hides/) Using 'production-similar' data in pre-production is a major security risk. Learn why traditional masking fails, where hidden PII hides, and how to fix it. Questions answered in this article (1) * [How-To: Spotting Hidden PII Local-First with Proxymock](https://speedscale.com/blog/beware-of-production-similar-data-the-security-iceberg-and-where-pii-actually-hides/#how-to-spotting-hidden-pii-local-first-with-proxymock) Want to try this on your own machine before rolling out infrastructure-wide controls? Speedscale’s proxymock is a local-first record, replay, and mocking tool that lets you capture real API traffic and spot dynamic patterns—including hidden PII and secrets—right from your workstation. Let’s walk… AI development · Published 2026-04-17 ## [Beyond AI Vibes: Deterministic Foundations for Agentic Coding](https://speedscale.com/blog/beyond-ai-vibes-deterministic-foundations-agentic-coding/) AI coding adoption is high and trust is dropping. A testing pyramid for agents, plus reproducible production context that grounds AI in real behavior. Performance testing · Published 2025-06-26 ## [Boba Paradox](https://speedscale.com/blog/boba-paradox/) It’s 2PM on a Thursday. Your engineering team is knee-deep in bugs from a recent release. But what’s the Slack channel buzzing about? Not flaky tests. Questions answered in this article (4) * [Why We’re Still Talking About Testing in 2024?](https://speedscale.com/blog/boba-paradox/#why-were-still-talking-about-testing-in-2024) It’s 2024, and testing is still front and center in every serious software development conversation. Why? Because as our software gets more complex and user expectations skyrocket, the risks of skipping proper testing have never been higher. Modern systems are a tangled web of services, APIs, and… * [What is Performance Testing?](https://speedscale.com/blog/boba-paradox/#what-is-performance-testing) Performance testing is all about making sure your software doesn’t just work—it works well, even when things get busy. Using specialized testing software, teams can simulate how real users interact with web applications, APIs, and other systems. This means throwing different types of system based… * [Why Testing Tools Get Skipped?](https://speedscale.com/blog/boba-paradox/#why-testing-tools-get-skipped) Let’s dig deeper. Why do test tools get deprioritized? Invisible ROI: When testing works, nothing happens. That makes it hard to sell. Cultural inertia: Testing is still often seen as “QA’s problem.” Postponed investment: Tools get pushed off “until after this next release.” Developer fatigue: Most… * [What if Testing Didn’t Suck?](https://speedscale.com/blog/boba-paradox/#what-if-testing-didnt-suck) Speedscale was built for teams that want to ship fast without sacrificing reliability. We help you: ✅ Record real traffic from production and leverage data from real user interactions to create accurate test scenarios ✅ Replay it automatically in CI/CD, running load tests with concurrent virtual… API mocking · Published 2024-08-28 ## [Boost Your Workflow with the Ultimate Local Development Mock](https://speedscale.com/blog/ultimate-local-development-mocks/) The benefits of API mocking extend beyond just speeding up development. It enables developers to work independently of external APIs... AI development · Published 2024-11-19 ## [Boosting Developer Productivity: Specific Metrics to Measure and Improve](https://speedscale.com/blog/developer-productivity/) As we close out 2024, developer productivity and happiness continue to be a focus for many organizations. Kubernetes and observability · Published 2024-09-09 ## [Boosting Kubernetes Developer Productivity: Top Tools and Strategies for Efficient Development](https://speedscale.com/blog/boosting-kubernetes-developer-productivity/) Developer productivity is not just about writing code faster—it's about creating efficient, self-service environments that minimize friction and reduce. API testing · Published 2026-08-26 ## [Break One Dependency, Not The Whole Cluster](https://speedscale.com/blog/scoped-chaos-rules-proxymock/) Scoped chaos rules are now in proxymock: pick traffic with a filter query, perturb it, and label every injected failure so it is never mistaken for a real one. Kubernetes and observability · Published 2024-11-20 ## [Build and Deploy Kubernetes Applications with Skaffold](https://speedscale.com/blog/getting-started-with-skaffold-for-kubernetes-deployments/) Skaffold is a command line tool that facilitates continuous development by streamlining the workflow for building, pushing, and deploying Kubernetes... Questions answered in this article (1) * [How to implement Skaffold](https://speedscale.com/blog/getting-started-with-skaffold-for-kubernetes-deployments/#how-to-implement-skaffold) In this section, you’ll install Skaffold and create a simple project to get a taste of the inner development workflow with Skaffold. API mocking · Published 2026-06-18 ## [Build WireMock mappings fast from real traffic](https://speedscale.com/blog/wiremock-export/) Skip hand-writing WireMock stubs. Speedscale records your real request and response traffic and exports it straight to WireMock mappings. AI development · Published 2026-02-18 ## [Building Speedy: An Autonomous AI Development Agent](https://speedscale.com/blog/building-speedy-autonomous-ai-development-agent/) How we built an AI agent that implements Jira tickets, creates merge requests, and monitors them autonomously—and the iterative journey to get there. Traffic capture and replay · Published 2026-06-12 ## [Capture once, test forever](https://speedscale.com/blog/traffic-data-lake/) Production traffic is the most complete record of what your system does, and most teams throw it away. One capture powers reproduce, validate, and sandbox. Performance testing · Published 2025-11-03 ## [Cascading Failures Aren’t Inevitable: Lessons from the AWS DNS Outage](https://speedscale.com/blog/cascading-failures-arent-inevitable-lessons-from-the-aws-dns-outage/) The AWS DNS outage exposed the risk of cascading failures. Learn how to prevent a single DNS failure from taking down your system by mapping service. AI development · Published 2025-05-19 ## [Catch Prompt Misfires Before They Burn Trust in LLM](https://speedscale.com/blog/catch-prompt-misfires-before-they-burn-trust-in-llm/) Large Language Models (LLMs) are incredibly powerful, but they are also incredibly fragile. Kubernetes and observability · Published 2026-08-17 ## [Chaos Monkey Won't Find Your Bug](https://speedscale.com/blog/two-kinds-of-chaos-infrastructure-and-application/) Infrastructure and application chaos break different layers and find different bugs. Netflix built two systems for a reason. Most enterprises buy just one. Engineering and company news · Published 2024-09-05 ## [Code Faster with a Tuned Dev Environment](https://speedscale.com/blog/local-development-environments/) The rise of remote development environments, like GitHub Codespaces, has certainly captured the spotlight in recent years. Questions answered in this article (1) * [What is a Local Development Environment?](https://speedscale.com/blog/local-development-environments/#what-is-a-local-development-environment) A local development environment is a setup where you host your project’s files directly on your computer rather than on a remote server. This setup allows developers to test, debug, and refine their code in a safe, isolated space before it goes live. By working locally, you gain full control over… API testing · Published 2025-09-04 ## [Considerations for Testing gRPC Streams](https://speedscale.com/blog/considerations-for-testing-grpc-streams/) If you’ve spent any time building cloud-native systems, you’ve probably tripped over the tricky beast that is gRPC streaming. It’s powerful, flexible... Questions answered in this article (1) * [Why Test with Real Pub/Sub?](https://speedscale.com/blog/considerations-for-testing-grpc-streams/#why-test-with-real-pubsub) Using Pub/Sub as part of your load test brings realism that mocks just can’t replicate. For example: Backpressure and bottlenecks – Pub/Sub enforces quotas and flow control. If your subscribers can’t keep up, Pub/Sub will happily slow things down. That’s the kind of production-like behavior you… AI development · Published 2026-05-18 ## [Conway's Law 2.0: The VP's Playbook](https://speedscale.com/blog/conways-law-ai-factory/) Learn how VPs of Engineering must adapt org charts, engineering roles, and performance metrics to lead in the era of the AI Software Factory. API mocking · Published 2024-08-26 ## [Crafting the Best Golang Developer Environments](https://speedscale.com/blog/crafting-the-best-golang-developer-environments/) Go is an open-source programming language and developer environment from Google that allows for incredibly efficient and powerful applications. AI development · Published 2026-04-15 ## [Dark Code: The AI-Generated Software Nobody Understands](https://speedscale.com/blog/dark-code/) Dark code is software no human has written, read, or reviewed. As AI tools accelerate, the gap between shipped code and understood code is widening fast. Traffic capture and replay · Published 2026-03-03 ## [Debugging Encrypted Microservice Traffic with Speedscale's eBPF Collector](https://speedscale.com/blog/you-cant-fix-what-you-cant-see-debugging-encrypted-microservice-traffic-with-speedscales-ebpf-collector/) Learn how to capture, inspect, archive encrypted microservice traffic with Speedscale's eBPF collector, no certificate management or code changes required. Questions answered in this article (1) * [How to create a snapshot](https://speedscale.com/blog/you-cant-fix-what-you-cant-see-debugging-encrypted-microservice-traffic-with-speedscales-ebpf-collector/#how-to-create-a-snapshot) In the Traffic Viewer, select the traffic that you want to save as a snapshot using the time picker and filters. Click Save to Tests/Mocks. Snapshots are reusable between replay runs. Each run generates its own report with its own latency graphs, assertion results, and captured traffic, but all… Kubernetes and observability · Published 2025-10-20 ## [Debugging Without a Net: The Pain of Reproducing Production Issues](https://speedscale.com/blog/debugging-without-a-net-the-pain-of-reproducing-production-issues/) Catch the ghost! Learn why reproducing production bugs is so hard, how unrealistic test environments fail you. Performance testing · Published 2026-01-30 ## [Determine Throughput Performance Testing](https://speedscale.com/blog/determine-throughput-performance-testing/) Measuring throughput and latency is a critical step in load testing software to ensure application performance and stability. In this article... Questions answered in this article (1) * [What is Throughput in Performance Testing?](https://speedscale.com/blog/determine-throughput-performance-testing/#what-is-throughput-in-performance-testing) Throughput in performance testing refers to the rate at which a system or application processes requests or transactions within a specified time frame. It is a critical metric that helps evaluate the performance and scalability of a system, ensuring that it can handle a large volume of data and… AI development · Published 2026-08-11 ## [Diagnose Serial N+1 API Calls With Tempo + proxymock](https://speedscale.com/blog/diagnose-n-plus-one-tempo-proxymock/) Diagnose serial N+1 API calls with Tempo and proxymock. Replay recorded traffic, inspect trace windows, and prove a concurrency fix preserves behavior. API mocking · Published 2026-09-02 ## [Did It Actually Send?](https://speedscale.com/blog/did-it-actually-send/) Part 4 of Getting Started with Mocks: the notifier stops returning a message and starts sending one, so the test needs a spy instead of a return value. AI development · Published 2025-12-16 ## [Digital Twins Gone Wild: My Unexpected AI Doppelgänger](https://speedscale.com/blog/digital-twins-gone-wild-my-unexpected-ai-doppelgnger/) Tired of Staging environments that don't match Prod? Learn how Speedscale's Digital Twin, built from real production traffic, solves dependency. Performance testing · Published 2026-02-12 ## [DLP, Traffic Replay, and the Missing Link to Software Quality](https://speedscale.com/blog/dlp-traffic-replay-and-the-missing-link-to-software-quality/) DLP applied to production traffic enables safe observability and realistic traffic replay, closing the gap between testing and production for faster. API testing · Published 2025-08-20 ## [Don't Just Monitor SLAs - Validate Them Automatically](https://speedscale.com/blog/dont-just-monitor-slas-validate-them-automatically/) Service level agreements (SLAs) are the contractual backbone between customers and technology vendors, outlining expected service availability... Engineering and company news · Published 2025-04-28 ## [Easy Cross-Platform cgo Builds](https://speedscale.com/blog/easy-cross-platform-cgo-builds/) When I first started writing Go software a little over a decade ago, one of the features I found particularly intriguing was the ability to build... Questions answered in this article (1) * [What about multi platform darwin and windows?](https://speedscale.com/blog/easy-cross-platform-cgo-builds/#what-about-multi-platform-darwin-and-windows) This article was primarily focused on cross-platform container builds, specifically to be run on Kubernetes linux nodes, so native darwin and windows builds were intentionally left out. The xx project does have some support for both of these target platforms, but with some pretty strict… Kubernetes and observability · Published 2026-09-14 ## [eBPF: Correlating rustls Plaintext to TCP Connections Without a File Descriptor](https://speedscale.com/blog/ebpf-rustls-plaintext-tcp-correlation/) Follow an eBPF debugging trail through rustls, Tokio inlining, and an empty map to learn how TLS plaintext gets matched to the right TCP connection. Kubernetes and observability · Published 2026-07-28 ## [eBPF: Preventing Garbage HTTP Payloads When Reading Kernel Scatter-Gather Buffers](https://speedscale.com/blog/ebpf-garbage-http-payloads-scatter-gather-buffers/) How our nettap eBPF agent produced garbage HTTP bodies from kernel iov\_iter scatter-gather buffers, and the CO-RE plus task-local storage fix that made it correct. Questions answered in this article (1) * [What Is Available to TCP eBPF Probes?](https://speedscale.com/blog/ebpf-garbage-http-payloads-scatter-gather-buffers/#what-is-available-to-tcp-ebpf-probes) nettap captures plaintext TCP payloads by attaching BPF fentry and fexit trampolines to tcp\_recvmsg and tcp\_sendmsg, then reading the application’s buffer directly out of the struct msghdr the kernel was given. For tcp\_recvmsg all of the heavy lifting was in the fexit probe since you get both the… Engineering and company news · Published 2024-08-22 ## [Elevating Developer Productivity with Speedscale Ephemeral Environments](https://speedscale.com/blog/developer-productivity-ephemeral-environments/) Speedscale leveraged Ephemeral / Preview Environments to help balance developer productivity and high-quality code by dynamically spinning mini-staging... Questions answered in this article (1) * [What are ephemeral environments?](https://speedscale.com/blog/developer-productivity-ephemeral-environments/#what-are-ephemeral-environments) Ephemeral or Preview Environments help balance the need for developer productivity while maintaining high-quality code. The idea of dynamically spinning “mini-staging” environments up and down on command has enormous promise for increasing experimentation and deployment safety. In theory, it lets… Traffic capture and replay · Published 2025-05-02 ## [Eliminating Flaky Tests with Traffic Replay](https://speedscale.com/blog/eliminating-flaky-tests-with-traffic-replay/) There are few things that can derail developer productivity and undermine your pipeline like a flaky test. Testing is the backbone of a good development... AI development · Published 2025-06-18 ## [Enterprise Vibe Coding](https://speedscale.com/blog/enterprise-vibe-coding/) \_Expanded explanations, guardrails, and practical check-lists included.\_ Vibe coding is a new approach to building software that emphasizes rapid... API mocking · Published 2024-11-18 ## [Ephemeral Data Best Practices Playbook](https://speedscale.com/blog/ephemeral-data/) When it comes to different concepts around data within software development, the concept of ephemeral data is gaining traction. Questions answered in this article (2) * [What is Ephemeral Data?](https://speedscale.com/blog/ephemeral-data/#what-is-ephemeral-data) Ephemeral data, by its nature, is temporary. This data typically has a pretty specific lifespan in terms of duration of time or purpose. In other words, ephemeral data typically exists only as long as it’s useful. After that, the data is processed through an automatic deletion mechanism that… * [Why is Ephemeral Data Important?](https://speedscale.com/blog/ephemeral-data/#why-is-ephemeral-data-important) Ephemeral data is a critical piece of network infrastructure, especially in the modern connected device landscape where privacy, security, and high-efficiency are becoming more and more important by the day. Let’s dig into some of the reasons ephemeral data is so important. API testing · Published 2025-12-08 ## [Ephemeral Environment Testing: Do you need it?](https://speedscale.com/blog/ephemeral-environments-testing/) Traditional testing methods often delay the software development lifecycle, as we have grown used to these outdated processes without considering. Questions answered in this article (3) * [What is Ephemeral Environment Testing?](https://speedscale.com/blog/ephemeral-environments-testing/#what-is-ephemeral-environment-testing) Ephemeral environment testing uses temporary, disposable environments for testing software. These environments mimic production systems by replicating configurations, dependencies, and data structures. However, they exist only for a short time, lasting just for the duration of the test or related… * [How Does Ephemeral Environment Testing Work?](https://speedscale.com/blog/ephemeral-environments-testing/#how-does-ephemeral-environment-testing-work) Generally speaking, ephemeral environment testing involves these three steps: Create an environment that resembles the production or final application deployment environment. Run the tests. Destroy the environment. In practice, developers spin up ephemeral environments using automation and… * [How to Set up Ephemeral Environments for Testing](https://speedscale.com/blog/ephemeral-environments-testing/#how-to-set-up-ephemeral-environments-for-testing) Setting up an ephemeral environment for testing is much like planting a seed that quickly grows, blooms, and then withers away—a process reminiscent of certain plants whose entire life cycle is completed in a matter of days. These environments are like flowers, active and vibrant for a brief period… Engineering and company news · Published 2025-12-29 ## [Essential KPIs for Software Development: Measure Success Effectively](https://speedscale.com/blog/kpis-for-software-development/) In almost all industries, a standard set of KPIs helps to guide teams on whether they are doing the right things in the right ways, with the right. Questions answered in this article (1) * [What are Software Development KPIs?](https://speedscale.com/blog/kpis-for-software-development/#what-are-software-development-kpis) KPIs - or Key Performance Indicators - are quantifiable metrics that help track a software development team’s progress toward a predefined goal. In essence, the KPI gives a metric by which progress can be tracked, giving a signal both when you are pacing toward success and failure. KPIs act as a… AI development · Published 2026-08-13 ## [Explain Non-CPU Latency With Prometheus + proxymock](https://speedscale.com/blog/explain-non-cpu-latency-prometheus-proxymock/) Diagnose a p95 latency regression that CPU profiling cannot explain using Prometheus histograms, then prove the fix with identical proxymock replays. AI development · Published 2026-03-23 ## [FastAPI Testing: Mock LLM APIs for Free](https://speedscale.com/blog/fastapi-mock-llm-apis/) Record real LLM traffic from a FastAPI app, mock it locally, and replay it in CI with proxymock. AI development · Published 2025-09-10 ## [Finding the Ghost in the Machine](https://speedscale.com/blog/finding-the-ghost-in-the-machine/) The industry is rapidly moving towards deeper AI integration than ever before. What was once simply focused on chatbots or recommendation engines has. Questions answered in this article (1) * [What Makes Multi-Agent AI Workflow Automation Different?](https://speedscale.com/blog/finding-the-ghost-in-the-machine/#what-makes-multi-agent-ai-workflow-automation-different) Multi-agent workflows are becoming the backbone of enterprise AI automation, where multiple AI agents collaborate across APIs and services to deliver outcomes that previously required significant engineering investment. These systems provide this functionality while offering a human-friendly… Kubernetes and observability · Published 2026-06-16 ## [Five things your logs will never tell you](https://speedscale.com/blog/five-things-your-logs-will-never-tell-you/) Logs, metrics, and traces are a lossy compression of production. Five things you can do with a traffic data lake that observability can't. Kubernetes and observability · Published 2026-09-11 ## [Five Ways to Use OpenTelemetry Beyond Observability](https://speedscale.com/blog/opentelemetry-beyond-observability/) Teams run inventory, security logs, request routing and billing through OpenTelemetry. Five non-observability uses, and the failure mode of each. Questions answered in this article (4) * [Can OpenTelemetry be used for data other than traces, metrics and logs?](https://speedscale.com/blog/opentelemetry-beyond-observability/#can-opentelemetry-be-used-for-data-other-than-traces-metrics-and-logs) Yes, and it routinely is. The Collector is widely deployed as a general-purpose data pipeline, entity events model infrastructure inventory, baggage carries routing and experiment assignment, and some teams feed usage metrics into billing. The project has also expanded its own scope with profiles,… * [Is OpenTelemetry safe to use for billing or audit data?](https://speedscale.com/blog/opentelemetry-beyond-observability/#is-opentelemetry-safe-to-use-for-billing-or-audit-data) Not on its own. OTLP provides at-least-once delivery and the specification calls duplicate data a deliberate, correct tradeoff for telemetry. Collectors drop under backpressure by design. Anything needing completeness or exactly-once semantics requires deduplication and a durable queue you add… * [What are the limits on OpenTelemetry baggage?](https://speedscale.com/blog/opentelemetry-beyond-observability/#what-are-the-limits-on-opentelemetry-baggage) The W3C Baggage specification requires propagation when the result is 64 list members or fewer and 8192 bytes or less. Past those limits entries may be discarded, and a platform that cannot propagate everything must not propagate partial members. The spec gives no guidance on which keys to drop… * [Should you put request and response payloads in spans?](https://speedscale.com/blog/opentelemetry-beyond-observability/#should-you-put-request-and-response-payloads-in-spans) Usually not. The default limit is 128 attributes per span, backends price on cardinality, and payloads carry PII across a trust boundary. If the goal is reproducing what happened, capture the traffic itself. Traffic capture and replay · Published 2026-06-12 ## [Fixing 403 auth errors when you replay traffic](https://speedscale.com/blog/fix-403-auth-errors-traffic-replay-proxymock/) Replay an authenticated flow and the protected calls fail with 403. Here is how proxymock recommendations fix the expired bearer token in one click. AI development · Published 2026-07-31 ## [Flamegraphs Find It. Replay Proves It.](https://speedscale.com/blog/flamegraphs-find-it-replay-proves-it/) Use Grafana Pyroscope and proxymock with an AI coding agent to find a Go CPU hotspot, preserve API behavior, and verify the performance fix. Traffic capture and replay · Published 2026-04-06 ## [From Datadog to CI Tests: Catch Regressions Before Deploy](https://speedscale.com/blog/from-datadog-to-test-suite/) Learn a practical workflow to convert Datadog metrics, traces, and incidents into CI tests that catch regressions before deploy. Questions answered in this article (1) * [How to pick safe, realistic thresholds](https://speedscale.com/blog/from-datadog-to-test-suite/#how-to-pick-safe-realistic-thresholds) Threshold debates can derail adoption. Keep it mechanical. Start with the last 14 to 30 days of stable production behavior, then define an explicit tolerance band. For example, if p99 sits around 142ms, you can gate at 160ms to absorb normal variance while still catching real regressions. Do the… AI development · Published 2025-05-30 ## [From External Chaos to Business Value: The Power of AI Mocking](https://speedscale.com/blog/from-external-chaos-to-business-value-the-power-of-ai-mocking/) In today’s interconnected software landscape, applications rarely live in isolation. Traffic capture and replay · Published 2025-07-11 ## [From Guesswork to Guarantees: How Traffic Replay Improves Release Confidence](https://speedscale.com/blog/from-guesswork-to-guarantees-how-traffic-replay-improves-release-confidence/) In modern software development, the pressure to move fast is matched only by the need to get it right. API mocking · Published 2026-09-03 ## [From Handwritten Mocks to proxymock: The Complete Loop](https://speedscale.com/blog/handwritten-mocks-to-proxymock/) Part 10 of Getting Started with Mocks: use proxymock to record real API traffic, inject failures, verify side effects, and expose contract drift. Questions answered in this article (2) * [Does proxymock replace unit-test mocks?](https://speedscale.com/blog/handwritten-mocks-to-proxymock/#does-proxymock-replace-unit-test-mocks) No. The package notifier’s function stub is still the fastest way to ask, “Given delayed, should I send a message?” An in-memory fake is still the clearest way to ask whether a second call sees the first write. proxymock answers questions those doubles cannot: what did the application put on the… * [Can an edited RRPair catch contract drift?](https://speedscale.com/blog/handwritten-mocks-to-proxymock/#can-an-edited-rrpair-catch-contract-drift) It catches your response to a contract change. That is valuable because you can make a missing field, changed type, or renamed property happen locally and repeatably. It does not prove the vendor made that change. Use the edited copy on every commit to keep the failure behavior covered. Use fresh… API testing · Published 2025-07-08 ## [From Specs to Reality: True API Testing](https://speedscale.com/blog/from-specs-to-reality-true-api-testing/) Linting - the process of analysing potential issues within your API specification - is a great step towards ensuring that you have strong syntax... Traffic capture and replay · Published 2026-08-19 ## [From Telemetry to Traffic](https://speedscale.com/blog/from-telemetry-to-traffic/) Compare eBPF, sidecars, telemetry agents, OpenTelemetry, APM, and proxies through an evolving ladder of production visibility. AI development · Published 2026-05-18 ## [From Traffic Context to Confirmed Fix in 3 Minutes](https://speedscale.com/blog/traffic-context-confirmed-fix-3-minutes/) Traffic Context is the missing piece in most debugging workflows. We ran our autonomous agent on a real production bug — it found the root cause, wrote a reproduce harness, applied the fix, and confirmed it. Here's what that looked like. Performance testing · Published 2024-02-14 ## [Gatling vs. Speedscale for Kubernetes Load Testing](https://speedscale.com/blog/speedscale-vs-gatling/) Gatling and Speedscale are two popular performance testing tools and load testing web applications. AI development · Published 2024-02-20 ## [Get Ahead of the Game: LLM Compliance and Mocking](https://speedscale.com/blog/get-ahead-of-the-game-llm-compliance-and-mocking/) As Large Language Models (LLMs) become increasingly integrated into enterprise applications, organizations face new challenges around compliance. API testing · Published 2024-03-15 ## [Getting Started with gRPC: A Developer's Guide](https://speedscale.com/blog/getting-started-with-grpc-a-developers-guide/) gRPC (gRPC Remote Procedure Calls) is a modern, open-source, high-performance RPC framework that can run in any environment. Kubernetes and observability · Published 2023-10-17 ## [Getting Started with Skaffold for Kubernetes](https://speedscale.com/blog/getting-started-with-skaffold/) With the explosive growth of Kubernetes over recent years, software engineering teams are facing new challenges: increasing complexity... Questions answered in this article (1) * [How to implement Skaffold](https://speedscale.com/blog/getting-started-with-skaffold/#how-to-implement-skaffold) In this section, you’ll install Skaffold and create a simple project to get a taste of the inner development workflow with Skaffold. Engineering and company news · Published 2024-10-01 ## [Golang Wrapper: Dependency Wrapping, in Go](https://speedscale.com/blog/dependency-wrapping-in-go/) All but the simplest applications borrow code. You could write everything yourself from just core language features but who has time for that? Questions answered in this article (1) * [What is Dependency Wrapping?](https://speedscale.com/blog/dependency-wrapping-in-go/#what-is-dependency-wrapping) Dependency wrapping is a nifty technique in Go programming that involves wrapping a dependency, such as a function or a struct, with another function or struct that provides additional functionality or behavior. Think of it as putting a gift in a box and then wrapping it with beautiful paper. The… Performance testing · Published 2024-10-16 ## [GoReplay vs Speedscale for Kubernetes Load Testing](https://speedscale.com/blog/goreplay-vs-speedscale-kubernetes-load-test-comparison/) GoReplay and Speedscale are two popular tools commonly used for load testing. Both share traffic shadowing as a core feature. Engineering and company news · Published 2024-12-30 ## [Graphql vs GRPC : Key Differences](https://speedscale.com/blog/graphql-vs-grpc/) APIs have never had more connections and requests for data. With variable data types, changing programming languages, and a demand for high performance... Questions answered in this article (5) * [Which is Better: GraphQL or gRPC?](https://speedscale.com/blog/graphql-vs-grpc/#which-is-better-graphql-or-grpc) This is a very hard question to answer - that being said; we can give you an answer based on our specific use case here at Speedscale. * [What’s the difference between GraphQL and gRPC?](https://speedscale.com/blog/graphql-vs-grpc/#whats-the-difference-between-graphql-and-grpc) GraphQL is a client-driven query language over HTTP and JSON, letting clients ask for exactly the data they need from a single endpoint. gRPC is an RPC framework over HTTP/2 and binary Protocol Buffers, focused on exposing service methods with strong typing and bidirectional streaming. GraphQL… * [Why did Speedscale switch from GraphQL to gRPC?](https://speedscale.com/blog/graphql-vs-grpc/#why-did-speedscale-switch-from-graphql-to-grpc) Schema drift. Our backend microservices used protobuf while the front end used a separate GraphQL schema, so every protobuf change had to be duplicated with custom translation logic like converting a map to an array. That was manual, error-prone, and slowed the team down, so we moved the… * [How much more efficient was gRPC than GraphQL for Speedscale?](https://speedscale.com/blog/graphql-vs-grpc/#how-much-more-efficient-was-grpc-than-graphql-for-speedscale) In our migration the web client needed roughly 50 to 90% less processing, and network data volume dropped about 70% on average, with even larger gains when messages had a high metadata-to-payload ratio. Schema drift also started surfacing at compile time instead of at runtime. * [What are the downsides of moving to gRPC-Web?](https://speedscale.com/blog/graphql-vs-grpc/#what-are-the-downsides-of-moving-to-grpc-web) HTTP/2 maturity was the main tax: nginx required all traffic to be HTTP/2 for grpc\_pass to a TLS endpoint, AWS ALB support was thin, we had to maintain certificates for every egress component, and our synthetic monitoring didn’t support HTTP/2. gRPC debugging also needs a new skillset since you… Engineering and company news · Published 2024-12-31 ## [gRPC Golang Example: Using gRPC with Golang](https://speedscale.com/blog/using-grpc-with-golang/) In this tutorial, you will learn how to work with the gRPC Golang library for microservice communication by creating a simple note-taking application. Questions answered in this article (1) * [Why Is gRPC Faster than REST?](https://speedscale.com/blog/using-grpc-with-golang/#why-is-grpc-faster-than-rest) gRPC code utilizes the HTTP/2 protocol, which offers multiple ways to improve performance: Header compression and reuse to reduce the message size Multiplexing to send multiple requests and receive multiple responses simultaneously over a single TCP connection Persistent TCP connections for… Performance testing · Published 2026-10-06 ## [Holiday readiness: run your first load test with skills](https://speedscale.com/blog/holiday-readiness-proxymock-skills/) Start holiday readiness with a local proxymock load test. Use agent skills to record a Node app, mock its API dependency, and inspect the results. AI development · Published 2026-05-06 ## [How a Marketing Intern Ended Up Running Claude in a Terminal](https://speedscale.com/blog/how-a-marketing-intern-ended-up-running-claude-in-a-terminal/) A marketing intern's journey from CMS drag-and-drop to running Claude in a terminal, and why validation still matters as AI speeds up development. AI development · Published 2026-02-12 ## [How AI Coding Is Breaking Synthetic Data Generation](https://speedscale.com/blog/how-ai-coding-is-breaking-synthetic-data-generation/) AI codingagents are accelerating the breakdown of synthetic data generation approaches. Performance testing · Published 2022-12-13 ## [How Load Testing and Mocks Work Together](https://speedscale.com/blog/combining-load-tests-mocks/) If you’ve worked with load testing before, you know that there are a lot of things to consider. API mocking · Published 2024-09-16 ## [How Mock Servers Enhance API Testing Efficiency](https://speedscale.com/blog/using-a-mock-server-understanding-efficient-api-testing/) API testing is critical to modern software development, ensuring that applications communicate seamlessly and function as expected. Kubernetes and observability · Published 2022-07-19 ## [How to Build Multi-Arch Docker Images](https://speedscale.com/blog/how-to-build-multi-arch-docker-images/) With ARM based dev machines and servers becoming more common, it is become increasingly important to build Docker images that support multiple. Performance testing · Published 2025-11-04 ## [How to Calculate TPS for Kubernetes Performance](https://speedscale.com/blog/determine-transactions-per-second/) Transactions-per-Second (TPS) is a valuable metric for evaluating system performance and is highly relevant for engineers overseeing Kubernetes apps. Traffic capture and replay · Published 2026-01-27 ## [How to Capture Network Traffic in Kubernetes](https://speedscale.com/blog/how-to-capture-network-traffic-in-kubernetes/) APIs are the backbone of modern software and enable different systems and applications to communicate seamlessly. API testing · Published 2024-10-22 ## [How to Conduct an HTTP/2 Test on APIs](https://speedscale.com/blog/how-to-test-http-2-apis/) Slowly but surely, HTTP/2 has become the preferred protocol for transferring data files between clients and servers. In contrast, HTTP/1... Questions answered in this article (1) * [What to Consider When Testing HTTP/2 APIs?](https://speedscale.com/blog/how-to-test-http-2-apis/#what-to-consider-when-testing-http2-apis) You might assume HTTP/2 introduces entirely new browser-server interaction features, yet it essentially represents incremental enhancements to the traditional HTTP/1 methods. Let’s go over a few things to consider when testing HTTP/2 APIs. Traffic capture and replay · Published 2026-01-09 ## [How to Do Full-Text Search Across All Application Traffic with Speedscale](https://speedscale.com/blog/how-to-do-full-text-search-across-all-application-traffic-with-speedscale/) This how-to video shows how to use Speedscale's full-text traffic search to instantly find where a specific piece of data appears as it flows through your. API mocking · Published 2026-01-29 ## [How to Get Started with GoMock Playbook](https://speedscale.com/blog/getting-started-gomock/) GoMock is a powerful tool for generating mock objects in Go, making it an essential asset for developers aiming to write advanced unit tests. Questions answered in this article (1) * [What is GoMock and Why Choose It?](https://speedscale.com/blog/getting-started-gomock/#what-is-gomock-and-why-choose-it) GoMock is a testing package provided by the Golang team. It integrates with the rest of the Go ecosystem, like go:generate and the built-in testing package. GoMock isn’t the only Golang testing framework, but it’s the preferred tool for many because of its powerful type-safe assertions. As you’ll… API mocking · Published 2024-04-11 ## [How to Mock APIS in Kubernetes Best Practices](https://speedscale.com/blog/how-to-mock-apis-in-kubernetes/) Mock APIs in Kubernetes are used to simulate actual API requests during API testing. This is useful for detecting issues early in development... Questions answered in this article (1) * [What Is a Mock?](https://speedscale.com/blog/how-to-mock-apis-in-kubernetes/#what-is-a-mock) As mentioned in the introduction, a mock is a kind of simulation where you can make requests to the Kubernetes API server with the goal of getting realistic responses. These responses can be used to analyze traffic, detect failures, improve performance, and more. There are two different kinds of… API mocking · Published 2023-11-21 ## [How to Mock gRPC APIs](https://speedscale.com/blog/mock-grpc-apis/) Developing APIs can be a complex process, particularly when you want to ensure they perform as expected under various real-world conditions. Questions answered in this article (2) * [What is production traffic replication?](https://speedscale.com/blog/mock-grpc-apis/#what-is-production-traffic-replication) Production traffic replication imitates real user interactions by capturing user data in a live environment and then replaying it in a testing environment. For example, if you have an online bookstore, conventional test scenarios might cover common use cases like searching for a book, adding it to… * [What to know about mocking APIs within Kubernetes?](https://speedscale.com/blog/mock-grpc-apis/#what-to-know-about-mocking-apis-within-kubernetes) Learn network implementations, how much of the environment to replicate, and best practices when creating mocks. API mocking · Published 2024-10-18 ## [How to Mock HTTP APIs With MockServer](https://speedscale.com/blog/mockserver-https-apis/) MockServer is a powerful tool for mocking HTTP APIs, making running integration tests more manageable and efficient in the initial development phases. Questions answered in this article (2) * [Why use MockServer to mock APIs?](https://speedscale.com/blog/mockserver-https-apis/#why-use-mockserver-to-mock-apis) As the name suggests, MockServer is a powerful tool that allows developers to mock HTTP APIs, making it much easier and more efficient to run an integration test in initial development phases. It aims to solve the problem of testing APIs that are still in development or not yet available, allowing… * [How to mock HTTP APIs](https://speedscale.com/blog/mockserver-https-apis/#how-to-mock-http-apis) Aiming to provide value to as many as possible, this tutorial will use one of the language-agnostic options: docker-compose. MockServer will be used to establish a mock HTTP API for a hypothetical online game platform. This platform offers a RESTful API that game developers use to fetch player… Performance testing · Published 2022-08-19 ## [How to Test Autoscaling in Kubernetes](https://speedscale.com/blog/how-to-test-kubernetes-autoscaling/) Autoscaling has become increasingly popular with the increased use and further development of cloud technologies, given the new capabilities of platforms. Questions answered in this article (1) * [What is Kubernetes Autoscaling?](https://speedscale.com/blog/how-to-test-kubernetes-autoscaling/#what-is-kubernetes-autoscaling) In any Kubernetes setup, you will have at least one cluster with at least one node. On these nodes, which are essentially just virtual machines, applications will be run inside pods. When you’re working with autoscaling, you’re typically referring to either vertical or horizontal scaling. This… AI development · Published 2025-03-21 ## [How to Test LLM Backend Performance with Service Mocking](https://speedscale.com/blog/testing-llm-backends-for-performance-with-service-mocking/) Test LLM backend latency, throughput, and rate limits without burning API credits. Mock OpenAI and Claude APIs for realistic load testing. Questions answered in this article (3) * [How do you load test an LLM backend without burning API credits?](https://speedscale.com/blog/testing-llm-backends-for-performance-with-service-mocking/#how-do-you-load-test-an-llm-backend-without-burning-api-credits) Record a small sample of real LLM API calls, then use a service mock to replay the responses. This lets you simulate thousands of concurrent users hitting your application while the mock returns realistic responses at a fraction of the cost. * [What metrics matter most for LLM performance testing?](https://speedscale.com/blog/testing-llm-backends-for-performance-with-service-mocking/#what-metrics-matter-most-for-llm-performance-testing) Focus on latency (time-to-first-token and total response time), throughput (requests per second your app can sustain), error rate (timeouts and rate limit hits), and cost per request. Compare these against your provider’s rate limits to find your ceiling. * [Can you test LLM applications in CI/CD without calling the real API?](https://speedscale.com/blog/testing-llm-backends-for-performance-with-service-mocking/#can-you-test-llm-applications-in-cicd-without-calling-the-real-api) Yes. Tools like Proxymock and Speedscale record production LLM traffic and replay it as a mock. Your CI pipeline runs against the mock, getting realistic responses with deterministic behavior — no API key needed, no variable costs, no flaky tests from provider outages. API testing · Published 2025-12-15 ## [How to Test Your React Frontend When the Backend Is Offline](https://speedscale.com/blog/how-to-test-your-react-frontend-when-the-backend-is-offline/) Learn how to test your React frontend without running backend services. Record real API traffic and mock responses for faster development, reliable. Kubernetes and observability · Published 2024-04-08 ## [How to Validate Edge Cases | A Kubernetes Guide](https://speedscale.com/blog/validate-edge-cases-kubernetes/) Optimizing eCommerce sites is a huge endeavor. With these 5 steps, you’ll be able to rapidly identify and resolve your scalability issues: Prioritize. Kubernetes and observability · Published 2026-10-01 ## [How We Rebuilt GitLab CI on GKE Spot VMs](https://speedscale.com/blog/rebuilding-gitlab-ci-on-gke/) How we moved GitLab CI to GKE with shared BuildKit caching, multiple Spot machine types, and an on-demand fallback for scarce capacity. Questions answered in this article (1) * [What about CGO cross-compilation?](https://speedscale.com/blog/rebuilding-gitlab-ci-on-gke/#what-about-cgo-cross-compilation) Most of our services are pure Go, so building and packaging them for multiple platforms is a non-issue. It’s an extremely simple setup: let Go do the cross-compilation, then use a COPY-only Dockerfile to package it. However, a few projects aren’t that simple and require CGO to link against C… Traffic capture and replay · Published 2026-08-25 ## [I built an API traffic classifier for business workflows](https://speedscale.com/blog/reading-business-workflows-out-of-api-traffic/) I pointed a classifier at 7,943 API calls to find business workflows. It worked, then showed where my assumptions about sessions and patterns fell apart. API testing · Published 2025-05-14 ## [I Hate Testing!](https://speedscale.com/blog/i-hate-testing/) Hi everyone, I'm Alan, Head of Customer Success here at Speedscale. If you'd told me a few years ago that I'd be working for a company knee-deep in the. AI development · Published 2026-07-23 ## [Imaginary Test Data. Real Token Bill.](https://speedscale.com/blog/imaginary-test-data-real-token-bill/) Testing AI applications with invented traffic looks fine until real users arrive. Then come the retries, the fallback models, and the token bill. AI development · Published 2025-08-11 ## [Is Your Main Agent Lying? Leverage Multi-agent Workflows to Improve Response Quality](https://speedscale.com/blog/is-your-agent-lying/) Learn how to use Claude Code sub-agents to get a 'second opinion' from other LLMs and build more reliable AI applications. Questions answered in this article (1) * [What’s a Sub-Agent, Really?](https://speedscale.com/blog/is-your-agent-lying/#whats-a-sub-agent-really) Think of a sub-agent as a tiny, self-contained AI. They live as .md files in a .claude/agents directory in your project’s root. For more details on how to implement them, check out the official documentation. Each one has its own: Clean Context Window: This is the most important part. When you call… Performance testing · Published 2024-08-12 ## [Isolating Bottlenecks: How to Determine If Your Slowdown Is Due to the Database or API](https://speedscale.com/blog/isolating-bottlenecks-how-to-determine-if-your-slowdown-is-due-to-the-database-or-api/) Every slowdown in your application can be traced to specific components like a database or an API. Questions answered in this article (1) * [How Can Speedscale Help with Pinpointing Performance Bottlenecks Accurately?](https://speedscale.com/blog/isolating-bottlenecks-how-to-determine-if-your-slowdown-is-due-to-the-database-or-api/#how-can-speedscale-help-with-pinpointing-performance-bottlenecks-accurately) Speedscale provides a reliable way to test and deliver applications by simulating high traffic volumes that can then be used for your different testing scenarios. Speedscale helps you pinpoint performance bottlenecks by first capturing actual traffic from your users in a late-stage environment,… API mocking · Published 2024-08-16 ## [Join Ken on SMC Journal - Scaling Kubernetes, Microservices, and Ephemeral Environments](https://speedscale.com/blog/join-ken-on-smc-journal-scaling-kubernetes-microservices-and-ephemeral-environments/) Check out Ken Ahrens and Scott Moore as they discuss some blockers of developer productivity when building in Kubernetes. Performance testing · Updated 2026-10-12 ## [k6 tutorial: captured traffic with mocked backends](https://speedscale.com/blog/speedscale-k6-tutorial/) Capture API traffic with Speedscale, export a k6 load scenario, and mock backend dependencies in Kubernetes with speedctl or locally with proxymock. Kubernetes and observability · Published 2025-11-18 ## [KubeCon + CloudNativeCon 2025: Recap](https://speedscale.com/blog/kubecon-cloudnativecon-2025-recap/) A marketing intern's high-energy recap of KubeCon 2025: discover major trends in Cloud Native AI, Platform Engineering, Security. Kubernetes and observability · Published 2025-11-25 ## [KubeCon Retrospective: Platform Engineering Needs to Do More Testing](https://speedscale.com/blog/kubecon-retrospective-platform-engineering-needs-to-do-more-testing/) Learn how digital twins and traffic replay, highlighted at kubecon, offer platform engineering teams a 'superpower' to test against real-world scenarios. API mocking · Published 2024-09-19 ## [Kubernetes Developer Environments Guide](https://speedscale.com/blog/kubernetes-developer-environments/) Kubernetes has transformed how developers build, test, and deploy applications, providing a consistent platform for managing containerized workloads. Questions answered in this article (1) * [Why Use Speedscale for Preview Environments?](https://speedscale.com/blog/kubernetes-developer-environments/#why-use-speedscale-for-preview-environments) Speedscale allows developers to replicate real-world traffic in a controlled local environment, enabling thorough testing of new features, bug fixes, and performance improvements. By replaying actual user traffic, Speedscale helps identify potential issues early, providing insights into how… Performance testing · Published 2024-12-23 ## [Kubernetes Load Test Tutorial Playbook](https://speedscale.com/blog/kubernetes-load-test-tutorial/) Performance tests, end-to-end tests, integration tests. There are many different types of tests you can run on your infrastructure. Questions answered in this article (1) * [Why Load Test Kubernetes?](https://speedscale.com/blog/kubernetes-load-test-tutorial/#why-load-test-kubernetes) Performance testing in a Kubernetes environment is essential for ensuring applications can handle high network traffic, scale effectively, and maintain high performance under stress. Conducting distributed load tests allows teams to simulate real-world scenarios, such as thousands of virtual users… Performance testing · Published 2024-10-22 ## [Kubernetes Load Testing Best Practices](https://speedscale.com/blog/kubernetes-load-testing/) Kubernetes has become the dominant orchestration platform for cloud-native apps– and for good reason. Questions answered in this article (1) * [What is the best Kubernetes load-testing tool?](https://speedscale.com/blog/kubernetes-load-testing/#what-is-the-best-kubernetes-load-testing-tool) Based on the evaluation points of this post—ease of use, CI/CD integration, and documentation quality—Speedscale and K6 emerge as strong choices for Kubernetes load testing. Each tool has its pros and cons. Speedscale prefers an Operator approach to setup which allows for much deeper Kubernetes… Performance testing · Published 2022-07-28 ## [Kubernetes Load Testing Comparison: Speedscale vs K6](https://speedscale.com/blog/kubernetes-load-testing-comparison-speedscale-vs-k6/) In this article, you'll be introduced to two different load testing tools that are both able to work with Kubernetes; Speedscale and K6. Questions answered in this article (1) * [How do they Compare?](https://speedscale.com/blog/kubernetes-load-testing-comparison-speedscale-vs-k6/#how-do-they-compare) Speedscale requires more setup in order to make a test, where K6 can be created without any prior setup. Which tool has the advantage depends heavily on what your use case is. K6 can test your services quickly, but you will inevitably also have to be testing the dependencies of your service, unless… Performance testing · Published 2026-01-08 ## [Kubernetes Load Testing Made Easy with Speedscale](https://speedscale.com/blog/kubernetes-load-testing-made-easy/) See how to get visibility into your Kubernetes workloads and run realistic load tests without writing YAML files or kubectl commands. Kubernetes and observability · Published 2024-12-09 ## [Kubernetes vs Docker: 7 Key Differences](https://speedscale.com/blog/kubernetes-vs-docker/) It’s impossible to learn about containerization without hearing about Docker and Kubernetes. These two tools together dominate the world of containers... Questions answered in this article (3) * [How is Kubernetes Different from Docker?](https://speedscale.com/blog/kubernetes-vs-docker/#how-is-kubernetes-different-from-docker) As mentioned in the introduction, these two tools aren’t meant to be substitutions of each other, as they don’t have the same functionality. Because of this, it’s difficult to compare the two tools as it’s like comparing apples and oranges. They look the same, many will even put them in the same… * [Which is Better: Kubernetes or Docker?](https://speedscale.com/blog/kubernetes-vs-docker/#which-is-better-kubernetes-or-docker) As you can see, these two tools serve very different use cases. Rather than trying to figure out which tool to use, it’s more important to figure out when one of these two tools should be used. You’ll often find that you should be implementing both, especially as your company scales. Docker will be… * [Does Kubernetes use Docker?](https://speedscale.com/blog/kubernetes-vs-docker/#does-kubernetes-use-docker) With all this talk about how Docker and Kubernetes work together, you’d imagine that Kubernetes uses Docker under the hood. The truth is that it doesn’t. With Kubernetes, you can choose what runtime you want to use, and at a point, it was indeed possible to use Docker as the container runtime.… AI development · Published 2026-01-11 ## [Let Your LLM Debug Using Production Recordings](https://speedscale.com/blog/observability-with-mcp/) Connect an MCP server to your LLM coding assistant so it can pull real production data on demand, validate its assumptions. AI development · Published 2024-12-19 ## [LLM Testing in 2025: Methods and Strategies](https://speedscale.com/blog/llm-testing/) Large Language Models, or LLMs, have become a near-ubiquitous technology in recent years. Questions answered in this article (1) * [What is LLM Testing?](https://speedscale.com/blog/llm-testing/#what-is-llm-testing) Firstly, let’s define what LLM testing even is. LLM testing is the process of taking a Large Language Model and evaluating it through a series of LLM testing tools. The results of these test scenarios - the LLM outputs - are then rigorously reviewed for everything from quality to speed in… Performance testing · Published 2026-10-05 ## [Load Test PostgreSQL Instantly using Production Recordings](https://speedscale.com/blog/load-test-postgresql-production-recordings/) Record the queries your app sends to PostgreSQL in Kubernetes, then replay them against a QA database as a load and regression test. No scripts to write. Traffic capture and replay · Published 2026-06-02 ## [Logs told me something broke. Traffic showed me what.](https://speedscale.com/blog/logs-told-me-something-broke-traffic-showed-me-what/) Capture production traffic and store it in your own Elasticsearch with Speedscale BYOC. Pull it locally with es-gather.py and reproduce bugs with proxymock. AI development · Published 2025-09-15 ## [Looking Back, Looking Ahead: Thoughts on My First Year at Speedscale](https://speedscale.com/blog/looking-back-looking-ahead-thoughts-on-my-first-year-at-speedscale/) When I started at Speedscale, I looked like this: And after one year of learning, growing, keeping pace with innovation well, let’s just say the journey... API mocking · Published 2026-09-02 ## [Make Failure Boring with Mocks](https://speedscale.com/blog/make-failure-boring/) Part 3 of Getting Started with Mocks: the same seam, now returning refusals, timeouts and nonsense, so the failure paths finally get tested. Engineering and company news · Published 2024-10-31 ## [Mastering Developer Productivity Analytics: A Guide to Boosting Team Efficiency](https://speedscale.com/blog/developer-productivity-analytics/) Developer productivity is ultimately a measure of the efficiency and effectiveness with which software developers produce high-quality code and complete... API mocking · Published 2024-09-04 ## [Mastering Golang Mocks for Efficient Testing and Improved Code Quality](https://speedscale.com/blog/golang-mocks/) Although GoMock is one of the most popular ways to create mocks in Golang, it’s important to understand the broader landscape of mocking methods in the... Questions answered in this article (1) * [Why Do We Need Mocks?](https://speedscale.com/blog/golang-mocks/#why-do-we-need-mocks) Mocks are essential in software development, particularly for testing code in isolation without the unpredictability of real external dependencies. By replacing real components with mocks, developers can focus on testing the logic of their code, leading to more efficient, reliable, and maintainable… Traffic capture and replay · Published 2025-09-08 ## [Mastering Kubernetes Testing with Traffic Replay](https://speedscale.com/blog/mastering-kubernetes-testing-with-traffic-replay/) Kubernetes has become the backbone of many modern application deployment pipelines, and for good reason as a container orchestration platform... Questions answered in this article (2) * [Why Testing Kubernetes is Uniquely Difficult?](https://speedscale.com/blog/mastering-kubernetes-testing-with-traffic-replay/#why-testing-kubernetes-is-uniquely-difficult) The problem with testing in Kubernetes is that there’s some fundamental misalignment between the Kubernetes approach and the approach to testing common in CI/CD pipelines. Kubernetes is a dynamic system - pods are created and destroyed constantly, services scale up and down, and configurations… * [What Traffic Replay Brings to the Table?](https://speedscale.com/blog/mastering-kubernetes-testing-with-traffic-replay/#what-traffic-replay-brings-to-the-table) An alternative approach to replicating in synthetic data is to utilize the actual data from your service. A good process for this is Traffic Replay. Traffic replay is the process of capturing traffic, the actual requests and responses from your API server and the constituent parts in the network,… Performance testing · Published 2025-10-21 ## [Mitmproxy vs Proxymock: Replaying Traffic for Realistic API Testing](https://speedscale.com/blog/mitmproxy-vs-proxymock-for-replay/) A pragmatic comparison of mitmproxy and proxymock for traffic replay. Learn which tool to use for investigative debugging vs developer productivity, how. API mocking · Published 2024-11-04 ## [Mock APIs: A Beginner’s Guide to Mocking Toolsets](https://speedscale.com/blog/mock-api-toolset/) Mock APIs are vital tools in modern software development. They allow developers to simulate APIs and continue testing and development without backend... API mocking · Published 2026-09-02 ## [Mock the Wire](https://speedscale.com/blog/mock-the-wire/) Part 7 of Getting Started with Mocks: a fake HTTP server finally runs the real client, so paths, headers, and parsing get tested. Java, Node, Go, Python. API mocking · Updated 2026-10-12 ## [Mock vs stub: differences and testing examples](https://speedscale.com/blog/mock-vs-stub/) A stub supplies responses; a mock verifies interactions. Compare both with runnable Python examples and learn when API traffic mocks help. Questions answered in this article (6) * [When should you use a stub?](https://speedscale.com/blog/mock-vs-stub/#when-should-you-use-a-stub) Use a stub to put the application into a specific condition. A declined card, an empty search result, or a dependency timeout can be difficult to reproduce on demand against a live service. A stub makes the condition repeatable. For the checkout example, set the gateway response to {"status":… * [When should you use a mock?](https://speedscale.com/blog/mock-vs-stub/#when-should-you-use-a-mock) Use a mock when the application must perform a particular interaction. A payment should use the correct amount. An email should go to the intended recipient. A failed operation might need to avoid writing a success record. Assert the arguments or behavior that express that requirement. Avoid… * [What is the difference between a mock and a stub?](https://speedscale.com/blog/mock-vs-stub/#what-is-the-difference-between-a-mock-and-a-stub) A stub supplies a controlled response. A mock verifies an expected interaction with a dependency. One test-double library can support both uses. * [Can a mock return a stubbed response?](https://speedscale.com/blog/mock-vs-stub/#can-a-mock-return-a-stubbed-response) Yes. A mock object can return configured responses and record calls. The assertions determine whether the test checks application output, interactions, or both. * [Are mocks better than stubs?](https://speedscale.com/blog/mock-vs-stub/#are-mocks-better-than-stubs) Choose based on the requirement. Use response stubbing to test outcomes under controlled conditions and interaction verification when a dependency call is part of the contract. * [What is the difference between a unit-test mock and an API mock server?](https://speedscale.com/blog/mock-vs-stub/#what-is-the-difference-between-a-unit-test-mock-and-an-api-mock-server) A unit-test mock replaces an object inside a process. An API mock server supplies responses across a network boundary and may also verify received requests. Performance testing · Published 2025-11-24 ## [Mocking PostgreSQL the Easy Way: Simplifying Testing with Speedscale Proxymock](https://speedscale.com/blog/mocking-postgresql-the-easy-way-simplifying-testing-with-speedscale-proxymock/) Record real PostgreSQL traffic with proxymock and replay it deterministically. No more local database setup, no more seeded test data. Engineering and company news · Published 2024-09-05 ## [Modern Development Environments Playbook](https://speedscale.com/blog/modern-development-environments/) A development environment is a crucial setup of tools, configurations, and processes that developers use to build, test, and deploy software. Performance testing · Published 2025-03-12 ## [Modernize Test Data Management with Traffic Replay](https://speedscale.com/blog/modernize-test-data-management-with-traffic-replay/) In software testing or platform engineering, having realistic data is crucial. For years, teams have relied on Test Data Management (TDM) to copy entire... Kubernetes and observability · Published 2026-01-20 ## [Moving Our Observability Data Collector from Sidecars to eBPF](https://speedscale.com/blog/speedscale-moves-observability-data-collector-sidecars-ebpf/) Speedscale transitions from Kubernetes sidecar-based observability collection to eBPF for lower latency, reduced resource consumption. API mocking · Published 2025-10-15 ## [MySQL Mocking with Speedscale's Proxymock: A Complete Guide](https://speedscale.com/blog/mysql-mocking-with-speedscales-proxymock-a-complete-guide/) Record real MySQL traffic with proxymock and replay it in tests. Eliminate local database setup and flaky CI runs. Questions answered in this article (1) * [What is MySQL and Why Mock It?](https://speedscale.com/blog/mysql-mocking-with-speedscales-proxymock-a-complete-guide/#what-is-mysql-and-why-mock-it) MySQL is one of the world’s most popular open-source relational database management systems (RDBMS). It powers countless applications, from small web apps to enterprise-grade systems. But when it comes to local development and CI/CD testing, running a full MySQL instance can be unnecessary or… AI development · Published 2026-08-12 ## [Observe Opaque Services With OpenTelemetry eBPF + proxymock](https://speedscale.com/blog/observe-opaque-service-opentelemetry-ebpf-proxymock/) Discover endpoints, RED metrics, and traces in an opaque Kubernetes service with OpenTelemetry eBPF Instrumentation, then replay traffic with proxymock. Kubernetes and observability · Published 2026-04-09 ## [OpenTelemetry Trace Testing for CI Release Gates](https://speedscale.com/blog/otel-trace-testing-ci-release-gates/) Trace-based testing uses OpenTelemetry traces as replayable test input so CI catches production regressions before deploy, not after incident review. Questions answered in this article (1) * [How to choose the first workflow to validate](https://speedscale.com/blog/otel-trace-testing-ci-release-gates/#how-to-choose-the-first-workflow-to-validate) Do not start with a giant “replay everything” initiative. Start narrow. Pick one workflow with all three traits: High user impact (auth, checkout, provisioning) Frequent change velocity Existing incident history Then ship one deterministic replay gate for that path. Once the team trusts it, expand… API mocking · Published 2024-08-21 ## [Optimizing DevOps with Kubernetes Ephemeral Environments: Efficient Testing and Deployment](https://speedscale.com/blog/optimizing-kubernetes-ephemeral-environments/) Ephemeral environments transform software development by providing temporary, isolated spaces for testing and deploying microservices without affecting... Traffic capture and replay · Published 2026-02-15 ## [Oracle JDK to OpenJDK: A Guide to Reliable Migration Testing](https://speedscale.com/blog/how-to-migrate-oracle-java-to-openjdk-with-traffic-replay/) Record production traffic on Oracle JDK, replay it on OpenJDK, and catch every regression before users do. A step-by-step Speedscale guide. API mocking · Published 2025-01-08 ## [Orchestrated Service Virtualization: The Definitive Guide](https://speedscale.com/blog/orchestrated-service-virtualization/) Software development requires a lot of things to be highly optimized due to the sheer number of parts and the interconnected nature of those parts. Questions answered in this article (1) * [What is Orchestrated Service Virtualization?](https://speedscale.com/blog/orchestrated-service-virtualization/#what-is-orchestrated-service-virtualization) Orchestrated Service Virtualization is a service virtualization solution which allows you to create simulations of interconnected services, APIs, and their constituent parts within a controlled environment. In effect, you are creating a simulation of the build given a certain constraint or target,… Traffic capture and replay · Published 2021-07-16 ## [Packet Capture Without "tcpdump" for Go Apps in Kubernetes](https://speedscale.com/blog/packet-capture-without-tcpdump/) Every developer knows there are some utilities that are completely indispensable from their workflows. The \_programmer's toolbelt,\_ if you will. Traffic capture and replay · Published 2025-10-21 ## [Part 1: Building a Production-Grade Traffic Capture and Replay System](https://speedscale.com/blog/how-to-build-a-traffic-capture-system/) Learn how to build a production-grade traffic capture system using proxies, eBPF, and tcpdump. Traffic capture and replay · Published 2025-10-31 ## [Part 2: Building a Production-Grade Traffic Capture, Transform and Replay System](https://speedscale.com/blog/how-to-build-a-traffic-transform-system/) Learn how to build a traffic analysis tool for network traffic transformation. Complete guide covering traffic analysis techniques, parsing. Questions answered in this article (4) * [Why Transform Network Traffic?](https://speedscale.com/blog/how-to-build-a-traffic-transform-system/#why-transform-network-traffic) Traffic analysis reveals that transformation turns noisy, environment-specific network traffic into stable, portable artifacts you can reuse. Make replay deterministic: replace timestamps, UUIDs, and tokens so runs are repeatable. Improve portability: adapt prod-shaped traffic to dev/CI/staging… * [How do you keep traffic replay from being flaky?](https://speedscale.com/blog/how-to-build-a-traffic-transform-system/#how-do-you-keep-traffic-replay-from-being-flaky) Find and normalize the dynamic tokens. Detectors catch ISO-8601 timestamps, UUIDs, JWTs, and high-entropy secrets, and transform rules replace them (timestamps to now(), UUIDs to uuid()). The hard cases span multiple requests, like a JWT that gets mutated across an OAuth flow, so the classifier has… * [How do you safely use production data in tests?](https://speedscale.com/blog/how-to-build-a-traffic-transform-system/#how-do-you-safely-use-production-data-in-tests) Redact at transform time with a layered approach: exact regexes, then ML or NLP classifiers, then human overrides. For fidelity, instead of blanking a value you can replace it with one of the same shape, so a redacted customer number still looks like a customer number during replay. * [Where should transform rules live?](https://speedscale.com/blog/how-to-build-a-traffic-transform-system/#where-should-transform-rules-live) Outside the data. Transforms are rules about the data, not the data itself, so keep them as small text artifacts (YAML or JSON) in version control near your tests. That makes re-runs comparable, keeps review safe, and lets you promote rule bundles from dev to CI to staging like code. Traffic capture and replay · Published 2025-11-12 ## [Part 3: Building a Production-Grade Traffic Capture and Replay System](https://speedscale.com/blog/how-to-build-a-traffic-replay-system/) Learn how to build a traffic replay system that validates services with production data. Questions answered in this article (4) * [What is traffic replay?](https://speedscale.com/blog/how-to-build-a-traffic-replay-system/#what-is-traffic-replay) Traffic replay takes captured request and response pairs and sends the requests at your service under test to validate a change against real production patterns. It catches the edge cases, timing dependencies, and integration bugs that simple hand-written tests miss. * [What makes traffic replay hard?](https://speedscale.com/blog/how-to-build-a-traffic-replay-system/#what-makes-traffic-replay-hard) Three things. State mismatch, because captured traffic references data that only exists in production. Time staleness, because timestamps and tokens expire. And non-determinism, because responses contain generated UUIDs and timestamps, so exact byte comparison fails every time. You solve them with… * [Should I replay against real dependencies or mocks?](https://speedscale.com/blog/how-to-build-a-traffic-replay-system/#should-i-replay-against-real-dependencies-or-mocks) For most cases, replay inbound requests to your service with a live database but mock the downstream dependencies from captured outbound traffic. That is the sweet spot: you can run repeatedly, validate responses in detail, and never risk corrupting production data. Shadow traffic is fast but risky… * [How do you know a replay passed?](https://speedscale.com/blog/how-to-build-a-traffic-replay-system/#how-do-you-know-a-replay-passed) Define objective quality gates instead of eyeballing it: status pass rate at or above 99%, JSON-path body match rate at or above 95% with timestamps and UUIDs ignored, p95 latency delta within +10%, and mock match rate at or above 98% with zero unmatched calls. Promotion between phases is automatic… API testing · Published 2025-08-05 ## [Peeking Under the Hood of Cursor's API Calls](https://speedscale.com/blog/peeking-under-the-hood-of-cursor/) Cursor is one of the go-to AI-native code editors for developers. Because it’s built on Visual Studio Code, it provides a pretty smooth path between... Questions answered in this article (4) * [What does Cursor send to its servers when you prompt it?](https://speedscale.com/blog/peeking-under-the-hood-of-cursor/#what-does-cursor-send-to-its-servers-when-you-prompt-it) On a prompt, Cursor sends a gRPC request to api2.cursor.sh containing your workspace launch.json, relevant code snippets (the first 4K of each selected file), a bulk upload of your directory structure, and your repository’s git status. On a large monorepo that is a lot of directory walking. * [Can Cursor leak secrets in my project?](https://speedscale.com/blog/peeking-under-the-hood-of-cursor/#can-cursor-leak-secrets-in-my-project) It can if you put them where it looks. Cursor uploads your launch.json verbatim, so anything sensitive left in it, like an AWS\_SESSION\_TOKEN or an API key, goes to the server with it. Keep secrets in dotenv or envrc and turn on Privacy Mode in a corporate setting. * [Which AI models does Cursor use in auto mode?](https://speedscale.com/blog/peeking-under-the-hood-of-cursor/#which-ai-models-does-cursor-use-in-auto-mode) Its GetDefaultModelNudgeData endpoint returned a portfolio that included Claude 3.7 Sonnet (thinking and max), Gemini 2.0 Flash, GPT-4o-mini, Claude 3.5 Haiku, and DeepSeek v3 and r1. Auto mode is not a static pick, Cursor nudges you between models server-side based on context and subscription… * [How can I see what Cursor sends myself?](https://speedscale.com/blog/peeking-under-the-hood-of-cursor/#how-can-i-see-what-cursor-sends-myself) Wrap it with proxymock, which records complete API requests and responses and converts binary protobuf and gRPC into readable JSON. That is how we decoded these calls. It is like Wireshark for developers instead of packet spelunkers. API testing · Published 2025-12-29 ## [Peeking Under the Hood with Claude Code](https://speedscale.com/blog/peeking-under-the-hood-with-claude-code/) Claude is one of the go-to AI-native code editors for developers. It provides a smooth and simple chat-based CLI that is easy to understand. Questions answered in this article (4) * [What does Claude Code send to Anthropic when you prompt it?](https://speedscale.com/blog/peeking-under-the-hood-with-claude-code/#what-does-claude-code-send-to-anthropic-when-you-prompt-it) Your prompt goes to api.anthropic.com/v1/messages as plain JSON, along with the model version and, through structured tool calls, whatever it reads from your working directory such as directory listings and file contents. It uses REST rather than the gRPC that Cursor uses, which tends to survive… * [Does Claude Code change my prompt before running it?](https://speedscale.com/blog/peeking-under-the-hood-with-claude-code/#does-claude-code-change-my-prompt-before-running-it) Yes. In our capture it rewrote a short prompt into a longer, more specific set of instructions before executing, and it broke the task into sub-tasks and parallel tool calls on its own. It behaves like a project manager, not just a raw model call. * [Can Claude Code run commands on my machine?](https://speedscale.com/blog/peeking-under-the-hood-with-claude-code/#can-claude-code-run-commands-on-my-machine) It can request to. The remote model issues structured tool calls that can run things on your local desktop, gated by Claude’s permissions and sandboxing. What is in your working directory is effectively context it can read, so think about what lives there. * [What telemetry does Claude Code collect?](https://speedscale.com/blog/peeking-under-the-hood-with-claude-code/#what-telemetry-does-claude-code-collect) A lot. Command-level events go to statsig.anthropic.com (Statsig is owned by OpenAI) and detailed logs go to Datadog, tagged by model and user, down to token counts, cost, and flags like is\_running\_with\_bun. Sticky organization, account, and user identifiers tie the events together. API mocking · Published 2024-12-03 ## [Platform Engineering vs. DevOps](https://speedscale.com/blog/platform-engineering-vs-devops/) Many engineering organizations have recently begun adopting the practice of platform engineering as a way to increase the velocity of new features being... Questions answered in this article (4) * [What is Platform Engineering?](https://speedscale.com/blog/platform-engineering-vs-devops/#what-is-platform-engineering) Platform engineering is an approach that focuses on building and maintaining a centralized and reusable platform for developers within an organization. This platform offers a methodology to streamline software development and deployment processes. It allows a self-service capability that empowers… * [How is Platform Engineering Different from DevOps?](https://speedscale.com/blog/platform-engineering-vs-devops/#how-is-platform-engineering-different-from-devops) The term Platform Engineering (PE) continues to evolve, but fundamentally, it encompasses the practice of building and maintaining the foundational infrastructure and systems that support business-critical applications. That usually means pursuing excellence in the domains of continuous integration… * [Which is Better: Platform Engineering or DevOps?](https://speedscale.com/blog/platform-engineering-vs-devops/#which-is-better-platform-engineering-or-devops) Choosing between Platform Engineering and DevOps comes down to the organization’s specific needs, goals, and challenges. Both options are strong choices, and in many cases, they are complimentary, not competing. For this reason, it’s better to consider this question in terms of the strengths of… * [Which Should You Choose?](https://speedscale.com/blog/platform-engineering-vs-devops/#which-should-you-choose) If your organization is in the early stages of adopting agile or DevOps principles, starting with DevOps practices is an excellent option as it lays the groundwork for collaboration and automation. For mature organizations facing scalability challenges, platform engineering can complement existing… Performance testing · Updated 2026-10-12 ## [Postman load testing: a practical API tutorial](https://speedscale.com/blog/postman-load-test-tutorial/) Run a Postman performance test, choose virtual users, inspect latency and errors, and isolate dependencies with recorded API mocks. Questions answered in this article (4) * [Can Postman do load testing?](https://speedscale.com/blog/postman-load-test-tutorial/#can-postman-do-load-testing) Yes. Use the Collection Runner Performance mode to run virtual users concurrently. A functional collection run with repeated iterations is a different test. * [Can Postman run a load test in the cloud?](https://speedscale.com/blog/postman-load-test-tutorial/#can-postman-run-a-load-test-in-the-cloud) Postman supports cloud performance runs on eligible paid plans. This tutorial uses the desktop App runner because its target is a localhost API. * [Are virtual users the same as requests per second?](https://speedscale.com/blog/postman-load-test-tutorial/#are-virtual-users-the-same-as-requests-per-second) No. Virtual users repeat a request workflow. Its length and response times affect the throughput the test produces. * [Can I use proxymock with a Postman load test?](https://speedscale.com/blog/postman-load-test-tutorial/#can-i-use-proxymock-with-a-postman-load-test) Yes. Postman can send inbound HTTP requests while proxymock supplies recorded responses for downstream dependencies. Configure unmatched-request behavior for the isolation the test needs. Traffic capture and replay · Published 2026-03-24 ## [Production Data Access for Developers: RBAC and DLP](https://speedscale.com/blog/production-data-in-developer-hands-rbac-and-dlp/) RBAC and DLP let developers access production data safely—without configuration drift or PII exposure. Here's how to design it right. AI development · Published 2026-03-13 ## [Prompt, Deploy, Pray Is Dead: Validating AI Code with Proxymock](https://speedscale.com/blog/prompt-deploy-pray-is-dead/) AI-generated code is moving fast—but without behavioral validation, you're gambling with production stability. See how Proxymock changes the equation. Kubernetes and observability · Published 2024-12-24 ## [Python Observability : A Complete Guide](https://speedscale.com/blog/python-observability/) Observability is a critical element of modern software development, unlocking awareness across complex and distributed systems with ease. Questions answered in this article (2) * [What is Python Observability?](https://speedscale.com/blog/python-observability/#what-is-python-observability) Python observability refers to the ability of a developer or provider to monitor and understand the flow and state of data within a Python application. This is often done through the analysis of traffic and data such as logs, metrics, traces, attributes of data, telemetry, and other states. Whereas… * [Why Observability is Critical for Python Applications?](https://speedscale.com/blog/python-observability/#why-observability-is-critical-for-python-applications) Python code is used in an incredibly diverse set of use cases and industries - it’s likely that, even if you didn’t know it, you interacted with Python at some point today. Accordingly, this ubiquity across simple to complex use cases shows that Python is powerful but diverse - and it is this… Performance testing · Published 2025-10-10 ## [QA Debt: The Silent Risk That Can Take Down Your Business](https://speedscale.com/blog/qa-debt-the-silent-risk-that-can-take-down-your-business/) Don't let 'QA debt' derail your career and company. Unlike technical debt, this invisible accumulation of missed tests and shortcuts builds silently. AI development · Published 2025-06-17 ## [R-RAG: Building a Resilient Retrieval-Augmented Generation Service](https://speedscale.com/blog/r-rag-building-a-resilient-retrieval-augmented-generation-service/) Retrieval-augmented generation (RAG) has quickly become the architecture of choice for enterprises building AI applications that require access to. Engineering and company news · Published 2024-04-29 ## [Reducing Engineering Cost using Contract Developers](https://speedscale.com/blog/reducing-engineering-cost-using-contract-developers/) Outsourced engineering teams are gaining in popularity and many investors have started to treat them as a requirement. Questions answered in this article (4) * [What Does a Seed-Stage CTO/VP of Eng do?](https://speedscale.com/blog/reducing-engineering-cost-using-contract-developers/#what-does-a-seed-stage-ctovp-of-eng-do) Before I go further, I want to make sure we want the same things. Prior to product-market-fit (PMF), I believe my job as CTO or VP of Engineering at Speedscale to be limited to the following goals: Minimize time between product experimentation and customer feedback. Drop the cost of producing each… * [Is Code Actually Your Core Intellectual Property?](https://speedscale.com/blog/reducing-engineering-cost-using-contract-developers/#is-code-actually-your-core-intellectual-property) It’s never been cheaper and easier to bring a SaaS business app to market and you may not want to pay full-price local engineers for some kinds of work. “Web forms on top of databases” is a well worn path and that type of engineering will be most impacted by these kinds of trends. That doesn’t mean… * [How to Pick the Best Partner?](https://speedscale.com/blog/reducing-engineering-cost-using-contract-developers/#how-to-pick-the-best-partner) You’ll notice that I use the word “partner” instead of “vendor” and this is intentional. A good outsourcing partner can give you access to top shelf talent in a part of the world you could never reasonably access yourself and at a reasonable cost. The best partner can really accelerate your ability… * [How do I know if it’s working out?](https://speedscale.com/blog/reducing-engineering-cost-using-contract-developers/#how-do-i-know-if-its-working-out) For project-based work it’s important to remember that you can give up the management of the people but never give up your management of the project. Here are a few tips to keep things on track: Secure Senior Technical Review - Maybe you have a hotshot CTO that can do regular code reviews. Maybe… AI development · Published 2026-01-29 ## [Refactor Safely with AI: Using MCP and Traffic Replay to Validate Code Changes](https://speedscale.com/blog/ralph-wiggum-loop-traffic-replay-mcp/) Use traffic replay via MCP to create a tight feedback loop for AI coding agents, preventing hallucinated success by validating against immutable. Performance testing · Published 2024-04-04 ## [Regression Test Performance Best Practices](https://speedscale.com/blog/regression-test-performance/) Regression testing is not a new concept. However, historically, it has been limited to functional testing due to the setup, configuration... Questions answered in this article (3) * [What is software “performance”?](https://speedscale.com/blog/regression-test-performance/#what-is-software-performance) Software performance refers to how effectively a software application responds to specific demands. Performance encompasses several key aspects, including load time, responsiveness, and the efficiency with which it processes data. Performance metrics are vital for gauging an application’s health… * [What is software “regression”?](https://speedscale.com/blog/regression-test-performance/#what-is-software-regression) Software regression occurs when new changes introduce errors in existing parts of a software application. Regressions are typically seen more once software products become increasingly more complex. * [What causes software regression?](https://speedscale.com/blog/regression-test-performance/#what-causes-software-regression) Software regressions come from errors while programming around existing code. This could be a bug fix that resolves the original issue but introduces another issue. Regressions could also result from poor configuration file changes which cause unexpected behavior down the line. Even if these… AI development · Published 2026-08-19 ## [Reliability Engineering in the AI Era](https://speedscale.com/blog/drop-the-site/) See why reliability engineering must span code, testing, telemetry, and incidents as AI agents erase the boundary between pre-production and production. Traffic capture and replay · Published 2026-04-19 ## [Replace API Synthetics with Traffic Replay](https://speedscale.com/blog/replace-api-synthetics-with-traffic-replay/) UI synthetics only tell you something is broken. Traffic replay per microservice isolates failures before any human walks up. Zero scripts required. Traffic capture and replay · Published 2026-04-30 ## [Replay Real Customer API Sessions as Datadog Synthetics Tests](https://speedscale.com/blog/isolate-a-user-session-in-datadog-synthetics-with-proxymock/) Export recorded proxymock traffic to Datadog Synthetics in one command. Auth headers redacted, global variables created. No scripting, no flaky journeys. AI development · Published 2026-08-13 ## [Reproduce A Rare Retry Path With Loki + proxymock](https://speedscale.com/blog/reproduce-rare-retry-path-loki-proxymock/) Find the rare payload that sends a service down a retry path, correlate it to the recorded response, and prove the fix with proxymock replay. Performance testing · Published 2024-02-23 ## [Revolutionize Platform Engineering with Traffic Replay](https://speedscale.com/blog/traffic-replay-for-platform-engineering/) Platform engineers focus on developing an internal developer platform to increase velocity during the software development process. Questions answered in this article (1) * [Which Performance Metrics to Monitor?](https://speedscale.com/blog/traffic-replay-for-platform-engineering/#which-performance-metrics-to-monitor) Once you’ve implemented the tooling for traffic replication, you need to identify which performance metrics you’ll actually monitor. Most cloud platforms and APIs can use the following as a starting point: Request duration: The average time taken for each request to be served. Network latency: The… API testing · Published 2026-01-20 ## [ROI of Digital Twin Testing: Cut Testing Costs by 50%](https://speedscale.com/blog/roi-of-testing-with-a-digital-twin/) Non-production environments cost 20-40% of cloud bills. Digital twin testing delivers 9x ROI through infrastructure, incident, and efficiency savings. Questions answered in this article (1) * [What is a Digital Twin for Software Testing?](https://speedscale.com/blog/roi-of-testing-with-a-digital-twin/#what-is-a-digital-twin-for-software-testing) Before we dive into ROI calculations, let’s clarify what we mean by “digital twin” in the context of testing. A digital twin for testing is a lightweight replica of your production system that uses real traffic patterns instead of synthetic test data. Unlike traditional staging environments that… AI development · Published 2026-04-23 ## [Run Local LLMs on Mac to Cut Claude Costs](https://speedscale.com/blog/local-llms-on-mac-cost-savings/) A practical hybrid workflow that uses costly LLM APIs for planning and local models (via Ollama + OpenCode) for execution, guarded by deterministic evals. AI development · Published 2026-02-16 ## [Runtime Validation vs Static Analysis: Why You Need Both](https://speedscale.com/blog/runtime-validation-vs-static-analysis/) Static analysis catches code smells. Runtime validation catches behavioral failures. Enterprise teams adopting AI coding tools need both to ship safely. Questions answered in this article (6) * [What Does Static Analysis Actually Catch?](https://speedscale.com/blog/runtime-validation-vs-static-analysis/#what-does-static-analysis-actually-catch) Static analysis tools like SonarQube, ESLint, Checkstyle, and Qodo scan source code without executing it. They identify problems by examining the code’s structure, syntax, and known vulnerability patterns. What static analysis is good at: Code smells and style violations. Unused variables, overly… * [What Does Runtime Validation Catch That Static Analysis Misses?](https://speedscale.com/blog/runtime-validation-vs-static-analysis/#what-does-runtime-validation-catch-that-static-analysis-misses) Runtime validation tests code against actual production traffic patterns. Instead of analyzing code in isolation, it replays real API calls, database queries, and service-to-service interactions against the changed code and compares the behavior to a known baseline. Runtime validation catches… * [Is runtime validation the same as integration testing?](https://speedscale.com/blog/runtime-validation-vs-static-analysis/#is-runtime-validation-the-same-as-integration-testing) No. Integration tests use synthetic data in pre-configured environments. Runtime validation replays actual production traffic. The difference is coverage: production traffic contains edge cases, timing patterns, and data shapes that synthetic tests never include. Integration tests verify what you… * [Does runtime validation slow down CI/CD pipelines?](https://speedscale.com/blog/runtime-validation-vs-static-analysis/#does-runtime-validation-slow-down-cicd-pipelines) It adds minutes, not hours. A typical replay of captured traffic for a single service takes 2-5 minutes depending on traffic volume. Compare that to the hours or days spent debugging a production incident caused by a behavioral regression that static analysis and unit tests missed. * [Can static analysis tools evolve to catch behavioral failures?](https://speedscale.com/blog/runtime-validation-vs-static-analysis/#can-static-analysis-tools-evolve-to-catch-behavioral-failures) Some static tools are adding AI-powered analysis that attempts to reason about runtime behavior. These are useful incremental improvements but fundamentally limited: you cannot determine how code behaves with real data without actually running it with real data. This is the halting problem in… * [What if we don’t have production traffic to replay?](https://speedscale.com/blog/runtime-validation-vs-static-analysis/#what-if-we-dont-have-production-traffic-to-replay) You can start by capturing traffic from any environment where real or realistic requests are flowing — staging, QA, or even local development with proxymock. Production traffic provides the highest fidelity, but any real traffic is better than synthetic test data for catching behavioral regressions. Performance testing · Published 2024-09-06 ## [Seasonal Holiday Readiness Testing with Production Traffic](https://speedscale.com/blog/testing-with-production-traffic/) Many businesses depend on seasonal products, offerings, and campaigns. Seasonal traffic usually refers to high traffic levels because of festival seasons. Questions answered in this article (1) * [What Is Seasonal Traffic?](https://speedscale.com/blog/testing-with-production-traffic/#what-is-seasonal-traffic) E-commerce is one of the most prominent examples of industries that experience seasonal traffic spikes during events. To give you an idea of the scale, Amazon’s Prime Day in 2023 generated 15.35 trillion requests on EBS. While only a few companies in the world get to that scale, many companies… AI development · Published 2026-08-13 ## [Separate Application Latency From Network Failure With Hubble](https://speedscale.com/blog/separate-app-latency-network-failure-hubble-proxymock/) Use Cilium Hubble flow evidence and proxymock replay to prove whether a Kubernetes timeout came from your code, a dependency, or a dropped packet. API mocking · Published 2024-02-15 ## [Service Mocking with Internal Developer Platforms](https://speedscale.com/blog/internal-developer-platforms-service-mocking/) With the growing prevalence of cloud-native environments, platform teams' infrastructures are increasingly dependent on various integrated APIs. Questions answered in this article (1) * [How Does Service Mocking Enhance an Internal Developer Platform?](https://speedscale.com/blog/internal-developer-platforms-service-mocking/#how-does-service-mocking-enhance-an-internal-developer-platform) Service mocking as part of your reference architectures can ensure your services are efficiently integrated for all possible interactions, thus improving software quality and easing infrastructure management. It’s especially useful in unit testing, where you test individual components or functions,… Kubernetes and observability · Published 2022-08-05 ## [Setting up a Multi-Architecture Kubernetes Cluster](https://speedscale.com/blog/setting-up-a-multi-architecture-kubernetes-cluster/) In the last post we covered the industry shift towards ARM machines for both local and production software engineering. API testing · Published 2025-10-27 ## [Settle Your QA Debt Before the Bugs Start Breaking Kneecaps](https://speedscale.com/blog/settle-your-qa-debt-before-the-bugs-start-breaking-kneecaps/) Practical strategies to eliminate QA bottlenecks and build resilient testing pipelines Performance testing · Published 2025-08-26 ## [Shift Left on Performance Testing – Without Killing Developer Velocity](https://speedscale.com/blog/shift-left-on-performance-testing-without-killing-developer-velocity/) Traditional performance testing often comes late in the delivery cycle, typically just before release. Questions answered in this article (5) * [What Is Shift Left Testing?](https://speedscale.com/blog/shift-left-on-performance-testing-without-killing-developer-velocity/#what-is-shift-left-testing) Shift Left testing is a proactive approach to software testing where testing activities, such as deploying functional tests, API tests, unit testing, and even performance testing, are moved to the early stages of the software development lifecycle. Instead of waiting until the final testing phase,… * [What Makes Something “Shift Left”?](https://speedscale.com/blog/shift-left-on-performance-testing-without-killing-developer-velocity/#what-makes-something-shift-left) Key characteristics of Shift Left testing include: Early Bug Detection: Catching defects when they’re cheaper and faster to fix. Continuous Feedback: Integrating test results into every step of the development cycle. Comprehensive Testing: Running unit tests, integration tests, and contract testing… * [Why Shift Left Performance Testing Matters?](https://speedscale.com/blog/shift-left-on-performance-testing-without-killing-developer-velocity/#why-shift-left-performance-testing-matters) Despite all this, the benefits of shift left are obvious and quite alluring. Early Bug Detection: Detect performance bottlenecks, latency issues, or resource contention before production, reducing costly rework. Defining clear performance requirements early in the process helps guide testing… * [What About Shift Right?](https://speedscale.com/blog/shift-left-on-performance-testing-without-killing-developer-velocity/#what-about-shift-right) While Shift Left emphasizes early validation, many readers are likely wondering about Shift Right testing. Shift Right testing focuses on validating in production environments or real-world scenarios. Cloud performance testing plays a crucial role here, as it evaluates application performance… * [What Makes Something “Shift Right”?](https://speedscale.com/blog/shift-left-on-performance-testing-without-killing-developer-velocity/#what-makes-something-shift-right) Key aspects of Shift Right testing include: User Feedback and Monitoring: Gathering insights from real users to detect performance issues, usability concerns, or unexpected behaviors. Continuous Monitoring: Tracking network traffic, application access, security posture, and resource usage in live… Performance testing · Published 2025-12-05 ## [Shopify Outage 2025: Rise of the Commerce Kaiju](https://speedscale.com/blog/shopify-outage-2025-rise-of-the-commerce-kaiju/) Shopify's infrastructure crumbled in 2025 like a city under a 'Commerce Kaiju' attack. AI development · Published 2026-02-11 ## [Silent Failures: Why AI Code Breaks in Production](https://speedscale.com/blog/silent-failures-why-ai-code-compiles-but-breaks-in-production/) AI-generated code compiles clean but breaks in production. Learn why static analysis misses behavioral failures and how runtime validation catches them. Questions answered in this article (2) * [Does runtime validation replace unit tests?](https://speedscale.com/blog/silent-failures-why-ai-code-compiles-but-breaks-in-production/#does-runtime-validation-replace-unit-tests) No. Unit tests verify individual functions work as designed. Runtime validation verifies that the entire service behaves correctly with real production data. They test different things and catch different bugs. * [Can runtime validation work with microservices?](https://speedscale.com/blog/silent-failures-why-ai-code-compiles-but-breaks-in-production/#can-runtime-validation-work-with-microservices) Yes. Speedscale captures traffic at the service boundary, so each microservice can be validated independently against its actual production traffic. This is especially valuable for teams running 50-200+ services where maintaining test environments is expensive. API mocking · Published 2024-09-19 ## [Simplifying AWS Testing: A Guide to AWS SDK Mock](https://speedscale.com/blog/simplifying-aws-testing-a-guide-to-aws-sdk-mock/) Testing AWS services is an essential step in creating robust cloud applications. Performance testing · Published 2024-08-31 ## [Simulating Database Performance Under Load with Speedscale](https://speedscale.com/blog/validate-database-performance-under-load/) Big data storage tools like BigQuery, Hadoop, and Cassandra are used to manage large volumes of structured and unstructured data generated by modern... Questions answered in this article (1) * [Why Simulate Big Data Database Tools for Performance Testing?](https://speedscale.com/blog/validate-database-performance-under-load/#why-simulate-big-data-database-tools-for-performance-testing) Tools like BigQuery are fundamental in database management because they provide the infrastructure needed to handle large volumes of structured and unstructured data. These tools enable distributed storage and parallel processing, thus allowing you to manage petabytes of data across multiple… AI development · Published 2025-09-12 ## [Simulating Multi-Agent Workflows to Find Hidden API Vulnerabilities](https://speedscale.com/blog/simulating-multi-agent-workflows-to-find-hidden-api-vulnerabilities/) API gateways are often viewed as the centralized entry point for client HTTP requests in a distributed system. Engineering and company news · Published 2025-03-19 ## [Six Lessons from Production gRPC](https://speedscale.com/blog/six-lessons-from-production-grpc/) In the half-decade since gRPC became part of our production ecosystem, we’ve encountered a range of challenges and discovered a few hidden pitfalls that. Questions answered in this article (4) * [What are the main challenges of running gRPC in production?](https://speedscale.com/blog/six-lessons-from-production-grpc/#what-are-the-main-challenges-of-running-grpc-in-production) HTTP/2 quirks (TLS end-to-end, inconsistent H2C upgrades, status codes buried in trailers, spotty firewall support), binary protobuf payloads that aren’t human-readable, protobuf-to-JSON dropping default values, and connection management where streams can hang. Most of it comes down to needing… * [Why is gRPC hard to debug?](https://speedscale.com/blog/six-lessons-from-production-grpc/#why-is-grpc-hard-to-debug) The payloads are binary protobuf, so you can’t read them in a browser or text editor without the .proto files and a decoder. HTTP/2 carries gRPC status codes in trailers that many tools hide, and the transport layer is abstracted, so you often can’t tell whether a message is truly in flight or just… * [Why do fields go missing when converting protobuf to JSON?](https://speedscale.com/blog/six-lessons-from-production-grpc/#why-do-fields-go-missing-when-converting-protobuf-to-json) Protocol Buffers omit default values in JSON output. If an enum or field is set to its default (like 0), the serialized JSON just drops that key. It’s efficient but confusing, especially without the .proto on hand, so document how defaults behave or generate JSON that includes them. * [What does a successful gRPC SendMsg actually mean?](https://speedscale.com/blog/six-lessons-from-production-grpc/#what-does-a-successful-grpc-sendmsg-actually-mean) That the message was queued successfully, not that it was sent. The real send happens asynchronously through gRPC’s internal scheduling and channel logic, so a success from SendMsg doesn’t guarantee delivery. Use debug logs or OpenTelemetry gRPC tracing to see what’s actually in flight. AI development · Published 2025-08-01 ## [Speeding up AI Coding Assistants using Deterministic Feedback](https://speedscale.com/blog/why-we-built-proxymock/) Every engineering leader has seen it: a senior developer is “in the zone”…then Slack pings, CI fails, or an AI suggestion derails everything. AI development · Published 2026-02-18 ## [Speedscale Launches proxymock OpenClaw Skill on ClawHub](https://speedscale.com/blog/speedscale-launches-proxymock-openclaw-skill-on-clawhub/) Speedscale launches proxymock as an OpenClaw skill on ClawHub, bringing traffic replay and production context to Claude for improved reliability. Questions answered in this article (1) * [What is the proxymock OpenClaw Skill?](https://speedscale.com/blog/speedscale-launches-proxymock-openclaw-skill-on-clawhub/#what-is-the-proxymock-openclaw-skill) The proxymock skill integrates our traffic replay tool with Claude, enabling developers to record, inspect, mock, replay, and generate API traffic without leaving their AI-assisted development environment. By observing production traffic in minute detail, proxymock adds critical context for AI… AI development · Published 2026-02-13 ## [Speedscale Named in Gartner® Market Guide for API Testing](https://speedscale.com/blog/gartner-market-guide-api-mcp-testing-tools/) Speedscale is a Representative Vendor in the Gartner Market Guide for API and MCP Testing Tools. See how traffic replay modernizes testing. AI development · Published 2025-11-06 ## [Speedscale Proxymock: Freely testing cloud native apps alongside AI code assistants](https://speedscale.com/blog/speedscale-proxymock-freely-testing-cloud-native-apps-alongside-ai-code-assistants/) Testing AI-generated code in cloud-native apps? Speedscale Proxymock provides a free tool for mock API endpoints and realistic sandboxes based on real. API mocking · Published 2025-01-15 ## [Speedscale vs Coder: Ephemeral Developer Environments for Different Needs](https://speedscale.com/blog/speedscale-vs-coder/) Compare Speedscale and Coder for developer productivity in 2025. Speedscale offers production traffic replay and API mocking for realistic testing. AI development · Published 2024-10-17 ## [Speedscale vs Jmeter Kubernetes Load Testing](https://speedscale.com/blog/speedscale-vs-jmeter-kubernetes-load-testing-comparison/) At some point, your development team may be considering implementing load testing (also known as stress testing) as part of your software testing process. Questions answered in this article (1) * [What are the Best Tools for Kubernetes Load Testing?](https://speedscale.com/blog/speedscale-vs-jmeter-kubernetes-load-testing-comparison/#what-are-the-best-tools-for-kubernetes-load-testing) If you’ve set up your infrastructure and want to add load tests, choosing a load testing framework can be tricky. Both Speedscale and JMeter are great options, but Speedscale is one of the best tools for Kubernetes load testing, as it was specifically built for this purpose. Speedscale is a more… Performance testing · Published 2024-07-15 ## [Speedscale vs. HyperTest: API Testing Comparison](https://speedscale.com/blog/speedscale-vs-hypertest/) Compared to UI testing, API testing can often feel abstruse because it primarily focuses on the underlying code and is mainly performed at the. API mocking · Published 2026-01-09 ## [Speedscale vs. LocalStack for Realistic Mocks](https://speedscale.com/blog/localstack-alternative/) API mocking plays a crucial role in modern software development allowing developers to simulate external API endpoints. Questions answered in this article (1) * [What are Speedscale and LocalStack?](https://speedscale.com/blog/localstack-alternative/#what-are-speedscale-and-localstack) Let’s dive into what these two API mocking tools are and how they mock cloud services. Performance testing · Published 2024-07-02 ## [Speedscale vs. SmartBear ReadyAPI for API Testing](https://speedscale.com/blog/speedscale-vs-smartbear-readyapi/) Application programming interface (API) testing helps verify that endpoints behave as expected, handle various inputs correctly, return the appropriate... AI development · Published 2025-07-22 ## [Speedscale: Avoid Regulatory Icebergs with Traffic Replay, and Save Money](https://speedscale.com/blog/speedscale-avoid-regulatory-icebergs-with-traffic-replay-and-save-money/) It has never been more critical to establish a solid foundation for regulatory compliance. Regulations govern a wide range of functions. API testing · Published 2026-03-03 ## [Spring Boot API Testing: A Practical Guide for Enterprise Teams](https://speedscale.com/blog/spring-boot-api-testing/) Enterprise Spring Boot APIs need more than unit tests. Learn how to test external service integrations, JWT auth, production edge cases with real traffic. Questions answered in this article (4) * [Does traffic replay replace WireMock for Spring Boot testing?](https://speedscale.com/blog/spring-boot-api-testing/#does-traffic-replay-replace-wiremock-for-spring-boot-testing) No. WireMock is still useful for deterministic integration tests where you need precise control over responses. Traffic replay complements WireMock by providing realistic test data derived from actual API responses. Many teams use WireMock for contract tests and traffic replay for regression tests.… * [What Java version does this work with?](https://speedscale.com/blog/spring-boot-api-testing/#what-java-version-does-this-work-with) The demo app runs on Java 17 with Spring Boot 3.1. proxymock and Speedscale work with any Java version and any Spring Boot version because they operate at the network level, not the JVM level. Your application’s HTTP traffic is captured and replayed regardless of the Java runtime. * [How do you handle API keys and secrets in recorded traffic?](https://speedscale.com/blog/spring-boot-api-testing/#how-do-you-handle-api-keys-and-secrets-in-recorded-traffic) proxymock and Speedscale support redaction rules that strip sensitive data from recordings. API keys, passwords, and PII can be masked or replaced with tokens before the recording is stored. For the demo app, the HMAC secret is configured in application.properties and JWT tokens are regenerated… * [Can AI coding agents use captured traffic while generating code?](https://speedscale.com/blog/spring-boot-api-testing/#can-ai-coding-agents-use-captured-traffic-while-generating-code) Yes. Speedscale’s MCP integration exposes captured traffic to AI agents like Cursor and Claude Code. The AI can see real request/response pairs from production while generating handler code, closing the context gap that causes most AI-generated code failures. API testing · Published 2025-08-11 ## [Stop Guessing with OAuth: Understanding CI/CD](https://speedscale.com/blog/stop-guessing-with-oauth-understanding-ci-cd/) OAuth 2.0 is the leading open authorization framework that enables secure delegated access to protected resources. Questions answered in this article (1) * [Why Synthetic Tests Miss Critical Bottlenecks?](https://speedscale.com/blog/stop-guessing-with-oauth-understanding-ci-cd/#why-synthetic-tests-miss-critical-bottlenecks) It might be tempting to just throw as much synthetic data at the problem as possible and validate that your OAuth flows work. Unfortunately, synthetic testing is often quite problematic. Simple synthetic tests generate uniform HTTP requests, but they lack the dynamics of real OAuth clients and… Kubernetes and observability · Published 2024-10-04 ## [Stop Using TCP Health Checks for Kubernetes Applications](https://speedscale.com/blog/stop-using-tcp-health-checks-for-kubernetes/) As developers, one of the most important things we can consider when designing and building applications is the ability to know if our application is. Questions answered in this article (2) * [What Are Container Probes?](https://speedscale.com/blog/stop-using-tcp-health-checks-for-kubernetes/#what-are-container-probes) Container probes are diagnostic checks that run periodically against containers within a pod. The outcome of these checks allows Kubernetes to control aspects of a pod’s lifecycle, with kubernetes liveness probes being crucial for maintaining application health. In other words, they can help… * [How Should I Configure Container Probes?](https://speedscale.com/blog/stop-using-tcp-health-checks-for-kubernetes/#how-should-i-configure-container-probes) Container probes, including liveness probe configuration, are defined as a part of your application’s pod spec with several options available, most importantly being the mechanism by which they are executed. Kubernetes provides four mechanisms that can be used: exec: probes of this type will… Kubernetes and observability · Published 2024-10-28 ## [Streamlining Your Kubernetes Development Environment: A Comprehensive Guide](https://speedscale.com/blog/kubernetes-development-environment/) Kubernetes has revolutionized how modern applications are built, deployed, and scaled. However, due to its complexity, managing a Kubernetes development... Traffic capture and replay · Published 2026-08-13 ## [Synthetic Monitoring Is Broken. Your Production Traffic Can Fix It.](https://speedscale.com/blog/synthetic-monitoring-is-broken-production-traffic-can-fix-it/) Synthetic monitoring depends on scripts engineers maintain by hand. Capturing and replaying real production transactions turns customer behavior into tests. AI development · Published 2025-05-30 ## [Take Control of Your AI Routing: Mocking Claude, Gemini, and GPT-4](https://speedscale.com/blog/take-control-of-your-ai-routing-mocking-claude-gemini-and-gpt-4/) A few short years ago, the idea of using a Large Language Model was relegated to some specific models and implementations for a given industry or use case. Kubernetes and observability · Published 2026-09-18 ## [Team-Based DLP: Give Each Group Its Own Redaction Rules](https://speedscale.com/blog/team-based-dlp-group-rules/) One forwarder, many teams, one DLP rule nobody wants to touch. Scoped group rules let each team own its redaction. How-to for proxymock web and Speedscale. Questions answered in this article (2) * [How to set it up in proxymock web](https://speedscale.com/blog/team-based-dlp-group-rules/#how-to-set-it-up-in-proxymock-web) proxymock web is the place to write a rule next to the traffic it has to redact. Rules are workspace files at proxymock/dlprules/.json, so they can be reviewed in a pull request like any other change. 1. Create the rule. Open DLP Rules under Config and click + New. The template is already a… * [How to set it up in the Speedscale dashboard](https://speedscale.com/blog/team-based-dlp-group-rules/#how-to-set-it-up-in-the-speedscale-dashboard) Teams that manage rules in Speedscale Cloud get the same model in the dashboard. Open DLP Rules, create or pick a rule, and open the Scope tab. Choose Group rule, fill in Owner, and name the workloads. The summary line above the tabs states in one sentence what the rule is and what it covers. The… API mocking · Published 2026-09-02 ## [Test Behavior, Not Choreography](https://speedscale.com/blog/test-behavior-not-choreography/) Part 5 of Getting Started with Mocks: a test that pinned the retry schedule broke on a change no customer could notice. Here is how to rewrite it. AI development · Published 2025-11-25 ## [Test Code Changes with Claude Code Using Real Traffic](https://speedscale.com/blog/test-code-changes-with-claude-code-using-real-traffic/) Claude Code can write features and fix bugs, proxymock traffic snapshots give me the integration tests, replays. Performance testing · Published 2026-09-24 ## [Test PostgreSQL With the Queries Your App Actually Runs](https://speedscale.com/blog/postgres-load-regression-testing-real-queries/) Replay recorded PostgreSQL queries to catch schema regressions and run realistic database load tests with proxymock, using the CLI or an AI assistant. Performance testing · Published 2026-09-25 ## [Test Your MySQL 8.4 Upgrade With Real App Queries](https://speedscale.com/blog/mysql-load-regression-testing-real-queries/) Replay your app's recorded MySQL statements against 8.4 to catch upgrade regressions, then load test the database with the same workload using proxymock. AI development · Published 2025-10-07 ## [Testing AI Code in CI/CD Made Simple for Developers](https://speedscale.com/blog/testing-ai-code-in-cicd-made-simple-for-developers/) Generative AI can produce code faster than humans, and developers feel more productive with it integrated into their IDEs. Questions answered in this article (1) * [How to Integrate AI Code Testing into Your CI/CD Pipeline](https://speedscale.com/blog/testing-ai-code-in-cicd-made-simple-for-developers/#how-to-integrate-ai-code-testing-into-your-cicd-pipeline) CI/CD is built around four stages: source (commit) stage, build stage, testing stage, and deploy stage. Since AI-generated code can introduce security vulnerabilities and quality issues, it’s important to incorporate AI-specific tests across each stage of the CI/CD pipeline. Source stage: The first… API testing · Published 2026-01-28 ## [Testing Golang with httptest Best Practices](https://speedscale.com/blog/testing-golang-with-httptest/) \_Go\_, often referred to as \_Golang\_, is a popular programming language built by Google. Its design and structure help you write efficient, reliable... Traffic capture and replay · Published 2024-12-05 ## [Testing Kubernetes Ingress with Production Traffic](https://speedscale.com/blog/test-kubernetes-ingress/) Kubernetes is an incredibly powerful solution, but testing the Kubernetes Ingress resources themselves can prove to be quite tricky. Questions answered in this article (2) * [Why Ingress Testing Fails - Misalignment and Data?](https://speedscale.com/blog/test-kubernetes-ingress/#why-ingress-testing-fails---misalignment-and-data) These faults can happen for a large variety of reasons, ranging from simple ingress rules mismatches to more complex issues with load balancers or web servers. With ingress specifically, the problem often has to do with a fundamental misalignment between the data being used in testing and the… * [Is Traffic Replay the Optimal Approach?](https://speedscale.com/blog/test-kubernetes-ingress/#is-traffic-replay-the-optimal-approach) In this post, you’ve seen just a simple example of how traffic replay can help you test your Ingress resources, but this is only the tip of the iceberg. Kubernetes and observability · Published 2026-03-27 ## [The 4 Golden Signals of Monitoring Explained](https://speedscale.com/blog/golden-signals/) Learn the 4 golden signals — latency, traffic, errors, and saturation — and how to use them for monitoring, alerting, and pre-release testing. Questions answered in this article (8) * [What are the Golden Signals?](https://speedscale.com/blog/golden-signals/#what-are-the-golden-signals) There are many different variables that can be tracked to understand system performance and system health. Fortunately, right now, there are a couple of common frameworks we can borrow from: Google SRE Handbook on Monitoring Distributed Systems with the Four Golden Signals: latency, traffic,… * [Why Golden Signals Matter?](https://speedscale.com/blog/golden-signals/#why-golden-signals-matter) The Golden Signals are an incredibly powerful set of metrics that unlock a variety of insights into system health and potential tool integrations. The Golden Signals concept is based around providing as much information as possible around system stability, user demand, resource allocation, and… * [What Should You Do with the Golden Signals?](https://speedscale.com/blog/golden-signals/#what-should-you-do-with-the-golden-signals) The Golden Signals provide some incredible benefits and use cases. Let’s take a look at a few of them. * [How to Detect Anomalies in Your System](https://speedscale.com/blog/golden-signals/#how-to-detect-anomalies-in-your-system) Detecting anomalies in your system leverages the Golden Signals as a foundational metric, testing actual system performance against a preferred baseline. There are quite a few techniques that can be deployed to make this process more effective. * [What are the 4 golden signals of monitoring?](https://speedscale.com/blog/golden-signals/#what-are-the-4-golden-signals-of-monitoring) The 4 golden signals are latency (how long requests take), traffic (how much demand your system handles), errors (the rate of failed requests), and saturation (how full your system’s resources are). They were defined by Google’s SRE team as the minimum metrics needed to understand system health. * [What is the difference between golden signals and the USE method?](https://speedscale.com/blog/golden-signals/#what-is-the-difference-between-golden-signals-and-the-use-method) Golden signals (latency, traffic, errors, saturation) focus on user-facing service health. The USE method (utilization, saturation, errors) focuses on infrastructure resource health. Golden signals tell you “is the user experience good?” while USE tells you “are the servers healthy?” Most teams use… * [How do you use golden signals for testing, not just monitoring?](https://speedscale.com/blog/golden-signals/#how-do-you-use-golden-signals-for-testing-not-just-monitoring) Capture production traffic and replay it against a pre-release build. Measure the golden signals during replay and compare them to your production baselines. If latency spikes, throughput drops, or error rates increase, you’ve caught a regression before it reaches users. Tools like Speedscale… * [Which tools are best for monitoring golden signals?](https://speedscale.com/blog/golden-signals/#which-tools-are-best-for-monitoring-golden-signals) Prometheus and Grafana are the most common open-source stack. Datadog, New Relic, and Dynatrace are popular commercial options. For pre-release golden signal validation, Speedscale measures all four signals during traffic replay and compares them against production baselines automatically. Performance testing · Published 2026-02-16 ## [The 6 Best Performance Testing Tools Guide](https://speedscale.com/blog/the-6-best-performance-testing-tools/) Compare the top 6 performance testing tools, Speedscale, JMeter, Locust, Gatling, NeoLoad, k6, across features, pricing, integrations, reliability. AI development · Published 2026-06-04 ## [The AI Code Explosion: Why Your Mocking Strategy is Breaking Down](https://speedscale.com/blog/ai-code-explosion-mocking-strategy-breaking-down/) AI-generated code breaks traditional mocking. Here's how BYOC capture and replay with proxymock keeps verification grounded in real production traffic. Performance testing · Published 2026-07-04 ## [The API tests passed. The database didn't.](https://speedscale.com/blog/compare-sql-between-runs/) Our v2 release looked clean in HTTP tests until we diffed the SQL workload — an N+1 loop, a startup migration, and 70 ms of extra DB time hiding in plain sight. Here's how to compare two releases without database access. AI development · Published 2026-07-27 ## [The Best Model Is a Routing Decision](https://speedscale.com/blog/the-best-model-is-a-routing-decision/) The best model isn't the smartest — it's whichever should get the next unit of work. Notes from NVIDIA on routing, local models, and the AI factory. Performance testing · Published 2026-01-15 ## [The CES Hangover: 3 Expensive Hardware Fails That Were Actually Software Problems](https://speedscale.com/blog/the-ces-hangover-3-expensive-hardware-fails-that-were-actually-software-problems/) Stop letting third-party API spikes crash your app. Learn why mocking latency for OpenAI, Anthropic. Kubernetes and observability · Published 2026-08-27 ## [The Compounding Platform Tax](https://speedscale.com/blog/the-compounding-platform-tax/) Security controls rarely break a banking platform alone. Their cumulative divergence from Kubernetes standards creates a compounding maintenance tax. AI development · Published 2025-09-30 ## [The Developer’s Guide to Debugging AI-Generated Code](https://speedscale.com/blog/the-developers-guide-to-debugging-ai-generated-code/) Master debugging AI-generated code by spotting flawed logic, removing deprecated APIs, and catching hallucinated functions before they ship. Questions answered in this article (5) * [How to Give Better Prompts for Cleaner Code](https://speedscale.com/blog/the-developers-guide-to-debugging-ai-generated-code/#how-to-give-better-prompts-for-cleaner-code) The quality of AI-generated code is directly correlated with the quality of the prompts you provide. By improving your prompting technique, you can significantly reduce debugging overhead and achieve more reliable code from the outset. Be Specific About Context: Instead of asking “write a function… * [Why does AI code often include non-existent functions?](https://speedscale.com/blog/the-developers-guide-to-debugging-ai-generated-code/#why-does-ai-code-often-include-non-existent-functions) AI models predict what code should look like based on training patterns, but they can’t actually check if functions exist in real libraries. They’ll confidently create pandas.DataFrame.merge\_smart() or combine elements from different libraries into something that sounds right but doesn’t work. It’s… * [Can I trust AI to write production-level code?](https://speedscale.com/blog/the-developers-guide-to-debugging-ai-generated-code/#can-i-trust-ai-to-write-production-level-code) AI-generated code can be a solid starting point, but don’t ship it blindly. Treat it like code from a junior developer—useful, but needs review and testing. With proper debugging workflows and tools like proxymock for real traffic validation, AI-generated code can definitely work in production.… * [What’s the best way to verify AI-generated logic?](https://speedscale.com/blog/the-developers-guide-to-debugging-ai-generated-code/#whats-the-best-way-to-verify-ai-generated-logic) Layer your validation: write unit tests for edge cases, use traffic replay tools to test with real data patterns, do manual code reviews for business logic, and run static analysis tools. AI code breaks in creative ways, so you need multiple approaches to catch everything. * [How can I avoid AI coding hallucinations?](https://speedscale.com/blog/the-developers-guide-to-debugging-ai-generated-code/#how-can-i-avoid-ai-coding-hallucinations) You can’t eliminate them completely, but better prompting helps a lot. Be specific about libraries and versions, paste in documentation when needed, and always validate against official docs. Using tools like proxymock to test against real production scenarios will quickly show you when the AI made… Engineering and company news · Published 2024-10-29 ## [The DevEx Advantage: Understanding and Improving Developer Experience](https://speedscale.com/blog/improving-developer-experience/) Developer Experience (DevEx) is a general term that encompasses all of the interactions a developer has with their work environment. Questions answered in this article (1) * [What Makes a Good Developer Experience?](https://speedscale.com/blog/improving-developer-experience/#what-makes-a-good-developer-experience) This, of course, raises the question: what makes a Developer Experience good? While there are as many development preferences as there are developers in the world, some general categories should be focused on to deliver an exceptional developer experience. AI development · Published 2026-05-15 ## [The DIY Traffic Replay Trap: Why AI Scripts Fail at Scale](https://speedscale.com/blog/ai-intern-trap-diy-traffic-replay-scalability-nightmare/) AI-generated scripts seem like a quick win, but DIY traffic replay tools become a maintenance nightmare at scale. Here's why Speedscale beats the prompt. AI development · Published 2026-03-20 ## [The Hidden AI Bill: Why Non-Prod LLM Costs Spiral](https://speedscale.com/blog/llm-simulation-missing-runtime-enterprise-ai-agents/) Production AI spend gets attention. Non-prod LLM calls in development, CI, and load tests often do not. Simulation fixes that. API testing · Published 2025-06-27 ## [The Hidden Cost of API Security Misconfigurations - And How to Catch Them Early](https://speedscale.com/blog/the-hidden-cost-of-api-security-misconfigurations-and-how-to-catch-them-early/) Security misconfiguration remains one of the most persistent and preventable causes of API vulnerabilities today. Questions answered in this article (1) * [How to Prevent Security Misconfigurations](https://speedscale.com/blog/the-hidden-cost-of-api-security-misconfigurations-and-how-to-catch-them-early/#how-to-prevent-security-misconfigurations) Preventing security misconfigurations takes more than good intentions. It requires proactive effort, automation, and embedded security awareness. Regular api security testing is essential to identify vulnerabilities in APIs and ensure that security controls like authentication and rate limiting are… Kubernetes and observability · Published 2026-05-27 ## [The Kubeshark Workflow That Doesn't Stop at the Dashboard](https://speedscale.com/blog/proxymock-observability-with-nettap/) A Kubeshark alternative that goes beyond observability. Stream live cluster traffic into proxymock, then replay or mock it locally from your laptop. Kubernetes and observability · Published 2026-03-26 ## [The Observability Gap: Why Monitoring Data Should Drive Tests](https://speedscale.com/blog/the-observability-gap/) Teams spend six figures on observability but test with synthetic data. Close the gap between what you know about production and what you validate pre-release. Questions answered in this article (2) * [What’s the difference between observability-driven testing and just using production data for tests?](https://speedscale.com/blog/the-observability-gap/#whats-the-difference-between-observability-driven-testing-and-just-using-production-data-for-tests) “Using production data” typically means copying a database snapshot into staging. Observability-driven testing is more precise: it captures the actual API traffic (requests, responses, timing) flowing through your services and replays it as tests. You’re not just using production data. You’re using… * [How do you handle PII and sensitive data in captured traffic?](https://speedscale.com/blog/the-observability-gap/#how-do-you-handle-pii-and-sensitive-data-in-captured-traffic) Production traffic must be sanitized before replay. This means stripping PII fields, redacting payment data, and rewriting auth tokens. Speedscale and proxymock handle this automatically via configurable DLP rules that scrub sensitive data before it leaves the capture pipeline. The sanitized… AI development · Published 2026-01-21 ## [The PII Testing Dilemma](https://speedscale.com/blog/the-pii-testing-dilemma/) Software is hard to test when production data contains PII and AI systems are causing an explosion in bugs. AI development · Published 2026-08-11 ## [The Pod Was Cheaper. The Service Wasn’t.](https://speedscale.com/blog/the-cheaper-pod-cost-more/) Use OpenCost and proxymock to prove Kubernetes rightsizing lowers cost per successful request without hiding behavior or throughput regressions in testing. AI development · Published 2025-07-16 ## [The Silent API Killer: Data Coupling in Your Tests](https://speedscale.com/blog/the-silent-api-killer-data-coupling-in-your-tests/) In API testing, speed, accuracy, and confidence in test results are everything. Regardless of whether you're validating functionality... Questions answered in this article (5) * [What Is Data Coupling in API Testing?](https://speedscale.com/blog/the-silent-api-killer-data-coupling-in-your-tests/#what-is-data-coupling-in-api-testing) So, what is data coupling at its core? Data coupling occurs when your testing is overly dependent on the specific state of the data layer. Issues such as pre-populated database records, static user IDs, or shared data setups between test cases can undermine the test results and the inferences based… * [Why Is This a Big Deal?](https://speedscale.com/blog/the-silent-api-killer-data-coupling-in-your-tests/#why-is-this-a-big-deal) While it may seem like a minor inconvenience, data coupling has far-reaching consequences across your API lifecycle: False confidence - your test results may look green, but they’re green for the wrong reasons. Regression risks - seemingly unrelated changes to the database schema or seed data can… * [What Should API Testing Look Like?](https://speedscale.com/blog/the-silent-api-killer-data-coupling-in-your-tests/#what-should-api-testing-look-like) To avoid data coupling, API testing needs to embrace isolation, repeatability, and determinism. Your tests should: Spin up and tear down their own test data Avoid assumptions about the application’s state Run reliably in parallel and in CI/CD Validate only the API layer, not downstream systems or… * [What to Look for in API Testing Tools?](https://speedscale.com/blog/the-silent-api-killer-data-coupling-in-your-tests/#what-to-look-for-in-api-testing-tools) When choosing or evaluating your API testing platform, look for platforms that support: Test data generation and cleanup CI/CD pipeline integration Test automation for functional API testing Load testing and performance monitoring Security testing and API validation Replay-based testing (traffic… * [Why Speedscale Is Your Best Defense Against Data Coupling?](https://speedscale.com/blog/the-silent-api-killer-data-coupling-in-your-tests/#why-speedscale-is-your-best-defense-against-data-coupling) If data coupling is the silent API killer, Speedscale is your shield. Traditional API testing tools often assume clean environments, stable data, and perfectly isolated services - but that’s rarely the case in modern software systems. Speedscale flips the script by bringing real traffic into your… AI development · Published 2026-06-30 ## [The Three Pillars Were Built for Humans](https://speedscale.com/blog/three-pillars-were-built-for-humans/) Metrics, logs, and traces were built for humans and cheap storage. AI inverts both assumptions, and the next maturity level is a deterministic replay sandbox. Engineering and company news · Published 2025-12-11 ## [The Ultimate Guide to a Smooth Dev Environment](https://speedscale.com/blog/the-ultimate-guide-to-a-smooth-dev-environment-setup-tips-and-best-practices/) Setting up a development environment can be challenging, especially for new developers or those adapting to new developer tools. Performance testing · Published 2024-12-27 ## [The Ultimate Guide to REST API Testing: Best Practices and Tools](https://speedscale.com/blog/rest-api-testing/) APIs might not always be in the spotlight, but they’re the unsung heroes of just about every modern software project. Questions answered in this article (1) * [What is API Testing and Why is it Important?](https://speedscale.com/blog/rest-api-testing/#what-is-api-testing-and-why-is-it-important) API testing is a critical part of the software development process. It ensures that Application Programming Interfaces, or APIs, function as intended and designed. Testing these APIs requires some best practices and tools, especially when considering specific forms and functions, such as RESTful… Performance testing · Published 2026-02-12 ## [The Ultimate Stress Test: Kim Jong Un, a Parachute, and a Multi-Billion Dollar Prop Bet](https://speedscale.com/blog/the-ultimate-stress-test-kim-jong-un-a-parachute-and-a-multi-billion-dollar-prop-bet/) From memes to market meltdowns: Explore how a multi-billion dollar Super Bowl prop bet involving Kim Jong Un pushed prediction markets and SRE teams to. API mocking · Published 2026-09-02 ## [They Aren't All Mocks](https://speedscale.com/blog/they-arent-all-mocks/) Part 6 of Getting Started with Mocks: stub, spy, fake, mock, and dummy, sorted by what each one does. Java, Node, Go, Python. API testing · Updated 2026-07-20 ## [Top 14 Postman Alternatives for API Testing in 2026](https://speedscale.com/blog/top-14-postman-alternatives/) A rebuilt 2026 guide to Postman alternatives. Which API clients are still maintained, what they cost, and which one fits local-first, gRPC, or team workflows. Performance testing · Published 2024-07-08 ## [Top 5 JMeter Alternatives](https://speedscale.com/blog/top-5-jmeter-alternatives/) Load tests ensure applications perform well under heavy loads and traffic spikes. Performance testing · Published 2024-06-21 ## [Top 5 K6 Alternatives](https://speedscale.com/blog/top-5-k6-alternatives/) K6 is an open source performance testing tool that lets developers and QA engineers simulate load on a system to identify performance bottlenecks before. API mocking · Published 2026-02-02 ## [Top 7 Kubernetes Chaos Engineering Tools](https://speedscale.com/blog/kubernetes-chaos-engineering-tools/) Developing highly resilient Kubernetes deployments is crucial for ensuring that your hosted applications in Kubernetes can effectively manage and recover. API mocking · Published 2024-03-25 ## [Top 8 API Mocking Tools and Methodologies](https://speedscale.com/blog/api-mocking-tools/) API mocking plays a critical role in software development to isolate the system under test, reducing dependencies across teams, streamlining the entire... Questions answered in this article (3) * [How to mock HTTP APIs with MockServer](https://speedscale.com/blog/api-mocking-tools/#how-to-mock-http-apis-with-mockserver) Get The Tutorial Consider a situation where a developer is working on an HTTP-based API for a complex online marketplace. Developers can define detailed requests and responses for each service. This enables thorough testing of each component in isolation, as well as their interplay, without relying… * [How to get started with GoMock](https://speedscale.com/blog/api-mocking-tools/#how-to-get-started-with-gomock) Get The Guide When it’s time for testing, an instance of this mock struct is created and expectations are set, specifying what parameters are expected when methods are invoked, what the mock should return, and how many times a method should be called. When the tests are run, any deviation from… * [What is the best API mocking tool?](https://speedscale.com/blog/api-mocking-tools/#what-is-the-best-api-mocking-tool) With the wide range of API mocking tools available, choosing the ‘best’ one isn’t a one-size-fits-all scenario. The right tool will heavily depend on the specific needs and circumstances of your project, as well as what phase of testing you are in. Whether you require the comprehensive… Performance testing · Published 2024-01-19 ## [Top Tools to Help Debug Kubernetes Applications](https://speedscale.com/blog/top-tools-to-help-debug-kubernetes-applications/) When building cloud-based applications, managing the infrastructure becomes a bigger challenge as you scale. Kubernetes brings order to the chaos... Questions answered in this article (1) * [Why Discuss These Tools?](https://speedscale.com/blog/top-tools-to-help-debug-kubernetes-applications/#why-discuss-these-tools) The tools in this list have been chosen mainly because of the capabilities they offer. They make debugging easier and deliver information that helps you solve problems. They are also accessible and are easy to use and set up. In addition, they are generally open source and either free or… Traffic capture and replay · Published 2024-10-24 ## [Top Traffic Replay Alternatives to Enhance Your Testing and Analysis](https://speedscale.com/blog/traffic-replay-alternatives/) Traffic replay is a valuable technique for capturing and analyzing network interactions, providing essential insights into user behavior and website... Questions answered in this article (1) * [What is Traffic Replay?](https://speedscale.com/blog/traffic-replay-alternatives/#what-is-traffic-replay) Traffic replay is a powerful web analytics tool that allows website owners to record and replay user sessions in real time. This feature is essential for understanding user behavior, identifying usability issues, and optimizing website performance. By replaying user sessions, website owners can… Performance testing · Published 2024-10-31 ## [Top Traffic Shadowing Alternatives for Efficient Load Testing and Refactoring](https://speedscale.com/blog/traffic-shadowing-alternatives/) This article explores the best alternatives to traffic shadowing for conducting efficient load testing and refactoring. Questions answered in this article (1) * [What is Traffic Shadowing?](https://speedscale.com/blog/traffic-shadowing-alternatives/#what-is-traffic-shadowing) Traffic shadowing, also called traffic mirroring, is an approach for software testing that utilizes recorded user traffic as the source of data for later replay against a service. This duplication of production traffic allows for effective testing and refactoring with data that is based on the real… API mocking · Published 2024-01-02 ## [Top Use Cases for Mock Services in Software](https://speedscale.com/blog/mock-services-top-use-cases/) Mocking APIs is a popular practice in software development, with an increasing number of developers now reaping the benefits–and no longer using their. Questions answered in this article (2) * [What is a mock service?](https://speedscale.com/blog/mock-services-top-use-cases/#what-is-a-mock-service) A mock service is a development tool that imitates a real software service by returning realistic responses–without requiring computed logic to produce the response. For many developers and engineering teams, this capability can be very useful, particularly for cases such as: using third-party APIs… * [How to run a mock service](https://speedscale.com/blog/mock-services-top-use-cases/#how-to-run-a-mock-service) To run a mock service, you’ll need to decide what data to mock and how to expose this mock service. Kubernetes and observability · Published 2026-07-02 ## [Trace without traces](https://speedscale.com/blog/trace-without-traces/) The trace was sampled out. I found the bug anyway — by filtering recorded traffic on the customer's email instead of a trace ID. Here's how to follow one request across four services with no trace IDs and no OpenTelemetry. Traffic capture and replay · Updated 2026-10-12 ## [Traffic mirroring in Kubernetes: Istio vs Speedscale](https://speedscale.com/blog/traffic-mirroring-options-kubernetes/) Compare Istio traffic mirroring with Speedscale replay in Kubernetes. Use capture, redaction, and dependency isolation for repeatable regression tests. Traffic capture and replay · Updated 2026-10-09 ## [Traffic Replay Tutorial: Capture, Replay, Read Results](https://speedscale.com/blog/traffic-replay-tutorial/) Capture one service's API traffic, replay it against a Kubernetes test workload, and use the report to tell a regression from a replay setup problem. Performance testing · Published 2025-07-29 ## [Traffic Replay: Production Without Production Risk](https://speedscale.com/blog/traffic-replay-production-without-production-risk/) The software and product life cycle is fraught with pitfalls and tradeoffs. While testing applications under production-like load is critical to ensuring. Questions answered in this article (1) * [Why Stress Testing Matters?](https://speedscale.com/blog/traffic-replay-production-without-production-risk/#why-stress-testing-matters) Stress testing is more than just a checkbox in the software development process—it’s a strategic approach to safeguarding the end user experience and the business as a whole. By subjecting systems to extreme load conditions, developers can identify and fix issues that might otherwise go unnoticed… Performance testing · Published 2024-03-04 ## [Traffic-driven Testing in Kubernetes](https://speedscale.com/blog/traffic-driven-kubernetes-testing/) Testing is crucial for ensuring the reliability and stability of your Kubernetes application in a containerized environment. Unlike traditional software... Questions answered in this article (1) * [Why Does Kubernetes Testing Make Business Sense?](https://speedscale.com/blog/traffic-driven-kubernetes-testing/#why-does-kubernetes-testing-make-business-sense) There are several reasons why Kubernetes testing is important from a business perspective. For starters, by performing extensive Kubernetes testing, organizations can ensure high availability of applications and thus minimize costly downtime. Kubernetes testing also allows DevOps teams to… Performance testing · Published 2024-12-11 ## [Traffic-Driven Testing: Shift Right Testing](https://speedscale.com/blog/shift-right-testing/) In the process of developing software, designing and performing testing is a critical aspect of ensuring high software reliability, improving software. Questions answered in this article (3) * [What is Shift-Right Testing?](https://speedscale.com/blog/shift-right-testing/#what-is-shift-right-testing) In the process of developing software, designing and performing testing is a critical aspect of ensuring high software reliability, improving software quality, and deploying strong fit and function. The shift-right testing approach moves testing to later in your production cycle as a way of doing… * [How Does Shift-Right Testing Work?](https://speedscale.com/blog/shift-right-testing/#how-does-shift-right-testing-work) Shift-Right testing moves the focus to production post-release, and accordingly, utilizes tooling built for this process. Shift-right testing practices arose from the need to get tests that better reflect how users interact with a product and from faster deployments that leave less room for robust… * [What is Traffic-Driven Testing?](https://speedscale.com/blog/shift-right-testing/#what-is-traffic-driven-testing) Traffic-driven testing uses real traffic for testing but doesn’t restrict you to only running tests in production. You capture the traffic and reuse it later. Like shift-right, traffic-driven testing uses real user data to power your tests, but you can manipulate and control this data. It’s… AI development · Published 2025-06-24 ## [Train on Gold, Not Garbage - Making Powerful AI Models from Golden Data](https://speedscale.com/blog/train-on-gold-not-garbage-making-powerful-ai-models-from-golden-data/) In 2025, training AI and Large Language Models is no longer just about scale - it’s about the quality of the signal. API testing · Published 2026-07-24 ## [Two confident fixes missed this production bug](https://speedscale.com/blog/two-confident-fixes-missed-this-production-bug/) A production bug survived two confident fixes and green tests. Replaying the captured request exposed the missing state and proved the real fix. API mocking · Published 2025-01-22 ## [Ultimate Guide to Creating a JSON Mock API](https://speedscale.com/blog/json-mock/) Using a JSON mock allows you to avoid using fake data or simulating interactions, resulting in better final output and stronger data flows. Questions answered in this article (2) * [What is a JSON Mock API?](https://speedscale.com/blog/json-mock/#what-is-a-json-mock-api) A JSON mock API is essentially a simulated interface that mimics the behavior of a real API using predefined JSON data. This API type is particularly useful for testing front-end applications without the need for an actual backend server. It allows developers to work on the front end independently… * [How to Create a JSON Mock API](https://speedscale.com/blog/json-mock/#how-to-create-a-json-mock-api) Creating a JSON mock API involves several steps. Firstly, you must choose the right tool to create and manage your mock. From here, you’ll need to identify your environmental constraints and desired final structure, which will allow you to actually create the environment itself. Next, you’ll need… Kubernetes and observability · Published 2025-08-22 ## [Under the Hood with Go TLS and eBPF](https://speedscale.com/blog/ebpf-go-design-notes-1/) There are many reasons why you might want to leverage eBPF for plaintext inspection of TLS traffic including security monitoring, debugging, traffic. AI development · Published 2025-05-08 ## [Unlock Cheaper & Faster AI Testing: Mocking Claude and MCP](https://speedscale.com/blog/unlock-cheaper-faster-ai-testing-mocking-claude-and-mcp/) Generative AI is quickly becoming ubiquitous in the software development space, with tools like Anthropic’s Claude offering rapid methodologies for code... AI development · Published 2025-08-25 ## [Unlocking AI Coding Reliability with Traffic Replay](https://speedscale.com/blog/missing-step-for-ai-coding/) Discover why AI coding agents need traffic replay to bridge the gap between stochastic AI and deterministic software engineering. AI development · Published 2026-09-15 ## [Use AI and traffic replay to test AI-generated code](https://speedscale.com/blog/test-ai-code-with-traffic-replay/) Have your coding agent test AI-generated code with proxymock: capture working API traffic, replay it against changes, and inspect the results. Engineering and company news · Published 2026-02-05 ## [Using GRPC with Python Best Practices Guide](https://speedscale.com/blog/using-grpc-with-python/) Microservices are now the architecture of choice for many developers when crafting cloud-native applications. API mocking · Published 2025-04-10 ## [Using Proxymock with AWS Services](https://speedscale.com/blog/using-proxymock-with-aws-services/) Amazon Web Services, or AWS, offers a variety of cloud services ranging from AWS resources such as CDNs and data lakes to cloud computing and. API mocking · Published 2025-04-11 ## [Using Proxymock with GCP Services](https://speedscale.com/blog/using-proxymock-with-gcp-services/) Google Cloud Platform, or GCP, is a cloud resources collection offered by Google for enterprise and standard users. API mocking · Published 2026-02-01 ## [Using Python MockServer for API Testing](https://speedscale.com/blog/python-mockserver/) Using a mock server is a popular method of working around these limitations and realities, you to test web server assets against specific requests... Questions answered in this article (1) * [How Is Speedscale Different from MockServer?](https://speedscale.com/blog/python-mockserver/#how-is-speedscale-different-from-mockserver) While MockServer is excellent for creating custom request-response mocks by hand or via configuration, Speedscale goes further by automatically capturing real-world production traffic and turning it into tests. This approach removes the guesswork of manually creating or updating mocks, ensures your… Traffic capture and replay · Published 2026-06-07 ## [Validate Spring Boot Upgrades with Traffic Replay](https://speedscale.com/blog/spring-boot-migration-traffic-replay-validation/) Spring Boot upgrades silently change JSON contracts and autoconfiguration. Use traffic replay to catch every regression before production. AI development · Published 2024-10-17 ## [Ways to Use Mock Services in Software Development](https://speedscale.com/blog/mock-services-in-software-development/) Mocking APIs is a popular practice in software development. An increasing number of developers are reaping the benefits and no longer using their valuable. Questions answered in this article (3) * [What is a mock service?](https://speedscale.com/blog/mock-services-in-software-development/#what-is-a-mock-service) A mock service is a development tool that imitates a real software service by returning realistic responses without requiring computed logic to produce the response. For many developers and engineering teams, this capability can be very useful, particularly for cases such as using third-party APIs… * [When to use mock services in software testing?](https://speedscale.com/blog/mock-services-in-software-development/#when-to-use-mock-services-in-software-testing) In software testing methodologies, services are defined as being in-scope or out-of-scope. The services that are in scope are the ones you care about when testing. This can be a single service or a cluster of services. Services that are out-of-scope are the ones you don’t want to test, however they… * [How to run a mock service](https://speedscale.com/blog/mock-services-in-software-development/#how-to-run-a-mock-service) To run a mock service, you’ll need to decide what data to mock and how to expose this mock service. AI development · Published 2026-06-10 ## [We won't train on your data is not a security architecture](https://speedscale.com/blog/we-wont-train-on-your-data-is-not-a-security-architecture/) MSA clauses and contractual guarantees aren't an architecture. If your production traffic leaves your cloud, you're trusting a policy, not a system. AI development · Published 2024-05-01 ## [Webinar Replay: The 4 Biggest Challenges of Scaling Cloud-Native AI Workloads](https://speedscale.com/blog/webinar-replay-the-4-biggest-challenges-of-scaling-cloud-native-ai-workloads/) When working with AI in cloud environments, traditional data provisioning and software testing methods don't work because of the behavior of AI and LLM. AI development · Published 2026-02-04 ## [What AI Has Never Seen: The Context Gap in Code Generation](https://speedscale.com/blog/what-ai-has-never-seen-the-context-gap-in-code-generation/) AI coding tools generate code from docs and examples—but they've never seen your production traffic. Here's what breaks AI-generated code. API mocking · Published 2025-01-14 ## [What Are Cloud Development Environments?](https://speedscale.com/blog/cloud-development-environments/) Especially, if you have a globally distributed team, CDEs give you a smoother developer experience just by its \_online\_ nature. Questions answered in this article (1) * [How to set up a cloud development environment](https://speedscale.com/blog/cloud-development-environments/#how-to-set-up-a-cloud-development-environment) Depending on the CDE provider, the exact specifics of setting up the environment can vary quite a bit. But here’s a general guide that discusses the major steps in the process. Engineering and company news · Published 2024-11-11 ## [What are Ephemeral Environments?](https://speedscale.com/blog/ephemeral-environments/) Development teams and product managers have many variables that affect their daily processes. Questions answered in this article (3) * [What Are Ephemeral Environments?](https://speedscale.com/blog/ephemeral-environments/#what-are-ephemeral-environments) Ephemeral environments are temporary environments used as infrastructure for development, testing, staging, and other non-production functions. While they replicate production-like conditions, they are generally not intended to be used as production environments. These environments are… * [How Do Ephemeral Environments Work?](https://speedscale.com/blog/ephemeral-environments/#how-do-ephemeral-environments-work) Ephemeral environments utilize automated systems to provision and manage resources. These systems typically leverage a cloud provider to provision resources based on a pre-determined build guide, utilizing cloud resources and replicated data to create environments for specific purposes. Once a… * [Why Do You Need Ephemeral Environments?](https://speedscale.com/blog/ephemeral-environments/#why-do-you-need-ephemeral-environments) Developing anything requires a high level of control. The ability to create in an environment you understand is incredibly impactful, but getting to that understanding has often required deep introspection of your data sources, the network, the systems tied into both, and the very code being worked… Engineering and company news · Published 2024-12-02 ## [What are Preview Environments?](https://speedscale.com/blog/preview-environments/) Local preview environments are transforming how developers test and validate code changes before merging them into the main codebase. Questions answered in this article (1) * [What are Preview Environments?](https://speedscale.com/blog/preview-environments/#what-are-preview-environments) A preview environment is a cloud-based, temporary environment that closely replicates the production setting of an application. These environments are designed to test code changes before they are merged into the main branch of a Git repository, offering developers and QA teams a safe space to… Kubernetes and observability · Published 2025-01-01 ## [What does OOMKilled mean and how do I prevent it?](https://speedscale.com/blog/what-does-oomkilled-mean/) When creating production-level applications, enterprises want to ensure the high availability of services. Questions answered in this article (1) * [What is a Kubernetes OOMKilled Error - And Why Does it Matter?](https://speedscale.com/blog/what-does-oomkilled-mean/#what-is-a-kubernetes-oomkilled-error---and-why-does-it-matter) When creating production-level applications, enterprises want to ensure the high availability of services. This often results in a lengthy development process that requires extensive testing for the applications or a new release. This involves testing the behavior of the application under load,… Traffic capture and replay · Published 2025-12-10 ## [What I Learned From Building an eBPF-Based Traffic Capture Application](https://speedscale.com/blog/what-i-learned-from-building-an-ebpf-based-traffic-capture-application/) Building a targeted eBPF network traffic capture tool reveals why a general-purpose eBPF observability agent is exponentially harder. Questions answered in this article (5) * [Where Does This Leave Us?](https://speedscale.com/blog/what-i-learned-from-building-an-ebpf-based-traffic-capture-application/#where-does-this-leave-us) After building our TLS capture tool and staring into the abyss of what a full observability agent would require, here’s my take: * [What did Speedscale build with eBPF?](https://speedscale.com/blog/what-i-learned-from-building-an-ebpf-based-traffic-capture-application/#what-did-speedscale-build-with-ebpf) A component that captures plaintext HTTP and HTTPS payloads from Go and non-Go (OpenSSL) applications without proxies. For Go it attaches probes to crypto/tls (\*Conn).Read and Write, and for OpenSSL apps it hooks socket read/write syscalls plus the OpenSSL read and write calls, so traffic can be… * [Why is targeted eBPF traffic capture easier than full observability?](https://speedscale.com/blog/what-i-learned-from-building-an-ebpf-based-traffic-capture-application/#why-is-targeted-ebpf-traffic-capture-easier-than-full-observability) Capture has fixed target functions, simple byte-buffer data types, stateless probes, and a stable ABI, so it is a tractable 1x baseline. Full APM with spans, traces, correlation, and stack unwinding is 50 to 100x harder because the complexity grows with each language runtime, not with scope. * [What makes general-purpose eBPF function tracing so hard?](https://speedscale.com/blog/what-i-learned-from-building-an-ebpf-based-traffic-capture-application/#what-makes-general-purpose-ebpf-function-tracing-so-hard) ABI differences across languages. Go passes arguments in version-dependent registers and strips symbols in production, the JVM and .NET generate code at runtime so addresses move, and interpreted languages force you to walk interpreter structs to find a single variable. On top of that, uprobes in a… * [When should I use eBPF for observability?](https://speedscale.com/blog/what-i-learned-from-building-an-ebpf-based-traffic-capture-application/#when-should-i-use-ebpf-for-observability) Use it for targeted, narrow-scope instrumentation like network capture, infrastructure monitoring, and security enforcement, where the surface area is small and bounded. Avoid it as a single-program solution for general-purpose APM across many languages, deep application-level tracing with full… API mocking · Published 2024-11-26 ## [What is a Demo Environment?](https://speedscale.com/blog/demo-environment/) One of the most important aspects of a product is the ability to showcase its functionality. Kubernetes and observability · Published 2024-12-17 ## [What is a Memory Leak?](https://speedscale.com/blog/memory-leak/) Memory leaks happen when a program fails to release memory it no longer needs, and can be a big issue for developers and system administrators alike... Questions answered in this article (3) * [What Are the Causes of Memory Leaks?](https://speedscale.com/blog/memory-leak/#what-are-the-causes-of-memory-leaks) Memory leaks can happen due to programming errors, poorly written algorithms, or resource-intensive processes. As available memory depletes over time, the system’s performance suffers, causing increased load times and bad user experiences. This can cause long-term tack on effects across the entire… * [How to Detect Memory Leaks](https://speedscale.com/blog/memory-leak/#how-to-detect-memory-leaks) Production traffic replication is a technique that uses traffic replay and automatic mocks to isolate a service under testing, providing a realistic environment for performance testing. Deeper dives can be found in other posts like the definitive guide to traffic replay or the advantages of mock… * [How to Fix Memory Leaks](https://speedscale.com/blog/memory-leak/#how-to-fix-memory-leaks) Identifying and isolating memory leaks in complex systems like Kubernetes can be a daunting challenge for developers, but it’s crucial to maintain optimal system performance and prevent cyber attacks. Using production traffic replication tools like Speedscale can make this process much more… Performance testing · Published 2023-12-04 ## [What is Load Testing? Best Practices for Getting Started](https://speedscale.com/blog/what-is-load-testing/) Load testing is a type of software performance testing that verifies the stability and scalability of a software application by subjecting it to a set. Questions answered in this article (4) * [What is load testing?](https://speedscale.com/blog/what-is-load-testing/#what-is-load-testing) Load testing is a type of software performance testing that verifies the stability and scalability of a software application by subjecting it to a set amount of expected usage. Imagine this scenario: you’re launching a new eCommerce website or a highly anticipated new product. After completing your… * [Who is load testing for?](https://speedscale.com/blog/what-is-load-testing/#who-is-load-testing-for) Load testing can benefit everyone, including developers, the greater organization, and even end-users. Developers benefit from the ability to identify issues or bottlenecks without disrupting user experience and relying on real-user reports. They can then fix these bottlenecks preemptively rather… * [When not to use load testing?](https://speedscale.com/blog/what-is-load-testing/#when-not-to-use-load-testing) Despite many great use cases for load tests, it may not be optimal in some situations. For example, if you’re a small startup still trying to find product-market fit, load testing may not be a top priority. Similarly, if your application has low usage, or serves mainly static content, the benefits… * [How does load testing work?](https://speedscale.com/blog/what-is-load-testing/#how-does-load-testing-work) Load testing is critical for determining the resiliency and scalability of an application under different kinds of load. It measures an application’s performance and stability by simulating real usage within realistic production conditions. In theory, you should measure any metric that can identify… Kubernetes and observability · Published 2024-12-06 ## [What is Resilience Testing: The Ultimate Guide](https://speedscale.com/blog/resilience-testing/) Today’s complex, dynamic applications demand rigorous resilience testing. A common hurdle is accurately mimicking real user behavior. Questions answered in this article (5) * [What is Resilience Testing?](https://speedscale.com/blog/resilience-testing/#what-is-resilience-testing) Resilience testing is a type of software testing where a system is tested against simulated adverse conditions. Resilience testing focuses on testing the software against common issues like hardware or system failures, network interruptions, or high traffic loads. Resilience testing can help test… * [What is Chaos Testing?](https://speedscale.com/blog/resilience-testing/#what-is-chaos-testing) Chaos testing, sometimes referred to as chaos engineering, is a method of resilience testing that intentionally introduces faults and unpredictability into the system. Chaos testing aims to identify weaknesses or vulnerabilities in a system that may not have surfaced during regular testing. By… * [Why Use Chaos Testing at All?](https://speedscale.com/blog/resilience-testing/#why-use-chaos-testing-at-all) Tailoring your resilience strategies to your specific user experience and business requirements is critical. An e-commerce app might prioritize maintaining its payment systems over its recommendation engine during a fault. However, a social media application might prioritize user feeds over direct… * [How Does Resilience Testing Work?](https://speedscale.com/blog/resilience-testing/#how-does-resilience-testing-work) Resilience testing works by causing controlled chaos in a very controllable environment. In essence, you are trying to systematically subject the service or system to conditions that would impact its operation in a way that doesn’t affect the actual operations of the service. Providers typically… * [Why Resilience Testing is Crucial?](https://speedscale.com/blog/resilience-testing/#why-resilience-testing-is-crucial) Resilience testing, and chaos testing especially, is crucial for a health service to maintain its flexibility and ensure a specific level of coordinated service. Consider the infamous 2012 AWS outage. Many services experienced significant downtime, yet Netflix remained largely operational due to… API mocking · Published 2024-12-04 ## [What is Service Virtualization?](https://speedscale.com/blog/what-is-service-virtualization/) Service virtualization is increasingly popular in the software & DevOps toolkit. Learn what it is, how it works, and how to use it. Questions answered in this article (1) * [Why Do You Need Service Virtualization?](https://speedscale.com/blog/what-is-service-virtualization/#why-do-you-need-service-virtualization) Service virtualization is a critical tool for solving the intrinsic problems of testing a production system. Testing the actual services for faults or issues means invoking those problems, and as such, it has a necessary impact on the production services themselves—by virtualizing those systems,… Traffic capture and replay · Published 2025-02-04 ## [What Is Shadow Traffic? All You Need to Know](https://speedscale.com/blog/shadow-traffic/) Production traffic can often be unpredictable, and distinguishing genuine user interactions from mere noise becomes a pivotal step in comprehensively. Questions answered in this article (2) * [What is Shadow Traffic?](https://speedscale.com/blog/shadow-traffic/#what-is-shadow-traffic) Simply put, shadow traffic refers to web traffic that standard analytics tools fail to accurately capture, analyze, or record. This traffic can arise for a variety of reasons, but ultimately they reflect a dark data source which is ill-defined and hard to surface - hence the term “shadow-sm”.… * [How to Manage Shadow Traffic](https://speedscale.com/blog/shadow-traffic/#how-to-manage-shadow-traffic) Effective management of shadow traffic involves proactive measures and continuous monitoring. You can help manage shadow traffic by implementing solutions such as server-side tracking, which shift tracking responsibilities from the client-side to the server-side. You can also deploy firewall and… Traffic capture and replay · Published 2025-01-06 ## [What is Traffic Mirroring: A Complete Guide](https://speedscale.com/blog/what-is-traffic-mirroring/) Ensuring seamless data flow and robust application performance is crucial in modern networking and cloud computing. Questions answered in this article (1) * [What is Traffic Mirroring?](https://speedscale.com/blog/what-is-traffic-mirroring/#what-is-traffic-mirroring) Traffic mirroring sounds straightforward—it involves capturing network traffic and replicating it to another location. In local networking, this is often called port mirroring or a network tap, but in web applications, this is commonly referred to as traffic capture and replay. While the process is… Performance testing · Published 2023-12-14 ## [What is Volume Testing? Best Practices](https://speedscale.com/blog/volume-testing/) Modern-day software applications aim to cover a wide range of users’ needs in a flexible and scalable way. Between fierce business competition and high... Questions answered in this article (2) * [What is volume testing?](https://speedscale.com/blog/volume-testing/#what-is-volume-testing) Volume testing — also known as flood testing — examines the stability and response time of a system by transferring huge volumes of data, and evaluates a variety of different system components like databases, software, etc. This type of software testing is a critical part of avoiding issues under… * [What to monitor in a testing plan?](https://speedscale.com/blog/volume-testing/#what-to-monitor-in-a-testing-plan) Your volume testing checklist must be created in detail, and should represent the live environment conditions as closely as possible. To achieve this, your test cases should cover all the use scenarios and data needed to accurately simulate production conditions, including the real-life data your… API mocking · Published 2026-09-02 ## [What Mocks Are Actually For](https://speedscale.com/blog/what-mocks-are-actually-for/) Part 1 of Getting Started with Mocks: the one job a mock does, the five situations where you need one, and what a green mocked test does not prove. AI development · Published 2026-04-20 ## [What the Warp Terminal Sends Home](https://speedscale.com/blog/what-the-warp-terminal-sends-home/) We recorded Warp traffic to see what gets sent back to the home base. Spoiler: It's everything. Questions answered in this article (4) * [Does the Warp terminal send my commands to its servers?](https://speedscale.com/blog/what-the-warp-terminal-sends-home/#does-the-warp-terminal-send-my-commands-to-its-servers) Yes. Every command you run, along with its output, exit code, working directory, and shell details, is sent to Warp’s /analytics/block endpoint and associated with your account. Warp applies secret redaction, but credential patterns in shell output are too varied to catch reliably, so vendor trust… * [What does Warp send when you use its AI features?](https://speedscale.com/blog/what-the-warp-terminal-sends-home/#what-does-warp-send-when-you-use-its-ai-features) A protobuf request to /ai/multi-agent or /ai/passive-suggestions that includes your prompt, your entire AGENTS.md file, and every skill definition in ~/.claude/skills/ with full file paths. Our capture included 24+ skills covering internal infrastructure tools. This happens on AI autocomplete too,… * [Which AI models does Warp actually use?](https://speedscale.com/blog/what-the-warp-terminal-sends-home/#which-ai-models-does-warp-actually-use) Routing is server-side and doesn’t always match the model you pick in the UI. One conversation in our test used GPT-5.2 and GLM 5, a model from Zhipu AI in China. The catalog has about 25 models from four providers, and the client never contacts OpenAI or Anthropic directly. Everything routes… * [Why is Warp’s network traffic hard to inspect?](https://speedscale.com/blog/what-the-warp-terminal-sends-home/#why-is-warps-network-traffic-hard-to-inspect) Its core API calls bypass the HTTP\_PROXY variable, so tools like Charles, Proxyman, and proxymock don’t see them. It uses rustls with NoKeyLog, which disables SSLKEYLOGFILE so raw packet captures can’t be decrypted, and the AI endpoints use protobuf instead of JSON. We got in with transparent TLS… API mocking · Published 2026-09-02 ## [When Handwritten Mocks Stop Scaling](https://speedscale.com/blog/when-handwritten-mocks-stop-scaling/) Part 9 of Getting Started with Mocks: a decision framework for stubs, fakes, fake servers, mock servers, record-and-replay, and real dependencies. Traffic capture and replay · Published 2026-04-09 ## [When Your Observability Literally Stops Traffic](https://speedscale.com/blog/when-your-observability-literally-stops-traffic/) Observability tells you what failed—but not how to recreate it. Why reproducibility is the missing fourth pillar, and what that means for incident response. AI development · Published 2026-06-29 ## [Which Bugs AI Agents Fix Better With Traffic](https://speedscale.com/blog/ai-rework-tax-which-bugs/) A second run of our AI bug-fixing benchmark shows where captured traffic lifts agents toward 90%, why service maps barely help, and which bugs still fail. Questions answered in this article (4) * [Which bug types do AI agents fix better with captured traffic?](https://speedscale.com/blog/ai-rework-tax-which-bugs/#which-bug-types-do-ai-agents-fix-better-with-captured-traffic) The ones whose truth is in the request or response. In my benchmark, race and write-path bugs went from 22% to 89% with traffic, state-machine transitions from 72% to 92%, streaming and multipart framing from 52% to 85%, and cross-service contract drift from 44% to 81%. Bugs that live on the wire… * [Do service maps help an AI agent pick the right microservice?](https://speedscale.com/blog/ai-rework-tax-which-bugs/#do-service-maps-help-an-ai-agent-pick-the-right-microservice) A little, but far less than payloads. Testing four ways (alert alone, alert plus service map, alert plus traffic, alert plus both), the map alone added 6 percentage points while traffic added 28, and traffic still added more than 20 on top of the map. The failing request carries the broken field… * [Which bugs does captured traffic not help with?](https://speedscale.com/blog/ai-rework-tax-which-bugs/#which-bugs-does-captured-traffic-not-help-with) Deep framework internals, where the fix hides in a buffer or state machine that no request ever touches. Those went from 75% to 79%, essentially flat, while wire-level bugs climbed toward 90%. Traffic is the tiebreaker when the bug’s truth is in the request or response, and dead weight when it… * [How much does it cost to give an AI agent captured traffic?](https://speedscale.com/blog/ai-rework-tax-which-bugs/#how-much-does-it-cost-to-give-an-ai-agent-captured-traffic) Close to free. The full second run, including the four-way test, was about 18,000 model calls for roughly $118, and 94% of the input tokens were cached because the codebase repeats across every run. Bolting a few captures onto each prompt adds little on top of that. 100 bugs in a private… AI development · Published 2026-04-07 ## [Why Autonomous AI Agents Can't Run on SaaS Infrastructure](https://speedscale.com/blog/byoc-autonomous-agents-sovereign-ai-factory/) SaaS AI fails when agents need continuous access to your codebase and internal APIs. Here's why BYOC is the only deployment model that works at scale. AI development · Published 2026-04-03 ## [Why You Should Stop Buying SaaS and Start Building It](https://speedscale.com/blog/why-you-should-stop-buying-saas-and-start-building-it/) LLMs have collapsed the cost of custom internal tools. Here's the startup distribution problem I've watched kill companies — and how I vibe-coded my way out. AI development · Published 2026-02-12 ## [Why Your Company Will Be Running OpenClaw Next Year](https://speedscale.com/blog/why-your-company-will-be-running-openclaw-next-year/) OpenClaw is the new model for AI agents in the enterprise. Here's why it's a security nightmare and who's building the governed version. Questions answered in this article (1) * [Who’s Building OpenClaw 2.0 for Business?](https://speedscale.com/blog/why-your-company-will-be-running-openclaw-next-year/#whos-building-openclaw-20-for-business) Every major platform vendor is racing to build what they’re calling the governed version of OpenClaw. The market is projected to grow from $7.84B to $52.62B by 2030 at a 46.3% CAGR. Gartner predicts 40% of enterprise apps will have embedded AI agents by end of 2026, up from less than 5% in 2025.… API mocking · Published 2026-05-22 ## [WireMock alternatives: pick the one that fits your problem](https://speedscale.com/blog/wiremock-alternatives/) A 2026 take on WireMock alternatives. Keep WireMock for what it's good at; add Microcks (now CNCF Incubating) or proxymock for the gaps. The honest map. API mocking · Updated 2026-10-12 ## [WireMock vs MockServer vs proxymock for API testing](https://speedscale.com/blog/wiremock-vs-mockserver-vs-proxymock/) Compare HTTP stubs, request verification, and recorded dependency mocks. Choose WireMock, MockServer, or proxymock for your Java API tests. Questions answered in this article (7) * [What is the difference between WireMock and MockServer?](https://speedscale.com/blog/wiremock-vs-mockserver-vs-proxymock/#what-is-the-difference-between-wiremock-and-mockserver) Both support HTTP request matching, configured responses, and request verification. Compare their APIs and lifecycle integration against the expectations your tests need. * [Can WireMock record real traffic?](https://speedscale.com/blog/wiremock-vs-mockserver-vs-proxymock/#can-wiremock-record-real-traffic) Yes. WireMock supports record and playback. Captured fixtures still need review and updates when the real dependency contract changes. * [When should I use proxymock instead of an HTTP stub server?](https://speedscale.com/blog/wiremock-vs-mockserver-vs-proxymock/#when-should-i-use-proxymock-instead-of-an-http-stub-server) Use proxymock when you need recorded dependency responses or want to replay inbound traffic against a code change. Follow the setup requirements for each protocol and client. * [Can I migrate from WireMock to proxymock?](https://speedscale.com/blog/wiremock-vs-mockserver-vs-proxymock/#can-i-migrate-from-wiremock-to-proxymock) Migrate incrementally: keep targeted WireMock tests and record one representative integration flow with proxymock. Compare the results before expanding coverage. A recording is not a one-to-one translation of WireMock matchers and verification assertions. * [Does proxymock work with Spring Boot?](https://speedscale.com/blog/wiremock-vs-mockserver-vs-proxymock/#does-proxymock-work-with-spring-boot) Yes. Follow the Java and protocol-specific setup instructions, including any client proxy or port-mapping configuration. Capture a representative flow and confirm its downstream calls appear in the recording before relying on the mocks. * [How do I handle sensitive data in recorded traffic?](https://speedscale.com/blog/wiremock-vs-mockserver-vs-proxymock/#how-do-i-handle-sensitive-data-in-recorded-traffic) Configure redaction rules, inspect tokens and personal data, and review recordings before sharing them. A traffic recording does not by itself establish privacy or compliance. * [How do Testcontainers and API mocks work together?](https://speedscale.com/blog/wiremock-vs-mockserver-vs-proxymock/#how-do-testcontainers-and-api-mocks-work-together) Testcontainers starts real dependencies in containers. API mocks supply controlled dependency responses. Use a real database container for database behavior and an HTTP mock for a payment timeout when those are the requirements you need to test. AI development · Published 2026-06-01 ## [Your AI agent is fixing the wrong service](https://speedscale.com/blog/ai-rework-tax/) I tested 100 bugs across 240 microservices the model has never seen. Alert only: 51% pass rate, wrong service 34% of the time. Traffic captures: 77%. Questions answered in this article (4) * [How reliably do AI coding agents fix real bugs?](https://speedscale.com/blog/ai-rework-tax/#how-reliably-do-ai-coding-agents-fix-real-bugs) Not very, on their own. The best agents fix about 50% of real bugs on SWE-bench verified, and in my own benchmark on a codebase the model had never seen, an agent working from a monitoring alert passed 51% of the tests. AI-generated code also tends to produce more issues than human-written code, so… * [Does giving an AI agent production traffic improve its bug fixing?](https://speedscale.com/blog/ai-rework-tax/#does-giving-an-ai-agent-production-traffic-improve-its-bug-fixing) Yes, substantially, when the bug shows up on the wire. Handing the agent the captured request and response for the failing call raised the pass rate from 51% to 77% in my test, a 26 percentage point jump with non-overlapping confidence intervals. * [Why do AI coding agents fix the wrong service?](https://speedscale.com/blog/ai-rework-tax/#why-do-ai-coding-agents-fix-the-wrong-service) With only an alert, the agent has to guess which of hundreds of services is broken and greps for vague keywords like latency or error rate that match half the codebase. In my 240-service test it edited the wrong service 34% of the time. Captured traffic names the specific endpoint and field, which… * [When does traffic context make an AI agent worse?](https://speedscale.com/blog/ai-rework-tax/#when-does-traffic-context-make-an-ai-agent-worse) When the real fix is below the HTTP boundary. On 11 bugs the captures gave the agent a confident theory that pointed at the symptom but the wrong layer, like an exception base class or a race condition in internal state that never appears in the trace. There it was faster, more decisive, and wrong.… API mocking · Published 2026-09-02 ## [Your First Useful Mock](https://speedscale.com/blog/your-first-useful-mock/) Part 2 of Getting Started with Mocks: a test you cannot write, one seam, and the smallest mock that makes a delayed package happen. Java, Node, Go, Python. API testing · Published 2026-03-11 ## [Your Flaky Tests Are a Data Problem, Not a Test Problem](https://speedscale.com/blog/qabot-fix-flaky-tests-ci/) Most flaky test fixes focus on retries and quarantine. The real fix is replacing hand-written test data with recorded traffic that stays fresh. Questions answered in this article (4) * [How does QABot know which values are dynamic?](https://speedscale.com/blog/qabot-fix-flaky-tests-ci/#how-does-qabot-know-which-values-are-dynamic) QABot uses structural analysis, not guesswork. It identifies JWTs by their three-part base64 structure and checks for exp/iat claims. It finds timestamps by matching ISO 8601, RFC 2822, and Unix timestamp patterns. It traces ID propagation by matching values that appear in a response and then… * [What if QABot gets a transform wrong?](https://speedscale.com/blog/qabot-fix-flaky-tests-ci/#what-if-qabot-gets-a-transform-wrong) The generated transforms are saved as YAML files in your repo. You can inspect and edit them. If QABot incorrectly identifies a static value as dynamic (or misses a dynamic one), you adjust the YAML and commit the change. Over time, QABot’s detection improves as it sees more recordings from your… * [Can I use this alongside WireMock?](https://speedscale.com/blog/qabot-fix-flaky-tests-ci/#can-i-use-this-alongside-wiremock) Yes. If you already have WireMock stubs for contract tests or specific fault injection scenarios, keep them. Use proxymock + QABot for integration and regression tests where you need realistic data across many dependencies. The two approaches complement each other. See our WireMock vs MockServer vs… * [Is QABot part of proxymock or Speedscale?](https://speedscale.com/blog/qabot-fix-flaky-tests-ci/#is-qabot-part-of-proxymock-or-speedscale) QABot is in beta as part of the Speedscale Cloud platform. The proxymock CLI is free for recording and replaying traffic locally. QABot’s analysis and recommendations live in the Speedscale dashboard. You push your local recordings with proxymock cloud push snapshot, review the recommendations in… API mocking · Published 2026-09-02 ## [Your Mock Is Lying](https://speedscale.com/blog/your-mock-is-lying/) Part 8 of Getting Started with Mocks: the carrier renames a field, production breaks, and every mocked test still passes. Java, Node, Go, Python. Kubernetes and observability · Published 2026-08-27 ## [Your Observability Stack Found the Fire. Congratulations.](https://speedscale.com/blog/your-observability-stack-found-the-fire/) Observability tells you when production is on fire. Capturing and replaying real traffic lets you recreate the incident, verify the fix, and keep it fixed. Performance testing · Published 2025-08-18 ## [Zero Trust Architecture Needs Zero Guesswork](https://speedscale.com/blog/zero-trust-architecture-needs-zero-guesswork/) The Zero Trust model has fundamentally shifted how organizations secure their applications and infrastructure. Questions answered in this article (1) * [Why a Zero Trust Architecture Demands Behavioral Validation?](https://speedscale.com/blog/zero-trust-architecture-needs-zero-guesswork/#why-a-zero-trust-architecture-demands-behavioral-validation) While older approaches to the internal network viewed these sources as relatively trustworthy, the rise of internal attacks, privilege escalation, and data breaches led many organizations to seek an alternative trust approach and model. The Zero Trust approach was the result - a view of systems…