A Developer's Guide to Improving AI Code Reliability
Improve AI code reliability with reviewed requirements, preserved traffic baselines, and explicit replay gates. Reuse working examples before deploying.
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Latest insights on Agentic AI workflows, cloud native architectures, and performance optimization best practices from the Speedscale team.
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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.
The Hidden AI Bill: Why Non-Prod LLM Costs Spiral
Production AI spend gets attention. Non-prod LLM calls in development, CI, and load tests often do not. Simulation fixes that.
Load Test PostgreSQL Instantly using 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.
Your Flaky Tests Are a Data Problem, Not a Test Problem
Most flaky test fixes focus on retries and quarantine. The real fix is replacing hand-written test data with recorded traffic that stays fresh.
Testing AI Code in CI/CD with a Verified Replay Gate
Test AI code in CI/CD with proxymock. Reuse recorded API traffic, prove a broken change fails, and keep replay reports for review before you deploy code.
The Developer’s Guide to Debugging AI-Generated Code
Debug AI-generated code with proxymock: reproduce failing API calls, inspect response differences, preserve the baseline, and verify fixes before release.
WireMock alternatives: pick the one that fits your problem
Compare WireMock alternatives by task: recorded mocks and replay with proxymock, HTTP expectations with MockServer, or contract-driven mocks with Microcks.
Playwright End-to-End Testing with Recorded API Mocks
Run Playwright tests with recorded API mocks, diagnose UI and API failures, then run the same specs in Kubernetes. Use the lab's commands and screenshots.
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.