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.
Speedscale Blog
Latest insights on Agentic AI workflows, cloud native architectures, and performance optimization best practices from the Speedscale team.
Featured Post
Recent Posts
Prompt, Deploy, Pray Is Dead: Validating AI Code with Proxymock
AI-generated code is moving fast—but without behavioral validation, you're gambling with production stability. See how Proxymock changes the equation.
AI Coding Agents Have a UX Problem Nobody Wants to Talk About
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.
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.
WireMock vs MockServer vs Proxymock: Java Mocking in 2026
Compare WireMock, MockServer, and proxymock for enterprise Java API mocking. See how each handles recorded traffic, Kubernetes, CI/CD, and AI-generated code.
Spring Boot API Testing: A Practical Guide for Enterprise Teams
Enterprise Spring Boot APIs need more than unit tests. Learn how to test external service integrations, JWT auth, and production edge cases with real traffic.
Debugging Encrypted Microservice Traffic with Speedscale's eBPF Collector
Learn how to capture, inspect, and archive encrypted microservice traffic with Speedscale's eBPF collector—no certificate management or code changes required.
Building Speedy: An 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.
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.
Runtime Validation vs Static Analysis: Why You Need Both
Static analysis catches code smells. Runtime validation catches behavioral failures. Enterprise teams adopting AI coding tools need both to ship safely.