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The latest News and Information on API Development, Management, Monitoring, and related technologies.

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Flamegraphs Find It. Replay Proves It.

I made an API endpoint 13 times faster. Then I realized my first verification only checked the status, headers, and response schema. I had not checked the totals. I had made the bug faster. That is the problem with giving an AI coding agent one kind of evidence. A CPU profile can show where the application is slow, but not whether an optimization preserves behavior. A traffic replay can prove that behavior stayed stable, but not explain why the code burns CPU. This walkthrough gives the agent two independent witnesses: Together, they turn AI code verification into an experiment with two independent checks.

The Pod Was Cheaper. The Service Wasn't.

A smaller Kubernetes pod can lower allocation cost while completing less work. Green status codes and matching schemas can hide it. This walkthrough combines OpenCost allocation data with proxymock behavior and performance evidence. A candidate passes only when behavior and throughput hold while unit cost falls.

Cut AI coding defects by 33% #mcpserver #aicoding #aiagents #grafana #aitools

We spend thousands of dollars "token maxing" and running endless debugging cycles just to walk our LLMs through a problem. But is the AI actually failing, or are we just withholding the right environment? Giving your AI assistant its own sandbox to test hypotheses might just be the missing link in your development workflow.

The best ways to visualize API responses in 2026

APIs power almost everything we use today, from cloud platforms and monitoring tools to ticketing systems and internal applications. But no matter how useful an API is, the response usually arrives as raw JSON. That's perfectly fine for machines, but much less convenient for people. Whether you're debugging an endpoint, exploring a new service, or building dashboards for your team, you'll probably want a better way to visualize that data. Fortunately, there are several ways to visualize API responses.

Stop Writing Log Lines: Use eBPF to Catch PII and Credentials

Tired of out-of-control log expenses and manual logging discipline? Discover next-generation observability with Speedscale. By using eBPF to record full-fidelity data right off the wire, you can instantly run full-text searches, track down leaking PII, and securely map out credentials across HTTP, Postgres, gRPC, and more—all without writing a single log line. Learn more: speedscale.com.

CLIs are more token-efficient than MCP. Or are they?

MCP servers have a reputation: they eat your context window. CLIs paired with skills, on the other hand, are more token efficient. But is this still true? I dropped all my MCP servers five months ago. Five months is a long time in AI land. When Anthropic came up with the concept of skills, many people stopped using MCP servers in favor of CLI tooling and skills.