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

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.

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.

eBPF: Preventing Garbage HTTP Payloads When Reading Kernel Scatter-Gather Buffers

Recently someone on our team opened a traffic snapshot and found an HTTP request that was captured with our eBPF capture agent, nettap. Our protocol dissector parsed most of the response correctly, but that correctness ended once the response headers were processed. What they ended up with was a recording of an HTTP request/response where the response body was just an incorrect collection of garbage binary data when it should have been JSON text.

Two confident fixes missed this production bug

Every new signup posts a message to our Slack. The format is dull and reliable: Overnight this week one arrived like this: That trailing nothing was the entire incident. No error logs, no alerts. A returning user had signed up, our signup service had attached them to a tenant we deprovisioned back in December, and the only symptom in the whole company was a Slack message that ran out of words.