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speedscale

Flamegraphs Find It. Replay Proves It.

Aug 11, 2026 By Matt LeRay In Speedscale
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.
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speedscale

The Pod Was Cheaper. The Service Wasn't.

Aug 11, 2026 By Matt LeRay In Speedscale
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.
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speedscale

Diagnose Serial N+1 API Calls With Tempo + proxymock

Aug 11, 2026 By Matt LeRay In Speedscale
One API request took 302 milliseconds. Nothing failed. CPU was mostly idle. The response was correct. The trace made the problem obvious: eight inventory calls, each waiting for the previous one. But the trace could not tell me why the application made eight calls, or whether changing their execution would preserve the response. It showed the shape of the wait, not the input that created it.
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eBPF: Preventing Garbage HTTP Payloads When Reading Kernel Scatter-Gather Buffers

Jul 28, 2026 By Shaun Duncan In Speedscale
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.
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Two confident fixes missed this production bug

Jul 24, 2026 By Ken Ahrens In Speedscale
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.
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Imaginary Test Data. Real Token Bill.

Jul 23, 2026 By Alan Mon In Speedscale
Ask an AI for K-pop concert advice without saying the group, city, date, or budget. It may confidently send you to a BLACKPINK tribute night in Cleveland with a $400 resale ticket. The AI was plenty confident. It just had nothing real to go on. That is exactly what happens when developers test AI applications with invented traffic. The test may look reasonable. The result may even pass.
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Fixing 403 auth errors when you replay traffic

Jul 13, 2026 By Ken Ahrens In Speedscale
Trigger warning: this one is about Java, authentication, and Docker Compose files. If that is not your thing, I am sorry, but they are part of life and they are honestly not that hard to work with. Everything here is open source on our GitHub repo, so you can follow along. Recording an authenticated Java flow, replaying it, hitting the dreaded 403, and fixing it with a proxymock recommendation.
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speedscale

AI writes code in seconds, but delivery still takes days

Jul 9, 2026 By Ken Ahrens In Speedscale
The pitch for AI coding was speed. Claude Code, Copilot, Cursor, whatever you’re running, they all generate business logic faster than you can review it. That part is real. But look at what happens after the code gets written and the numbers get ugly. CircleCI’s 2026 State of Software Delivery Report found AI drove a 59% increase in average throughput.
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The API tests passed. The database didn't.

Jul 4, 2026 By Matthew LeRay In Speedscale
We shipped v2 of a small products API on a Thursday. Green CI. Green replay. The new search endpoint worked. I went home feeling competent. Friday morning I ran the same traffic against both builds with proxymock and compared the SQL. v2 had added 80 queries on the same HTTP script. A per-product audit COUNT was firing inside the list handler. A startup migration had run ALTER TABLE and CREATE TABLE audit_log. Total DB time was up 70 ms on a demo that should have been boring.
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