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speedscale

The Three Pillars Were Built for Humans

Jun 30, 2026 By Matthew LeRay In Speedscale
It was 2am and I was paying for the privilege. Something was on fire in production, and I’d done the modern thing: I pointed an AI agent at it. It ingested the dashboards. It read the logs. It walked the traces. Then it handed me back a beautifully formatted paragraph that said, in effect, “latency is elevated on the checkout path.” I knew that. The page told me that.
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speedscale

Which Bugs AI Agents Fix Better With Traffic

Jun 29, 2026 By Ken Ahrens In Speedscale
In the first experiment, I wanted a baseline: if an AI coding agent gets the same production signal a human would get, can it fix bugs in a codebase it has never seen? Yes, but only when I gave it better context. With only an alert, the agent passed 51% of the runtime tests. When I added captured traffic, the actual request and response for the failing call, it climbed to 77%. This post is the second pass.
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Five things your logs will never tell you

Jun 22, 2026 By Matthew LeRay In Speedscale
A customer escalation hit my queue when I was on the customer smoke jumpers team at an observability vendor. My team was the group that parachutes into Fortune 500 accounts one bad week from churning and usually after a big customer outage. The customer had filed a billing dispute three weeks earlier and their on-call engineers were stuck. They had our full stack: logs, metrics, traces, end-to-end instrumentation, every product we sold and some we didn't. They could see the request came in. They could see it returned a 500. They could not see the body. The trace was sampled out. The log line was truncated at 4KB.
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speedscale

Beware of PII in Testing Data: The Security Iceberg and Where PII Actually Hides

Jun 19, 2026 By Speedscale Team In Speedscale
If you run a platform tools or security team, you have likely heard this request from developers: “I just need a copy of the production database for staging so I can run realistic load and integration tests.” It is a completely reasonable request. Production traffic and data contain the actual request shapes, real-world value distributions, long-tail anomalies, and timing patterns that make tests useful.
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speedscale

Build WireMock mappings fast from real traffic

Jun 18, 2026 By Ken Ahrens In Speedscale
I’m a big fan of service mocking. I’ve been working in and around software for about 25 years, and one thing never changes: when you sit down to work on your code, you almost never have everything available. The database, the third-party API, the message queue, the service two teams over. Something’s missing. So you’ve got to stub it out or mock it out and keep moving.
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speedscale

Fixing 403 auth errors when you replay traffic

Jun 12, 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

Capture once, test forever

Jun 12, 2026 By Ken Ahrens In Speedscale
We’ve gotten used to understanding our applications through signals, summaries, and traces. Tiny little bits of information about how the app really works. Not because that’s the best way to do it, but because it’s been too hard to get the real thing. The real information exists. It’s on the network. How people called your app and what your code did. What other systems it called, the database queries it made, and the result sets that came back.
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speedscale

We won't train on your data is not a security architecture

Jun 10, 2026 By Ken Ahrens In Speedscale
Every enterprise contract I’ve signed in the last two years has the same clause. “Vendor will not use Customer Data to train machine learning models.” Sometimes it’s a paragraph. Sometimes it’s a whole section. The language varies but the intent is identical: don’t feed our production data into your AI. I get it. I sign the same clause as a vendor. But here’s what’s been bothering me: that clause is a promise, not an architecture.
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speedscale

Validate Spring Boot Upgrades with Traffic Replay

Jun 7, 2026 By Speedscale Team In Speedscale
Spring Boot version upgrades—whether moving from 2.x to 3.x, 3.x to 4.x, or even minor bumps like 3.2.5 to 3.3.1—regularly introduce subtle, breaking changes that unit and integration tests miss. JSON serialization shifts, autoconfiguration reordering, and transitive dependency conflicts can silently alter your API contract.
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speedscale

The AI Code Explosion: Why Your Mocking Strategy is Breaking Down

Jun 4, 2026 By Alan Mon In Speedscale
The rise of AI-assisted coding has transformed how software is built. With tools generating entire features in seconds, the bottleneck is no longer writing code—it’s verifying it. Because AI can generate boilerplate and handle API integrations instantly, more service changes are being pushed into authentication logic, API calls, and configurations. Teams desperately need a way to verify these changes before merging, especially when the code touches external dependencies.
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Testing AI Code is a Security Nightmare? #Speedscale #DevOps #Kubernetes #AICoding #SoftwareTesting

Jun 4, 2026 By Speedscale In Speedscale
AI can write a feature in seconds, but where are you testing it? Sending production traffic, API payloads, and auth headers to a third-party SaaS is a massive security risk. In this video, we break down why the Bring Your Own Cloud (BYOC) model is the ultimate fix for DevSecOps. Learn how to safely test AI-generated code against real production traffic entirely within your own VPC or Kubernetes cluster. No data leaks, no massive DLP pipelines, and no endless masking rules.
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The Bug Hiding in Your Production Traffic

Jun 3, 2026 By Speedscale In Speedscale
Your logs showed 500 errors. The traces showed the dependency graph. Neither showed the actual bug, a DEL control character getting appended to the query string. This is how I found it. In this video I walk through Speedscale BYOC (bring your own cloud): capture real production traffic, store it in your own Elasticsearch cluster inside your VPC, pull it down locally with a single script, and reproduce the exact bug using proxymock. The data never leaves your environment.
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Logs told me something broke. Traffic showed me what.

Jun 2, 2026 By Ken Ahrens In Speedscale
Here’s a problem I run into constantly: something breaks in production, I can see the 500 errors in my logs, but I can’t reproduce it locally. The trace shows me the dependency graph but not the actual request that failed. This is especially painful in microservices. I was looking at a CNCF example the other day (a simple demo app, like 4 pods) and it already had so many cross-service dependencies that understanding what broke required looking at the whole system at once.
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Your AI agent is fixing the wrong service

Jun 1, 2026 By Ken Ahrens In Speedscale
Everyone wants an AI agent factory in 2026. Autonomous agents fixing bugs and shipping features while you sleep. I’ve been building toward that myself. But the error rates don’t support the fantasy. The best AI coding agents in the world fix about 50% of real bugs on SWE-bench verified. Half the time they fail. And AI-generated code produces 1.7x more issues than human-written code.
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