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Settle Your QA Debt Before the Bugs Start Breaking Kneecaps

Oct 27, 2025 By Alan Mon In Speedscale
In Part One, we discussed how QA debt builds silently over time — causing slower releases, late-night firefights, and unpredictable test cycles. The next step is understanding how much debt you have and where it hides. This post goes deeper into measuring QA debt — what to track, how to collect data, and how to use those insights to create a sustainable plan for improvement.
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Stop Debugging Blindly! How Traffic Capture Can Help Your Code #speedscale #trafficcapture #ai

Oct 24, 2025 By Speedscale In Speedscale
Is AI "slop" or new code pushing tons of bugs into production? You can't test everything forever. Learn how traffic capture is the most efficient way to understand how your code is actually running in the real world. By grabbing data from sidecars, packet captures, or logs, you get the context you need to prevent bugs and improve performance.
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Mitmproxy vs Proxymock: Replaying Traffic for Realistic API Testing

Oct 21, 2025 By Matthew LeRay In Speedscale
Replaying traffic is a core tool in your toolbox when you need to reproduce a tricky bug or validate how your app behaves. Traffic replay is especially valuable for testing complex software applications that rely on APIs and microservices, where integration and functionality must be thoroughly validated.
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speedscale

Part 1: Building a Production-Grade Traffic Capture and Replay System

Oct 21, 2025 By Ken Ahrens In Speedscale
A few years ago I was on call during the Super Bowl. At the time I was working for an observability vendor and one of our customers had an outage caused by a surge in user traffic. But our monitoring system didn’t have enough data to know what went wrong and I sat on a call for 2 hours painfully listening to them spinning up more servers and trying to catch up with the user load.
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speedscale

Debugging Without a Net: The Pain of Reproducing Production Issues

Oct 20, 2025 By Alan Mon In Speedscale
Every engineer has been there — a late-night page, a broken feature in production, and no clear way to reproduce it. The logs are vague. The metrics look normal. Your local environment works fine. Yet something somewhere is failing for real users. So begins the detective work — debugging a live system with almost no tools, no perfect test data, and no clone of production.
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Your "Technical Debt" is a LIE! Meet QA Debt.

Oct 17, 2025 By Speedscale In Speedscale
The REAL reason your system WILL FAIL. We all talk about technical debt, but QA Debt is the silent killer costing companies millions. It's the accumulation of skipped regression checks, outdated test suites, and ignored production data. The result? Unpredictable, catastrophic outages that can sink your business (and your career!). Learn how to identify and pay down your QA Debt before it's too late. It's not about testing more it's about testing SMARTER.
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speedscale

MySQL Mocking with Speedscale's Proxymock: A Complete Guide

Oct 15, 2025 By Alan Mon In Speedscale
Testing database-driven applications is notoriously painful. If your app depends on MySQL, you’ve probably spent hours setting up local databases, running migrations, loading data, and then cleaning everything up just to rerun your tests. This repetitive cycle slows development, breaks pipelines, and introduces inconsistency between local and production environments.
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A Developer's Guide to Improving AI Code Reliability

Oct 13, 2025 By Matt Tanner In Speedscale
You've probably been there: your AI coding assistant just generated what looks like a perfect solution to your problem. Decent code quality, reasonable structure, and even some comments. You run it, and... it works. So you ship it. Three weeks later, your production logs are full of 500 errors from edge cases the AI never considered, or worse, you discover the code has been making unvalidated database calls that could have been prevented with basic input sanitization.
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