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By Alan Mon
The dashboards are red, the alerts are firing, and Slack has officially become a war room. Someone has asked, "Anyone else seeing this?" and 14 people have immediately responded with screenshots. Welcome to another day in distributed systems. The recent GitHub outage is a great reminder of how complicated modern applications have become. Services talk to services, infrastructure scales up and down, retries multiply traffic, and dependencies behave in ways nobody expected. Thankfully, we have observability.
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By Ken Ahrens
The query count in our snapshot drawer went blank, and the unit test for that request kept passing. When we went looking in recorded traffic, the API gateway had rejected that request 210 times in a single recording. Every one of those rejections came back as 200 OK. So we searched the rest. We record our own API gateway with Speedscale, and two recording windows from November 3 to 5 (about 38 hours between them) held 1,238 responses with gRPC status INVALID_ARGUMENT. All 1,238 returned HTTP 200.
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By Matt LeRay
This guide uses Speedscale’s readiness scorecard to compare three builds of a Spring Cloud Gateway service on Kubernetes. It covers a regression that still meets the test’s pass-rate goal, a GET-only retry evaluated under injected dependency failures, and a CI check that requires a Ready verdict. The example uses api-gateway from the banking demo’s readiness-demo branch. The three image tags identify distinct builds.
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By Matt LeRay
Speedscale’s automatic release readiness scorecard grades a completed replay against the release rules in its test configuration. It returns a Ready or Not ready verdict, letter grades for ten metric families, a weighted score and a confidence factor. This feature provides a concrete and automatic baseline for whether new releases are ready for production. The underlying test runs recorded traffic against a build, with dependencies mocked from the recording.
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By Matt LeRay
Your Playwright test clicks Next page, waits for the item list, and times out. Now you’re digging through a trace to find out whether the page broke or an API call failed. Traditional browser-testing workflows focus on clicks, page state and UI assertions. Those checks tell you whether a user journey works, but investigating a failure also means understanding the APIs behind the page.
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By Matt LeRay
Change one field in a.proto from double to string, and nothing complains. The code compiles, the deploy goes green, and a service still built from the old contract keeps answering with a double. Here’s what Go’s protobuf runtime does when a client on the new contract reads that answer: No error. risk_score comes back empty, and the nine bytes of the double are tucked away as unknown fields.
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By Matt LeRay
Replay a GraphQL recording at the server that produced it, and every request comes back 200 OK. Here is one of those 200s, from a Session query whose recorded token has expired: A GraphQL server reports most failures inside a successful HTTP response, so any check that stops at the status code passes this request. And that is the second way GraphQL hides from URL-shaped tooling.
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By Matt LeRay
A readiness check should make a release safer. During one release validation, ours kept Kraken’s traffic replays stuck in Initializing until they timed out. The operator was asking Kubernetes for EndpointSlices. Its installed permissions did not allow that request. The code needed a real cluster, the generated permissions, and a replay trying to start before that mistake became obvious. Kraken put those pieces together during release validation.
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By Alan Mon
On October 20, a power failure in one of Google Cloud’s three London zones disrupted Revolut, Lloyds, HSBC and others for hours. One zone failed, errors spread region-wide, and Google warned customers they might not be able to create new workloads to fail over to. Most teams find out how resilient they are during an outage, not before one. These five questions let you find out first.
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By Matt LeRay
What happens to transaction posting when statement traffic gets expensive? That’s the question a bank’s platform team actually needs answered before a busy month-end. It’s also a question most load tests can’t ask, because they turn one dial for the whole recording. Statements get heavier, posting gets heavier, and the average latency across both looks fine right up until customers can’t move money.
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By Speedscale
End-to-end (E2E) testing brings your entire system together in a staging or UAT environment to test real user paths and ensure core functions work as expected. However, because E2E tests are non-comprehensive and miss edge cases, they must be combined with other testing methodologies. Learn more: speedscale.com.
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By Speedscale
Learn what a unit test is, how AI coding assistants can write them for you, and the three key conditions every unit test should check to ensure software quality. Learn more: speedscale.com.
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By Speedscale
Learn how to test your application's fallback mechanisms by intentionally injecting chaos and simulated dependency failures into recorded API traffic. Easily configure scoped rules to inject status code errors or delays during mock runs to verify your app handles failure gracefully. Learn more: speedscale.com.
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By Speedscale
Learn how AI handles different types of testing, from simple unit tests to complex end-to-end setups. Discover where AI succeeds in writing test code and where human strategy is still needed. Learn more: speedscale.com.
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By Speedscale
While AI coding agents increase initial build speed, they often lack context about real-world user behavior, leading to downstream production bugs. Watch to learn how to move beyond basic agent-on-agent reviews and set up a true "Quality Factory" using: Check out our demos or get started free: speedscale.com.
Test AI-Generated Code with Real Traffic#aiagents #devops #observability #shiftleft #softwaretesting
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By Speedscale
AI can generate code in seconds, but testing it against real production behavior is where developers get stuck. Learn how capturing and replaying actual production traffic in development helps you catch bugs before you deploy!
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By Speedscale
Learn how to quickly set up a load testing foundation for your Node app using the free ProxyMock tool combined with an AI coding agent. This walkthrough demonstrates how to record traffic, mock dependencies, and analyze latency distribution results in just a few simple steps. Learn more: speedscale.com.
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By Speedscale
DevOps customers are rejecting standalone AI agents and web interfaces in favor of integrating context directly into their existing harnesses, such as Copilot or Claude. Rather than logging into separate tools, developers prefer combining models and technologies within a single context window to streamline software development and debugging. Learn more: speedscale.com.
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By Speedscale
Learn how to track cluster performance in real time using the replay progress panel, which highlights key phases including provision, mock, app, load, analyze, and result. You will also discover how to easily troubleshoot failed runs by expanding component lanes to review specific step reasons and cluster events. Learn more: speedscale.com.
Feature Spotlight: Automatic Testing with Proxymock MCP Skills #aiagents #mcpserver #softwaretesting
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By Speedscale
Learn how to integrate your AI coding agent with Speedscale using the MCP server to record, replay, tune mocks, and analyze reports directly within your workspace. Streamline your testing workflow by letting your agent automatically capture traffic, resolve failing responses, and optimize match rates. Learn more: speedscale.com.
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Continuous Resiliency from Speedscale gives you the power of a virtual SRE-bot working inside your automated software release pipeline. Forecast the real-world conditions of every build, and know you’ll hit your SLO’s before you go to production.
Feed Speedscale traffic (or let us listen) and we’ll turn it into traffic snapshots and corresponding mock containers. Insert your own service container in between for a robust sanity check every time you commit. Understand latency, throughput, headroom, and errors -- before you release! The best part? You didn’t have to write any scripts or talk to anyone!
Automated Traffic Replay for Every Stakeholder:
- DevOps / SRE Pros: Understand if your app will break or burn up your error budget before you release.
- Engineering Leads: Let Speedscale use traffic to autogenerate tests and mocks. Introduce Chaos testing and fuzzing.
- Application Executives: Understand regression/performance, increase uptime and velocity with automation.
Before you go to production, run the projection.