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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.

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.

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.

Apple’s first foldable iPhone is here. Your applications need to be ready for a screen that opens, closes, and runs two apps side by side. Perfecto has a long record of supporting new Apple releases, and the iPhone Duo continues it. In this post, you’ll learn what the iPhone Duo means for your testing strategy, how Perfecto helps your team test on it, and how Perforce Autonomous Testing keeps your tests working as devices change. Request Demo Back to top.

Four ways engineering leaders can grow quality engineering capacity so verification keeps pace with AI-accelerated development.

A new Forrester Total Economic Impact (TEI) study commissioned by Confluent, an IBM company and data streaming platform, found that a representative composite organization achieved 137% ROI, USD 2.1 million in net present value and a 10-month payback period. Those are meaningful results. The ROI is notable. What's more interesting is where the value came from. Modernization is often framed as an infrastructure problem. Leaders compare platform costs, migration and operating costs.

Let’s say a regional sales director posts a soft renewal number in the channel. A teammate asks the question that decides the plan: trend, or seasonal blip? Nobody in the thread can answer, so the thread does what threads do. It moves on, and the plan gets anchored to the most confident opinion in the room. The maddening part: the data existed. It was modeled, governed, correct, sitting in the warehouse the whole time. It's not a data problem; the answer was there.

OctoPerf 18.0.0 is out! In version 17 we separated the injection engine from JMeter, and this release is where it starts to pay off: K6 is now available as a load engine next to JMeter and Playwright. Playwright Virtual Users also measure the Core Web Vitals of every page they open. K6 scripts are code, so they usually live in Git next to the application and get reviewed like it. With OctoPerf 18 you can run them without modifying them: This is why we did all that work in OctoPerf 17.