Systems | Development | Analytics | API | Testing

Twenty years of boots-on-the-ground testing experience reveals a clear pattern: the industry has moved from tracking manual test cases in Excel sheets, to managing Selenium Grid configurations, to watching algorithms generate scripts in seconds. Right now, if you are in a managerial role, your feeds are absolutely flooded with pitches promising that.

A customer emailed on a Tuesday: checkout hung for ten seconds. I opened our tracing tool, punched in the time window, and got nothing. The trace was sampled out. We keep 1% of traces, like most shops with real traffic do. The one request that actually mattered was in the 99% we threw away. I spent twenty minutes admiring our observability stack before admitting it couldn’t answer a first-grader’s question: what happened to this person? Here’s what I know now.

Smoke testing checks whether a new build is stable enough to test. Sanity testing checks whether a specific fix or change works as expected. Both are quick validation techniques, but they happen at different stages for different reasons. The easiest way to tell them apart: if you just deployed a new build and want to know if core features are still standing, that’s a smoke test.

Writing a load test script from scratch is the boring part. You already have the request you want to hammer: it is sitting in your browser’s network tab, in a Postman collection, or described in an OpenAPI spec. So why retype it as a k6 script or build a JMeter test plan by hand? Now you do not have to. LoadFocus converts a cURL command, a HAR file, a Postman collection or an OpenAPI spec into a runnable k6 script or JMeter.jmx test plan.

Static analysis has always excelled at finding defects, vulnerabilities, and compliance violations. Before AI-assisted code remediation, however, developers still had to research the root cause, design a fix, and manually verify that the correction satisfies the relevant requirements. The new, built-in AI-assisted code remediation feature speeds up this process.

The agentic AI conversation is too obsessed with the front door. Customer-facing agents get most of the attention because they are visible.

As AI takes on more software quality decisions, Sauce Labs becomes the first — and only — dedicated testing platform to earn independent certification for responsible AI governance.

Some approaches to API governance interrupt developers mid-flow, forcing them to context-switch into a separate tool and manually verify their API definition before they can ship. That approach has never really worked. Not because developers don’t care about quality, they do, but because the best time to fix an API is the moment you’re already thinking about it. That’s what has always guided how Swagger grows. Not “come to us.” But “we’ll be there.”

At Perforce Delphix, we have found that referential integrity is very often a deciding factor for enterprises evaluating data masking and test data management solutions. That same requirement is emerging in conversations about synthetic data, as well. Mayank Ahluwalia, Senior Product Manager at Perforce Delphix, has seen this need firsthand in his conversations with enterprise leaders.