Systems | Development | Analytics | API | Testing

Migrating a load testing project is rarely hard. It is long, and easy to abandon halfway. OctoPerf 17 ships a NeoLoad migration playbook for AI agents. Real prompts, real output, project downloadable. Target: JPetStore, our public MyBatis demo shop. Every step is reproducible. One User Path, split Init / Actions / End, six containers walking a purchase. Around them: Download it to follow along.

OctoPerf 17.0.0 is available, on the SaaS platform and for On-Premise installations. It rebuilds how test results are stored and read, upgrades Playwright, and considerably extends what an AI agent can do through the OctoPerf MCP server. One thing to know before you upgrade. A result recorded before this version must be updated before its report shows data again. Nothing is lost, and the update runs on its own the first time you open the report.

EHR interoperability enables secure, accurate clinical data exchange across healthcare systems. It requires aligned APIs, patient identity, data standards, security, and governance.

Every testing vendor says "AI-powered" now. Fewer of them can show you the actual verification pipeline underneath that claim: what gets checked, what gets trusted without checking, and what happens the moment something breaks. This is that pipeline, as I run it against True Production Insights, formerly known as TrueTest, every time we ship a change to it.

Playwright has gone from a browser automation library most QA teams had never heard of to one of the most-searched testing frameworks in the industry, and interest keeps climbing. If you're evaluating it for your team, comparing it to Selenium or Cypress, or just trying to understand what the interest is about, this guide covers the fundamentals: what Playwright actually is, how it works, what it's used for, and where to go next once you're ready to dig into best practices. THE SHORT ANSWER.

Playwright makes it easy to get a test running quickly. It's harder to keep a whole suite of Playwright tests reliable six months later, once your app has changed, your team has grown, and nobody quite remembers why a particular test is flaky three days a week. If you're new to Playwright, our guide to what Playwright is and how it works is a good place to start first.

Testing across web, mobile, and performance layers has become one of the hardest problems in enterprise software delivery. Teams juggle fragile scripts, siloed tools, and mounting maintenance work that slows every release. AI cross-platform testing changes that equation, and Perforce Autonomous Testing puts it within reach. In this post, you will learn what AI-driven cross-platform testing is, why it matters for QA leaders, and how Perforce Autonomous Testing works from setup to execution.

In April 2026, when our Perforce engineering team was introduced to Claude, my team didn't jump straight into using it. We sat down, mapped our entire development lifecycle, and asked one focused question: Where does AI create the highest impact for us, specifically?

Spike testing applies a sharp, sudden increase in load, holds it briefly, then drops back. It is not about the maximum number of users; a system can pass a stress test at a higher level and still fail a spike at a lower one, because the failure comes from the rate of change rather than the volume.

Writing Tests from Requirements often starts with the same decision: how many scenarios does this change actually need? The number of Tests needed for a Requirement depends on the behavior it describes. A small change may require only a few Tests, while a feature with several acceptance criteria, user roles, and possible outcomes may need a broader set. AI Test Case Generation in Xray now lets testers account for that difference before generation begins.