Systems | Development | Analytics | API | Testing

Use Conversational Analytics in BigQuery to query data, run analyses, and generate reports using natural language on data in BigQuery and Lakehouse.

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.”

WWDC 2026 delivered plenty for app developers to talk about, but some of the most consequential announcements were aimed squarely at the people running the infrastructure underneath. We've already covered the under-the-radar announcements for iOS developers and what Xcode 27's Device Hub means for CI/CD. This one is for the fleet operators. If you run Mac infrastructure at any scale, the Virtualization framework is already part of your life. On Apple Silicon, it's the only way to run a macOS guest.

If you're building iOS apps on Bitrise and using one of the Xcode 26 edge stacks, you must switch to the Xcode 26 stable stack before July 31, 2026.

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.

Project leaders and QA engineers understand that cloud testing challenges are not created equal. Some issues are inconvenient but manageable, while others can jeopardize releases, security, or compliance. The real expertise lies in identifying which obstacles are truly business-critical – the ones that, if ignored, can cascade into outages, breaches, or regulatory failures.

As software vendors place more controls around data access, enterprises must decide whether their future AI capabilities will be defined by their strategy or their vendors' policies.

Organizations have rapidly adopted artificial intelligence, but a stark divide is emerging: those who are embedding AI into the core of their operations, and those who are treating it as a standalone tool. According to a recent Harvard Business Review Analytic Services survey, only a small share of resondents say their organization has largely integrated AI into workflows.

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.

A year ago we announced that Databox is becoming an AI-first company. At the time, that mostly meant what it meant for many companies in 2025: AI becoming a strategic priority. Teams were encouraged to experiment and adopt new tools, as it was clear that AI wasn’t a trend we could ignore. That was the easy part. What’s become clear over the last year is that there’s a significant difference between being AI-first and being AI-native.