Systems | Development | Analytics | API | Testing

Every team in your company has the same problem: they need answers from data, but getting them is never fast. Marketing wants to know which campaigns are working. Sales wants to know which deals are stalling. Leadership wants to know if the business is on track. Each team asks different questions, but they all end up in the same place—waiting for someone else to pull the numbers. What if your teams could just ask questions and get answers instantly? That’s what Databox MCP enables.

Struggling with flaky tests and slow automation? Explore the best AI-powered testing tools of 2026 — and why Sauce Labs stands out.

Discover how AI helps continuously test games 24/7, catch bugs earlier, and eliminate dev crunch.

This week, we had a chat with one of our enterprise customers about their thoughts on AI inside their Yellowfin environment. They’re currently running version 9.15 and use Yellowfin as the primary BI layer inside their app.

One of the most common infrastructure changes Java developers and operators are dealing with today is the migration from Oracle Java to OpenJDK. The reason is the licensing changes made by Oracle and the maturity of the OpenJDK distributions. The migration process is quite simple: replace the JDK, recompile the code, and redeploy the application. However, the differences between the two runtimes can lead to unexpected issues that are not caught by unit tests.

When building AI experiences, choosing between WebSockets and HTTP isn't always straightforward. Which protocol is better for streaming LLM responses? How do you maintain continuity when users switch devices mid-conversation? Should you use both? The answer depends on the type of AI experience you're building. Modern AI applications often require both protocols, each serving different purposes. The key question is: how do you decide which communication pattern fits each scenario in your AI stack?

In the highly dynamic environment of modern engineering, an appropriate strategy for API quality is more important than ever. We are pleased to announce that Speedscale has been named in the latest “Market Guide for API and MCP Testing Tools” report from Gartner. As software development is shifting towards complex distributed architectures, integrating Model Context Protocol (MCP) for AI-based workflows, the need for realistic testing has never been higher.