Systems | Development | Analytics | API | Testing

The ideal data streaming platform empowers you to handle every type of data movement with confidence. In our first Confluent Cloud launch of 2026, we’re delivering on the promise of Apache Kafka for any workload, at any scale.

The types of software testing define how modern systems maintain stability, performance, and security in fast release cycles. In 2026, software is API-driven and continuously deployed, so testing is no longer a final step – it is embedded across the development lifecycle. Each testing type addresses specific risks and helps teams build a strong foundation of software testing instead of relying on random test cases. Let’s explore how these testing types work in practice.

The fun part of data analysis: Chatting with your data Taking BI on-the-go with a Responsive UI Putting you in control of your reports Enterprise scale without the headache Final thoughts Business decisions rarely happen in a straight line. They involve follow-ups, hunches, and "wait, what about...?" moments. Your BI software should be able to keep up. With the release of Yellowfin 9.17, we are making analytics feel more conversational, more flexible, and easier to use in the moments that matter.

An important question for CXOs and strategy heads alike arises as businesses grow internationally: Are we scaling globally merely to increase capacity, or are we also building capability? Global Capability Centres (GCCs), formerly known as Global In-House Centres (GICs), fill that need by acting as strategic powerhouses that are more than just back-end support engines.

A Response to Gartner’s Latest Research Last week, Gartner published a report titled MCP Servers Will Fuel the Next AI Revenue Surge — Context as a Service (1) that should be required reading for every enterprise technology leader. Then, Kong CEO Augusto Marietti (Aghi for short) wrote out his thoughts on the subject and why context is king. I’d like to continue that conversation.

Gartner published a report last week that I think marks a genuine inflection point for how enterprise technology leaders should think about AI strategy. The headline finding: we have crossed a threshold where competitive advantage in the AI era is no longer about access to data — it's about the semantic intelligence wrapped around it. Gartner calls this the "context economy," and they believe it will reshape how software is built, sold, and monetized over the next several years. I agree.