Systems | Development | Analytics | API | Testing

Announcing Kong AI Gateway 2.0: Built for the Pace of Agentic AI

We have big news for platform and AI infra teams: *Kong AI Gateway 2.0 is available today in private beta*. It runs on its own dedicated runtime, ships on its own release cadence, and carries a completely reimagined user experience designed around the way teams actually build with AI: models, MCP servers, and agents as first-class citizens, not plugins bolted onto an API gateway.

AI to Write Rules, or AI to Make Decisions?

Last April FloQast, an American maker of accounting software, published something unusual: a detailed engineering post on Amazon Web Services’ machine-learning blog, co-authored with AWS personnel, explaining precisely how its AI-powered transaction-matching feature works under the hood. The post described cloud infrastructure, model selection, and the specific technique (generating matching rules from user-supplied examples) that powers its AutoRec product.

Bitrise Remote Development Environments demo

In this short demo, our Senior Solutions Engineer Naveen Nazimudeen introduces Bitrise Remote Developer Environments (RDEs) and shows how they speed up mobile development. If you'd like to learn more, get in touch with us! Bitrise provides a full-stack, vertically integrated mobile DevOps solution that unites the tools, processes and testing frameworks engineering teams need to build best-in-class mobile experiences. Over 400,000 developers use Bitrise’s products: Bitrise CI, Build Cache, Release Management, and Insights.

Cloudera Agent Studio & Iceberg MCP to Monitor Table Health

In this video, Cloudera’s Dipankar demonstrates how to build an AI agent in Cloudera Agent Studio powered by an open-source Apache Iceberg MCP Server. As a real-world use case, the agent monitors Apache Iceberg table health by analyzing metadata for issues such as small files, partition skew, snapshot history, and other operational signals. Subscribe to stay ahead of the curve with the latest in data strategy, open architectures, and enterprise AI innovations.

How Enterprise Teams Are Validating AI-Generated Code at Scale | Perforce 2026

Your testing strategy was built for a world before AI wrote code. That world is gone. AI is now generating code, reviewing pull requests, writing tests, and analyzing defects, faster than any team can validate it manually. In this session, Perforce CTO leaders Anjali Arora and Rod Cope sit down with VP of Product Steven Feloney to break down why traditional test automation can't keep pace, and what comes next.

Java debugging: how to debug Java code in IntelliJ, Eclipse, and jdb

An effective Java debugging strategy lets us pause execution, inspect data, and observe real execution rather than relying on vague assumptions. The complexity of the Java Virtual Machine creates unique challenges, but a focused approach will turn this complexity to our advantage. This guide will equip you with the tools to do this, looking at: By the end, you’ll have a practical workflow to debug Java reliably across local and remote environments.

Xray and Lynqa: Agentic AI Test Execution in Jira

AI is becoming part of every stage of the testing lifecycle. Teams are using it to analyze requirements, design test cases, generate automation scripts, and accelerate execution activities that previously required significant manual effort. Within Xray, AI already helps transform Jira requirements into actionable test cases with AI Test Case Generation.

The Skill AI Can't Generate: Why Discernment Is the New Data Literacy

For more than a decade, I have argued that the most valuable skill in a data-driven organisation is not access to information. It is the judgment to know when that information is wrong. AI has made that skill more important, not less. When I wrote about AI literacy in 2023, the pushback I heard most often was that the technology was not yet good enough for the question to matter. Now it is. AI can generate answers, summaries, recommendations, code, analysis, and increasingly, actions.