Systems | Development | Analytics | API | Testing

We’re proud to share that Kong Insomnia has been recognized as a vendor in the Gartner Market Guide for API and MCP Testing Tools in February, 2026. In a rapidly evolving landscape where AI-driven integration and MCP servers are reshaping how APIs are built, tested, and consumed, being recognized by Gartner validates what our community and customers already know: Insomnia is a serious, enterprise-ready platform for modern API development and testing.

‍Mobile development has a reputation for being slow, complex, and harder than it needs to be. Platform quirks, rigid review gates, and ever-growing app complexity can make it feel like the toolchain is working against you. But the data tells a different story. We analyzed tens of millions of builds across thousands of mobile teams on Bitrise, spanning three years of real-world data from 2022 to 2025. The results challenge some common assumptions, and confirm others.

Exceptions are inevitable. It’s how we deal with them that matters. An effective exception handling regime is the difference between an app that only works in sandbox and one that can adapt and scale in the real world. JavaScript can throw up all kinds of weird and wonderful exceptions, because it runs in inherently unpredictable environments. So we’ve put together this guide to give you a clear, repeatable plan for handling them.

If you’re a mobile developer running builds on Jenkins, you already know the drill: a flaky agent goes down on a Friday afternoon, your Xcode version is three months behind, and the DevOps engineer who set the whole thing up left six months ago. The builds ship eventually - but at what cost? Jenkins is a powerful, battle-tested automation server. For teams building web backends or managing complex polyglot pipelines, it earns its place.

AI is reshaping how software gets built, tested, and delivered. For quality engineering teams, AI agents promise extraordinary acceleration by automating analysis, executing tests, generating assets, and orchestrating tasks across the SDLC. But when enterprises begin experimenting at scale, new challenges appear. Where are these agents running? What exactly are they doing? Who approves their decisions? How do we govern them safely?

Queues for Kafka is now in General Availability (GA) on Confluent Cloud and is coming soon to Confluent Platform, coinciding with the Apache Kafka 4.2 release. This milestone brings production-ready queue semantics and elastic consumer scaling natively to Kafka through KIP-932, enabling organizations to consolidate their messaging infrastructures while gaining elastic consumer scaling and per-message processing controls. Get started.