Systems | Development | Analytics | API | Testing

For the tenth consecutive time, Gartner has named Google Cloud Apigee a Leader in the 2025 Gartner Magic Quadrant for API Management.

A few years ago, we looked across many deployments and noticed a pattern: teams would build prototypes, spin up ML pipelines, and then stall. The model’s accuracy dropped. The “aha insights” dried up. The data scientists would get stuck waiting for dashboards to refresh, or data to be cleaned.AI is sexy. It sells. But it doesn’t do itself. The missing piece? Data readiness. Not just fast data.

The term “Behavior Driven Development”, or BDD, is an umbrella term for a wide variety of techniques. The general principles of BDD include reframing tests as descriptions of system behavior – “when I do one thing, I should see this result”. Historically, those descriptions were the output of a computer program. Over time, the uses of BDD shifted toward Gherkin, an English-like but precise language.

Modern businesses don’t run in just one place. Your applications might live in Amazon Web Services (AWS), your analytics in Microsoft Azure, and critical systems on-premises. The challenge? Keeping all that data connected and flowing in real time—without adding complexity or risk. As more organizations adopt these multicloud strategies, the need for secure, private data replication has become critical.

‍ Trust is the currency in FinTech - and in 2025, that currency is under siege. Cybercrime is accelerating. Global costs from cyber attacks are projected to hit USD 10.5 trillion annually in 2025, up sharply from about USD 3 trillion in 2015. Meanwhile, in the financial sector where your app may live, the stakes are even higher: the average cost of a data breach in financial services is pegged at USD 6.08 million.

Kafka cluster-to-cluster data replication is critical to many use cases: disaster recovery (DR), cloud or data center migration, testing applications with production-like data, and multi-region data distribution. Easy replication of data between clusters: The business case is clear, but the cost model is not. Some solutions appear free but impose heavy operational burden.

In August, Katalon delivers a blend of AI intelligence and enterprise readiness. From TestCloud’s flexible configurations and TestOps’ new AI-powered root cause analysis, these updates enable teams to debug smarter, share insights more widely, and maintain quality at scale.

With software applications growing increasingly complex, the way we test them to guarantee reliability and security must also increase accordingly. Among the many types of testing available, Grey Box Testing stands out as a hybrid method that presents us with a balanced perspective of insights from both black box and white box testing. It doesn`t matter if you’re a developer, QA engineer, or someone new to testing; grey box testing is important to everyone in today’s technological landscape.

If you’ve been following Kong, you know that Kong was the first in the API platform space to introduce an enterprise-grade AI Gateway for LLM workloads. Today, we’ve also introduced a new enterprise-grade MCP Gateway to ensure that you can roll out production-ready MCP deployments. But we are focused on more than just the Gateway. Today, we’re excited to announce additional MCP workflow support in the Konnect Developer Portal and a brand new MCP integration solution, the MCP Composer.

Today, we're open-sourcing Volcano SDK, a TypeScript SDK for building AI agents that combines LLM reasoning with real-world actions through MCP tools. Why Volcano SDK? One reason: because 9 lines of code are faster to write and easier to manage than 100+. Without Volcano SDK? You'd need 100+ lines handling tool schemas, context management, provider switching, error handling, and HTTP clients. With Volcano SDK: 9 lines. Look how we compress 100+ lines with the following example: That's it.