Systems | Development | Analytics | API | Testing

The Apache Kafka community is proud to announce the release of Apache Kafka 4.1.0. This blog post highlights the many new features and improvements included in this release. For a full list of changes, be sure to check the release notes. Queues for Kafka (KIP-932) is now in preview. It's still not ready for production, but you can start evaluating and testing it. See the preview release notes for more details. This release also introduces a new Streams Rebalance Protocol (KIP-1071) in early access.

In today’s cost-conscious climate, every line item on your cloud bill is under the microscope. That makes now the ideal time to rethink your data streaming strategy. For many teams, using a hyperscaler-hosted Apache Kafka service feels like the easy choice—one vendor, one bill, no additional contracts, and minimal setup. It makes sense early on, especially for small-scale projects or basic use cases. But, as your Kafka usage grows and becomes mission-critical, that simplicity comes at a cost.

APIs are the foundation of modern software ecosystems—connecting applications, services, and databases so information can flow securely and efficiently. But as systems become more complex and businesses demand faster innovation, traditional, manual approaches to API management no longer scale. That’s where AI-powered API gateways come in.

If your organization relies on Informatica’s Information Lifecycle Management (ILM) for business reporting, recent announcements about the platform entering maintenance mode have likely raised important questions about your reporting strategy. Understanding what this transition means and how to protect your critical data access are essential for maintaining business continuity.

Be “Day 0 Ready” with our Pixel 10 Series Testing — eliminate coverage gaps and stay ahead of your users.

Minimize data loss during planned DR activities and ensure business continuity with soft failover in BigQuery Managed Disaster Recovery.

In the software development lifecycle (SDLC), deployment is the final step, the one where your app is delivered to users. Traditionally, this has meant installing software on the customer’s premises or hosting it in-house. But this approach comes with significant overhead: With the rise of cloud computing, Software as a Service(SaaS) and Platform as a Service(PaaS), these manual steps are quickly being replaced.

When it comes to dashboards, there are usually two schools of thought: self-service dashboards users can build themselves or finished dashboards. In our world, we call these finished dashboards managed dashboards. There is no right or wrong choice. Self-service dashboards are excellent for exploration and flexibility. Managed dashboards are just as valuable because they give users exactly what they need without forcing them to do extra work to get to the data.