Connecting multiple systems and exchanging data among them is afrequent requirement in many business scenarios. This typically involves one or many source systems, an intermediary processor, and one or many destination systems. Some organizations invest in purpose-built solution suites such as Data Warehouse, Master Data Management (MDM), or Extract, Transform, Load (ETL) platforms, which, in-theory, cover a wider spectrum of requirements.

We are proud to announce the release of Apache Kafka® 3.7.0. This release contains many new features and improvements. This blog post will highlight some of the more prominent features. For a full list of changes, be sure to check the release notes. See the Upgrading to 3.7.0 from any version 0.8.x through 3.6.x section in the documentation for the list of notable changes and detailed upgrade steps.

Everything you need to deploy high-performance serverless apps is available in Singapore: Singapore is our first Asia-Pacific region in GA, joining Washington, D.C. and Frankfurt, Germany, EU in the GA club with all our services available in these 3 regions. The new Eco instances are now available in Singapore and allow you to start for only $1.61/month, billed per second.

Since we launched the Open Preview of our serverless Apache Flink® service during last year’s Current, we’ve continued to add new capabilities to the product that make stream processing accessible and easy to use for everyone. In this blog post, we will highlight some of the key features added this year.

The class of 2027 saw a massive influx of applications at top universities across the United States. Harvard received close to 57,000 applications for the class of 2027, while MIT received almost 27,000. UC Berkeley and UCLA, meanwhile, received 125,874 and 145,882 respectively. Manual transcript processing is an uphill battle for educational institutions at every level.

Today marks a monumental milestone: Autoscaling is now in public preview and available to all our users. Don't like to wake up in the middle of the night to scale up? Do you still have nightmares of the time you forgot to scale down your cloud infrastructure? Autoscaling is the answer: we adjust infrastructure to demand dynamically. We built our autoscaling feature to be: Autoscaling is powerful and raises some questions: It was the most requested feature on our feedback platform with new regions.