Confluent Blog

Streaming data has become critical to the success of modern businesses. Leveraging real-time data enables companies to deliver the rich, digital experiences and data-driven backend operations that delight customers. For

Collecting and indexing logs from servers, applications, and devices enables crucial visibility into running systems. A log analytics pipeline allows teams to debug and troubleshoot issues, track historical trends, or

Confluent uses property-based testing to test various aspects of Confluent Cloud’s Tiered Storage feature. Tiered Storage shifts data from expensive local broker disks to cheaper, scalable object storage, thereby reducing

With the release of Confluent Platform 6.0, we officially made Tiered Storage generally available. At launch, we supported two major cloud-specific object stores: Amazon S3 and Google Cloud Storage. Today,

This is the third month of Project Metamorphosis, where we discuss new features in Confluent’s offerings that bring together event streams and the best characteristics of modern cloud data systems.

This month, we kicked off Project Metamorphosis by introducing several Confluent features that make Apache Kafka® clusters more elastic—the first of eight foundational traits characterizing cloud-native data systems that map

The combination of streaming machine learning (ML) and Confluent Tiered Storage enables you to build one scalable, reliable, but also simple infrastructure for all machine learning tasks using the Apache

A preview of Confluent Tiered Storage is now available in Confluent Platform 5.4, enabling operators to add an additional storage tier for data in Confluent Platform. If you’re curious about

I am pleased to announce the release of Confluent Platform 5.4. Like any new release of Confluent Platform, it’s packed with features. To make them easier to digest, I want