Confluent Blog

Due to the distributed architecture of Apache Kafka®, the operational burden of managing it can quickly become a limiting factor on adoption and developer agility. For this reason, it is

The rise of the cloud introduced a focus on rapid iteration and agility that is founded on specialization. If you are an application developer, you know your applications better than

Note: Please see the blog post Introducing Cluster RBAC, Audit Logs, and BYOK for Enterprise-Grade Security for the latest updates.

The cloud opens up exciting new opportunities for information gathering, analysis, and sharing that can make every organization’s products and services better. Thanks to the cloud and its decentralized nature,

The promise of cloud computing is simplicity, speed, and cost savings. But what about workloads that can’t move to the cloud? Are they stuck using expensive legacy tooling and practices?

Since the MongoDB Atlas source and sink became available in Confluent Cloud, we’ve received many questions around how to set up these connectors in a secure environment. By default, MongoDB

Near-real-time insights have become a de facto requirement for Azure use cases involving scalable log analytics, time series analytics, and IoT/telemetry analytics. Azure Data Explorer (also called Kusto) is the

Hybrid cloud architecture and accelerated cloud migrations are becoming the norm rather than the exception, as our increasingly digital world introduces certain challenges along the way, including modernizing existing application/architecture,

If you are taking your first steps with Apache Kafka®, looking at a test environment for your client application, or building a Kafka demo, there are two “easy button” paths

Whether you are a developer working on a cool new real-time application or an architect formulating the plan to reap the benefits of event streaming for the organisation, the subject