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Technology
Aiven, Confluent, Redpanda, StreamNative and Ververica Form Streamhouse Working Group
New industry initiative establishes an open category for data architectures that power real-time applications and AI agents
KCP: How to Migrate to Confluent Cloud in Days, Not Weeks
Learn how to migrate to Confluent Cloud in hours using Confluent’s open source Kafka Copy Paste tool. Get an in-depth introduction to the KCP tool and a walk-through of the four steps of migrating from MSK to Confluent Cloud using the tool.
AI Tools for Builders — Confluent's MCP Server & Agent Skills
Confluent's AI developer tools are now GA: an open-source local MCP server, a managed MCP server, and Agent Skills. Together they give AI coding assistants direct access to your streaming platform — the tools to act on it and the domain knowledge to build correctly.
Sharpening your Stream Processing Skills with Kafka Tutorials
Event stream processing solves many business challenges, from big data ingestion and data integration, to real-time data processing and IoT. It gives you the ability to analyze big data streams […]
Kafka Connect Elasticsearch Connector in Action
The Elasticsearch sink connector helps you integrate Apache Kafka® and Elasticsearch with minimum effort. You can take data you’ve stored in Kafka and stream it into Elasticsearch to then be […]
Mock APIs vs. Real Backends – Getting the Best of Both Worlds
When building API-driven web applications, there is one key metric that engineering teams should minimize: the blocked factor. The blocked factor measures how much time developers spend in the following […]
Introducing Confluent Developer
Today, I am pleased to announce the launch of Confluent Developer, the one and only portal for everything you need to get started with Apache Kafka®, Confluent Platform, and Confluent […]
99th Percentile Latency at Scale with Apache Kafka
Fraud detection, payment systems, and stock trading platforms are only a few of many Apache Kafka® use cases that require both fast and predictable delivery of data. For example, detecting […]
Turning Data at REST into Data in Motion with Kafka Streams
The world is changing fast, and keeping up can be hard. Companies must evolve their IT to stay modern, providing services that are more and more sophisticated to their customers. […]
Celebrating Over 100 Supported Apache Kafka Connectors
We just released Confluent Platform 5.4, which is one of our most important releases to date in terms of the features we’ve delivered to help enterprises take Apache Kafka® and […]
Apache Kafka as a Service with Confluent Cloud Now Available on Azure Marketplace
Less than six months ago, we announced support for Microsoft Azure in Confluent Cloud, which allows developers using Azure as a public cloud to build event streaming applications with Apache […]
Announcing ksqlDB 0.7.0
We are pleased to announce the release of ksqlDB 0.7.0. This release features highly available state, security enhancements for queries, a broadened range of language/data expressions, performance improvements, bug fixes, […]
Seamless SIEM – Part 2: Anomaly Detection with Machine Learning and ksqlDB
We talked about how easy it is to send osquery logs to the Confluent Platform in part 1. Now, we’ll consume streams of osquery logs, detect anomalous behavior using machine […]
Integrating Elasticsearch and ksqlDB for Powerful Data Enrichment and Analytics
Apache Kafka® is often deployed alongside Elasticsearch to perform log exploration, metrics monitoring and alerting, data visualisation, and analytics. It is complementary to Elasticsearch but also overlaps in some ways, […]
Seamless SIEM – Part 1: Osquery Event Log Aggregation and Confluent Platform
Osquery (developed by Facebook) is an open source tool used to gather audit log events from an operating system (OS). What’s unique about osquery is that it uses basic SQL […]
Building a Materialized Cache with ksqlDB
When a company becomes overreliant on a centralized database, a world of bad things start to happen. Queries become slow, taxing an overburdened execution engine. Engineering decisions come to a […]
Streaming Machine Learning with Tiered Storage and Without a Data Lake
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 […]