Confluent Blog
Queues for Apache Kafka® Is Here: Your Guide to Getting Started in Confluent
Confluent announces the General Availability of Queues for Kafka on Confluent Cloud and Confluent Platform with Apache Kafka 4.2. This production-ready feature brings native queue semantics to Kafka through KIP-932, enabling organizations to consolidate streaming and queuing infrastructure while...
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.
Confluent Intelligenceの新機能：Real-Time Context Engineのアップグレードや新しいモデルのサポート、ML関数など
Real-Time Context Engineによるクエリ機能の強化、PII検出、センチメント分析、およびTimesFM、Anthropic、Fireworks AIの各モデルのサポートなど、Confluent Intelligenceの新機能をご紹介します。
Confluent Cloud の新機能：あらゆるスケールであらゆるワークロードに対応するデータストリーミング
Confluent Cloudの2026年第1四半期リリースでは、Queues for Kafkaによるメッセージキュー機能や、KCPによる移行の簡素化、Confluent IntelligenceによるAI機能の強化に加え、fetch-from-followerやclient quotasなど、スケーラビリティやコスト制御を高める機能が追加されています。
Scaling the Streaming Stack: Introducing the Sell with Confluent Partner Program
Sell with Confluent is our new reseller engagement model, designed to empower partners with streamlined quoting, automated incentives, and scalable growth.
How to Break Off Your First Microservice
Learn how to safely break off your first microservice from a monolith using a low-risk, incremental migration approach.
Apache Kafka 4.2.0 Release Announcement
Apache Kafka 4.2.0 is here. Explore production-ready share groups, Kafka Streams rebalance GA, new metrics, security enhancements, and upgrade details.
Beyond Zero-Ops: Architectural Precision for MongoDB Atlas Connectors
Master MongoDB Atlas Connectors on Confluent Cloud. Go beyond basic setup with architectural best practices for Source and Sink. Learn to ensure idempotency, handle CDC events, tune performance, and configure precision filtering for resilient, high-velocity data pipelines.
How to Future-Proof Architectures With Continuous Availability Via Hybrid & Multicloud
Learn how to design future-proof architectures for hybrid and multicloud environments, balancing portability, resilience, and long-term flexibility and using Kafka to implement continuous availability.
Do Customers Really Care If You Love Them?
Products win trust initially. Sustained value, partnership, and execution earn loyalty, renewal, and advocacy.
Disaster Recovery in 60 Seconds: A POC for Seamless Client Failover on Confluent Cloud
Kafka client failover is hard. This post proposes a gateway‑orchestrated pattern: use Confluent Cloud Gateway plus Cluster Linking to reroute traffic, reverse replication, and enable one‑click failover/failback with minimal RTO.
Focal Systems: Boosting Store Performance with an AI Retail Operating System and Real-Time Data
Discover how Focal Systems uses computer vision, AI, and data streaming to improve retail store performance, shelf availability, and real-time inventory accuracy.
Streaming Data Integration with Apache Kafka®
Streaming data integration supports enriched, reusable, canonical streams that can be transformed, shared ,or replicated to different destinations, not just one.
Cloud API Keys vs Resource-Specific API Keys in Confluent Cloud
Learn the difference between cloud API keys and resource-specific API keys in Confluent Cloud, plus best practices for service accounts and production security.
Empowering Customers: The Role of Confluent’s Trust Center
Learn how the Confluent Trust Center helps security and compliance teams accelerate due diligence, simplify audits, and gain confidence through transparency.
How a Tier‑1 Bank Tuned Apache Kafka® for Ultra‑Low‑Latency Trading
A global investment bank and Confluent used Apache Kafka to deliver sub-5ms p99 end-to-end latency with strict durability. Through disciplined architecture, monitoring, and tuning, they scaled from 100k to 1.6M msgs/s (<5KB), preserving order and transparent tail latency.
Thunai Automates Customer Support with AI Agents and Data Streaming
Learn how Thunai uses real-time data streaming to power agentic AI, achieving 70–80% L1 support deflection and cutting resolution time from hours to minutes.