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Realtime Compute for Apache Flink

Alibaba Cloud Pushes Open-Source Apache Flink Toward Agentic Streaming for AI

At Flink Forward Asia 2026, Alibaba Cloud shared plans to push Apache Flink towards “agentic streaming”, driven by the rise of agents and multimodal data in the agentic AI era.

Apache Flink Agents 0.3 Release Announcement

Flink Agents brings AI agents into the Flink streaming pipeline — an agent becomes a first-class operator in your real-time datastream.

Apache Fluss (Incubating): Redefining Streaming Storage for Real-time Data Analytics and AI

Explore Apache Fluss, the revolutionary streaming storage solution bridging traditional systems and lakehouse architectures for real-time data analytics and AI.

Introducing Fluss: Streaming Storage for Real-Time Analytics

Today, we are excited to introduce Fluss, a cutting-edge streaming storage system designed to power real-time analytics.

Understanding Fluss Partial Update

Traditional streaming data pipelines often need to join many tables or streams on a primary key to create a wide view.

Why Fluss? Top 4 Challenges of Using Kafka for Real-Time Analytics

Jark Wu Creator of Fluss project The industry is undergoing a clear and significant shift as big data computing transitions from offline to real-time processing.

Apache Fluss(Incubating) vs. Apache Paimon: Two Engines for the Real-Time Lakehouse

Apache Fluss and Paimon:Fluss delivers sub-second real-time data for Flink (reducing state bloat); Paimon is a streaming lakehouse format with ACID and minute-level latency.

Building a Cloud-Native Productivity Tracking Architecture for Distributed Teams

This article introduces an Alibaba Cloud reference architecture for real-time, multi-tenant productivity tracking of distributed engineering teams.

Big Data & AI Platform Monthly Newsletter — April 2026

Brought to you by the Alibaba Cloud Big Data & AI Product Team.

Build Alibaba Cloud API Gateway Monitoring with Realtime Compute for Apache Flink and SLS

This article introduces how to build a real-time, scalable API gateway monitoring system for Alibaba Cloud Open Platform using Realtime Compute for Apache Flink and SLS.

What's Coming in Apache Flink Agents 0.3

Version 0.3 aims to enhance capabilities with features like Agent Skills Integration, Mem0 based Long-Term Memory support and Durable Execution Reconciler.

The Delta Join in Apache Flink: Architectural Decoupling for Hyper-Scale Stream Processing

Discover how Delta Join in Apache Flink revolutionizes stream processing, reducing state and costs while boosting performance and stability.

Apache Flink FLIP-15: Smart Stream Iterations & Optimization

Learn Apache Flink FLIP-15 smart iterations with StreamScope and intelligent termination. Master backpressure optimization, deadlock prevention, and advanced loop processing for real-time analytics.

Realtime Compute for Apache Flink Unveils Incremental Processing & Streaming

From the 2025 Apsara Conference: Alibaba Cloud debuts major Realtime Compute for Apache Flink upgrades in computing, storage, and real-time AI integration.

Real-Time Lakehouse Solutions: Apache Flink & Apache Paimon Integration

Alibaba Cloud presents key optimizations in Flink-Paimon real-time lakehouse architecture, including the Variant data type for efficient semi-structur...

Alibaba Cloud, Ververica, Confluent, and LinkedIn Join Forces on Streaming Innovation for Agentic AI

Apache Flink Agents: A landmark collaboration to build a scalable, production-grade framework for event-driven streaming agents powered by Apache Flink.

Apache Flink FLIP-18: Accelerating Sorting with Code Generation

FLIP-18: Boost Flink's sorting efficiency with code generation, optimizing memory access and byte order handling.

Apache Flink FLIP-17: Side Inputs for Stream Processing API

FLIP-17 introduces side inputs to Apache Flink's DataStream API for more flexible and efficient stream processing with auxiliary data.

FLIP-16: Reliable Iterative Stream Processing in Apache Flink

FLIP-16 explores and addresses the challenges of reliable iterative stream processing in Flink, highlighting memory, complexity, and performance issue.

Building a Unified Lakehouse for Large-Scale Recommendation Systems with Apache Paimon at TikTok

TikTok transitioned to a unified Lakehouse architecture, powered by Apache Paimon, to optimize large-scale recommendation models (LRMs) that utilize user behavior sequences.