Apache Flink® - Stateful Computations over Data Streams
All streaming use cases
- Event-driven Applications
- Stream & Batch Analytics
- Data Pipelines & ETL
Guaranteed correctness
- Exactly-once state consistency
- Event-time processing
- Sophisticated late data handling
Layered APIs
- SQL on Stream & Batch Data
- DataStream API & DataSet API
- ProcessFunction (Time & State)
Operational Focus
- Flexible deployment
- High-availability setup
- Savepoints
Scales to any use case
- Scale-out architecture
- Support for very large state
- Incremental checkpointing
Excellent Performance
- Low latency
- High throughput
- In-Memory computing
- Flink and Prometheus: Cloud-native monitoring of streaming applications
- This blog post describes how developers can leverage Apache Flink's built-in metrics system together with Prometheus to observe and monitor streaming applications in an effective way.
- What to expect from Flink Forward San Francisco 2019
- The third annual Flink Forward conference in San Francisco is just a few weeks away. Let's see what Flink Forward SF 2019 has in store for the Apache Flink and stream processing communities. This post covers some of its highlights!
- Monitoring Apache Flink Applications 101
- The monitoring of business-critical applications is a crucial aspect of a production deployment. It ensures that any degradation or downtime is immediately identified and can be resolved as quickly as possible. In this post, we discuss the most important metrics that indicate healthy Flink applications.
- Apache Flink 1.6.4 Released
The Apache Flink community released the fourth bugfix version of the Apache Flink 1.6 series.
- Apache Flink 1.7.2 Released
The Apache Flink community released the second bugfix version of the Apache Flink 1.7 series.