Google Cloud Dataflow is a fully managed service for executing Apache Beam pipelines within the Google Cloud Platform ecosystem. Dataflow provides a fully managed service for executing Apache Beam pipelines, offering features like autoscaling, dynamic work rebalancing, and a managed execution environment. [1]
Dataflow is suitable for large-scale, continuous data processing jobs, and is one of the major components of Google's big data architecture on the Google Cloud Platform. [2]
History
editGoogle Cloud Dataflow was announced in June, 2014[3] and released to the general public as an open beta in April, 2015.[4] In January, 2016 Google donated the underlying SDK, the implementation of a local runner, and a set of IOs (data connectors) to access Google Cloud Platform data services to the Apache Software Foundation.[5] The donated code formed the original basis for Apache Beam.
In August 2022, there was an incident where user timers were broken for certain Dataflow streaming pipelines in multiple regions, which was later resolved. [6] Throughout 2023 and 2024, there have been various other updates and incidents affecting Google Cloud Dataflow, as documented in the release notes and service health history.[7]
References
edit- ^ "Cloud Dataflow Runner". beam.apache.org. Retrieved 2024-07-03.
- ^ "GCP Dataflow and Apache Beam for ETL Data Pipeline". EPAM Anywhere. Retrieved 2024-07-03.
- ^ "Sneak peek: Google Cloud Dataflow, a Cloud-native data processing service". Google Cloud Platform Blog. Retrieved 2018-09-08.
- ^ "Google Opens Cloud Dataflow To All Developers, Launches European Zone For BigQuery". TechCrunch. Retrieved 2018-09-08.
- ^ "Google wants to donate its Dataflow technology to Apache". Venture Beat. Retrieved 2019-02-21.
- ^ "Google Cloud Service Health". status.cloud.google.com. Retrieved 2024-07-03.
- ^ "Dataflow enhancements in 2023". Google Cloud Blog. Retrieved 2024-07-03.
External links
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