uce commented on a change in pull request #397:
URL: https://github.com/apache/flink-web/pull/397#discussion_r537557800
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File path: _posts/2020-12-04-release-1.12.0.md
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@@ -0,0 +1,332 @@
+---
+layout: post
+title: "Apache Flink 1.12.0 Release Announcement"
+date: 2020-12-04T08:00:00.000Z
+categories: news
+authors:
+- morsapaes:
+ name: "Marta Paes"
+ twitter: "morsapaes"
+- aljoscha:
+ name: "Aljoscha Krettek"
+ twitter: "aljoscha"
+
+excerpt: The Apache Flink community is excited to announce the release of
Flink 1.12.0! Close to 300 contributors worked on over 1k tickets to bring
significant improvements to usability as well as new features to Flink users
across the whole API stack. We're particularly excited about adding efficient
batch execution to the DataStream API, Kubernetes HA as an alternative to
ZooKeeper, support for upsert mode in the Kafka SQL connector and the new
Python DataStream API! Read on for all major new features and improvements,
important changes to be aware of and what to expect moving forward!
+---
+
+The Apache Flink community is excited to announce the release of Flink 1.12.0!
Close to 300 contributors worked on over 1k tickets to bring significant
improvements to usability as well as new features that simplify (and unify)
Flink handling across the API stack.
+
+**Release Highlights**
+
+* The community has added support for **efficient batch execution** in the
DataStream API. This is the next major milestone towards achieving a truly
unified runtime for both batch and stream processing.
+
+* **Kubernetes-based High Availability (HA)** was implemented as an
alternative to ZooKeeper for highly available production setups.
+
+* The Kafka SQL connector has been extended to work in **upsert mode**,
supported by the ability to handle **connector metadata** in SQL DDL.
**Temporal table joins** can now also be fully expressed in SQL, no longer
depending on the Table API.
+
+* Support for the **DataStream API in PyFlink** expands its usage to more
complex scenarios that require fine-grained control over state and time, and
it’s now possible to deploy PyFlink jobs natively on **Kubernetes**.
+
+This blog post describes all major new features and improvements, important
changes to be aware of and what to expect moving forward.
+
+{% toc %}
+
+The binary distribution and source artifacts are now available on the updated
[Downloads page]({{ site.baseurl }}/downloads.html) of the Flink website, and
the most recent distribution of PyFlink is available on
[PyPI](https://pypi.org/project/apache-flink/). Please review the [release
notes]({{ site.DOCS_BASE_URL
}}flink-docs-release-1.12/release-notes/flink-1.12.html) carefully, and check
the complete [release
changelog](https://issues.apache.org/jira/secure/ReleaseNote.jspa?version=12348263&styleName=Html&projectId=12315522)
and [updated documentation]({{ site.DOCS_BASE_URL }}flink-docs-release-1.12/)
for more details.
+
+We encourage you to download the release and share your feedback with the
community through the [Flink mailing
lists](https://flink.apache.org/community.html#mailing-lists) or
[JIRA](https://issues.apache.org/jira/projects/FLINK/summary).
+
+## New Features and Improvements
+
+### Batch Execution Mode in the DataStream API
Review comment:
What do you think about adding a link to @aljoscha's FlinkForward talk
on this topic? I don't know if we have precedent for such links, but it could
help interested users to get more details and better understand where we're
headed with the unification.
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