Add known python issue (#30701)

* Add known python issue

* Add blogs

CHANGES.md

@@ -52,6 +52,40 @@
 
 * ([#X](https://github.com/apache/beam/issues/X)).
 -->
+# [2.56.0] - Unreleased
+
+## Highlights
+
+* New highly anticipated feature X added to Python SDK ([#X](https://github.com/apache/beam/issues/X)).
+* New highly anticipated feature Y added to Java SDK ([#Y](https://github.com/apache/beam/issues/Y)).
+
+## I/Os
+
+* Support for X source added (Java/Python) ([#X](https://github.com/apache/beam/issues/X)).
+
+## New Features / Improvements
+
+* X feature added (Java/Python) ([#X](https://github.com/apache/beam/issues/X)).
+
+## Breaking Changes
+
+* X behavior was changed ([#X](https://github.com/apache/beam/issues/X)).
+
+## Deprecations
+
+* X behavior is deprecated and will be removed in X versions ([#X](https://github.com/apache/beam/issues/X)).
+
+## Bugfixes
+
+* Fixed locking issue when shutting down inactive bundle processors. Symptoms of this issue include slowness or stuckness in long-running jobs (Python) ([#30679](https://github.com/apache/beam/pull/30679)).
+
+## Security Fixes
+* Fixed (CVE-YYYY-NNNN)[https://www.cve.org/CVERecord?id=CVE-YYYY-NNNN] (Java/Python/Go) ([#X](https://github.com/apache/beam/issues/X)).
+
+## Known Issues
+
+* ([#X](https://github.com/apache/beam/issues/X)).
+
 # [2.55.0] - Unreleased
 
 ## Highlights
@@ -106,7 +140,7 @@
 
 ## Known Issues
 
-* ([#X](https://github.com/apache/beam/issues/X)).
+* In Python pipelines, when shutting down inactive bundle processors, shutdown logic can overaggressively hold the lock, blocking acceptance of new work. Symptoms of this issue include slowness or stuckness in long-running jobs. Fixed in 2.56.0 ([#30679](https://github.com/apache/beam/pull/30679)).
 
 # [2.54.0] - 2024-02-14
 
@@ -147,6 +181,7 @@
 
 * Some Python pipelines that run with 2.52.0-2.54.0 SDKs and use large materialized side inputs might be affected by a performance regression. To restore the prior behavior on these SDK versions, supply the `--max_cache_memory_usage_mb=0` pipeline option. ([#30360](https://github.com/apache/beam/issues/30360)).
 * Python pipelines that run with 2.53.0-2.54.0 SDKs and perform file operations on GCS might be affected by excess HTTP requests. This could lead to a performance regression or a permission issue. ([#28398](https://github.com/apache/beam/issues/28398))
+* In Python pipelines, when shutting down inactive bundle processors, shutdown logic can overaggressively hold the lock, blocking acceptance of new work. Symptoms of this issue include slowness or stuckness in long-running jobs. Fixed in 2.56.0 ([#30679](https://github.com/apache/beam/pull/30679)).
 
 # [2.53.0] - 2024-01-04
 
@@ -190,6 +225,7 @@
 * Potential race condition causing NPE in DataflowExecutionStateSampler in Dataflow Java Streaming pipelines ([#29987](https://github.com/apache/beam/issues/29987)).
 * Some Python pipelines that run with 2.52.0-2.54.0 SDKs and use large materialized side inputs might be affected by a performance regression. To restore the prior behavior on these SDK versions, supply the `--max_cache_memory_usage_mb=0` pipeline option. ([#30360](https://github.com/apache/beam/issues/30360)).
 * Python pipelines that run with 2.53.0-2.54.0 SDKs and perform file operations on GCS might be affected by excess HTTP requests. This could lead to a performance regression or a permission issue. ([#28398](https://github.com/apache/beam/issues/28398))
+* In Python pipelines, when shutting down inactive bundle processors, shutdown logic can overaggressively hold the lock, blocking acceptance of new work. Symptoms of this issue include slowness or stuckness in long-running jobs. Fixed in 2.56.0 ([#30679](https://github.com/apache/beam/pull/30679)).
 
 # [2.52.0] - 2023-11-17
 

website/www/site/content/en/blog/beam-2.53.0.md

@@ -62,6 +62,15 @@ For more information on changes in 2.53.0, check out the [detailed release notes
 
 * Upgraded to go 1.21.5 to build, fixing [CVE-2023-45285](https://security-tracker.debian.org/tracker/CVE-2023-45285) and [CVE-2023-39326](https://security-tracker.debian.org/tracker/CVE-2023-39326)
 
+## Known Issues
+
+* Potential race condition causing NPE in DataflowExecutionStateSampler in Dataflow Java Streaming pipelines ([#29987](https://github.com/apache/beam/issues/29987)).
+* Some Python pipelines that run with 2.52.0-2.54.0 SDKs and use large materialized side inputs might be affected by a performance regression. To restore the prior behavior on these SDK versions, supply the `--max_cache_memory_usage_mb=0` pipeline option. ([#30360](https://github.com/apache/beam/issues/30360)).
+* Python pipelines that run with 2.53.0-2.54.0 SDKs and perform file operations on GCS might be affected by excess HTTP requests. This could lead to a performance regression or a permission issue. ([#28398](https://github.com/apache/beam/issues/28398))
+* In Python pipelines, when shutting down inactive bundle processors, shutdown logic can overaggressively hold the lock, blocking acceptance of new work. Symptoms of this issue include slowness or stuckness in long-running jobs. Fixed in 2.56.0 ([#30679](https://github.com/apache/beam/pull/30679)).
+
+For the most up to date list of known issues, see https://github.com/apache/beam/blob/master/CHANGES.md
+
 ## List of Contributors
 
 According to git shortlog, the following people contributed to the 2.53.0 release. Thank you to all contributors!

website/www/site/content/en/blog/beam-2.54.0.md

@@ -61,7 +61,11 @@ For more information on changes in 2.54.0, check out the [detailed release notes
 
 ## Known Issues
 
-* N/A
+* Some Python pipelines that run with 2.52.0-2.54.0 SDKs and use large materialized side inputs might be affected by a performance regression. To restore the prior behavior on these SDK versions, supply the `--max_cache_memory_usage_mb=0` pipeline option. ([#30360](https://github.com/apache/beam/issues/30360)).
+* Python pipelines that run with 2.53.0-2.54.0 SDKs and perform file operations on GCS might be affected by excess HTTP requests. This could lead to a performance regression or a permission issue. ([#28398](https://github.com/apache/beam/issues/28398))
+* In Python pipelines, when shutting down inactive bundle processors, shutdown logic can overaggressively hold the lock, blocking acceptance of new work. Symptoms of this issue include slowness or stuckness in long-running jobs. Fixed in 2.56.0 ([#30679](https://github.com/apache/beam/pull/30679)).
+
+For the most up to date list of known issues, see https://github.com/apache/beam/blob/master/CHANGES.md
 
 ## List of Contributors