Build scans give you a visual timeline of task execution. In the following
example build, you can see long-running tasks at the beginning and end of the build:

image::performance/parallel-task-slow.png[title="Bottleneck in parallel execution"]

Tweaking the build configuration to run the two slow tasks early on and in parallel
reduces the overall build time from 8 seconds to 5 seconds:

- Fixes the bug in informer-gen that it produces incorrect code if a type has nonNamespaced tag set. ([#80458](https://github.com/kubernetes/kubernetes/pull/80458), [@tatsuhiro-t](https://github.com/tatsuhiro-t))
- Resolves bottleneck in internal API server communication that can cause increased goroutines and degrade API Server performance ([#80465](https://github.com/kubernetes/kubernetes/pull/80465), [@answer1991](https://github.com/answer1991))

== What is a build scan?

https://scans.gradle.com/[Build scans] are a persistent, shareable record of what happened when running a build.
Build scans provide insights into your build that you can use to identify and fix performance bottlenecks.

In Gradle 4.3 and above, you can create a build scan using the `--scan` command line option:

[listing.terminal]
----
$ gradle build --scan
----

For older Gradle versions, the

|Nofootnote:2[]
|===

If you suspect issues with your plugin code, try creating a link:https://scans.gradle.com/[Build Scan] to identify bottlenecks.

* Resolves bottleneck in internal API server communication that can cause increased goroutines and degrade API Server performance ([#80465](https://github.com/kubernetes/kubernetes/pull/80465), [@answer1991](https://github.com/answer1991))

* Resolves bottleneck in internal API server communication that can cause increased goroutines and degrade API Server performance ([#80465](https://github.com/kubernetes/kubernetes/pull/80465), [@answer1991](https://github.com/answer1991))

* Update to go 1.12.10 ([#83139](https://github.com/kubernetes/kubernetes/pull/83139), [@cblecker](https://github.com/cblecker))
* Resolves bottleneck in internal API server communication that can cause increased goroutines and degrade API Server performance ([#80465](https://github.com/kubernetes/kubernetes/pull/80465), [@answer1991](https://github.com/answer1991))

* Fixes a panic in kube-controller-manager cleaning up bootstrap tokens ([#82887](https://github.com/kubernetes/kubernetes/pull/82887), [@tedyu](https://github.com/tedyu))
* Resolves bottleneck in internal API server communication that can cause increased goroutines and degrade API Server performance ([#80465](https://github.com/kubernetes/kubernetes/pull/80465), [@answer1991](https://github.com/answer1991))

Modifier function, each modifier can have a function of this type assigned\n * to its `fn` property.<br />\n * These functions will be called on each update, this means that you must\n * make sure they are performant enough to avoid performance bottlenecks.\n *\n * @function ModifierFn\n * @argument {dataObject} data - The data object generated by `update` method\n * @argument {Object} options - Modifiers configuration and options\n * @returns {dataObject} The data object, properly modified\n */\n\n/**\n...

    both NumPy and TensorFlow headers.

# Release 2.3.0

## Major Features and Improvements

*   `tf.data` adds two new mechanisms to solve input pipeline bottlenecks and
    save resources:

    *   [snapshot](https://www.tensorflow.org/api_docs/python/tf/data/experimental/snapshot)
    *   [tf.data service](https://www.tensorflow.org/api_docs/python/tf/data/experimental/service).