## Date

2012-12-01

## Context

In Gradle, we often need to serialize in-memory objects for caching or transmitting them across process barriers, etc.
Java serialization is one way to implement this, however, despite its simplicity of implementation, it has several drawbacks:

 * (or {@link FluentFuture#transform(com.google.common.base.Function, Executor)
 * FluentFuture.transform}), but you will often find it easier to use a framework. Frameworks
 * automate the process, often adding features like monitoring, debugging, and cancellation.
 * Examples of frameworks include:
 *
 * <ul>
 *   <li><a href="https://dagger.dev/producers.html">Dagger Producers</a>

---
name: Feature request
about: Suggest an idea
title: ''
labels: enhancement
assignees: ''

---

Start by telling us what problem you’re trying to solve. Often a solution already exists!

   | * type: the type of tool. An often used value is 'jdk'. Toolchains-aware
   |   plugins should document which type you must use.
   |
   | * provides: A list of key/value-pairs.
   |   Based on the toolchain-configuration in the pom.xml Maven will search for
   |   matching <provides/> configuration. You can decide for yourself which key-value
   |   pairs to use. Often used keys are 'version', 'vendor' and 'arch'. By default

## Date

2012-12-01

## Context

In Gradle we often need to serialize in-memory objects for caching, or to transmit them across process barriers, etc.
Java serialization is one way to implement this, however, despite its simplicity of implementation, it has several drawbacks:

- **Performance:**
Java's built-in serialization mechanism is often slower compared to other serialization solutions.

**`kube.Client`** is a fairly light wrapper around Kubernetes clients, but offers quite a few benefits.
Istio consumes _many_ different types of clients (at the time of writing, 7), as well as informers for each of these.
Additionally, we often need to convert to various different client forms for different libraries we integrate with.

`kube.Client` just bundles these all in one place, so we have a single object to pass around anywhere we need Kubernetes access.

  abstract ImmutableCollection<E> delegateCollection();

  @Override
  public boolean contains(@CheckForNull Object target) {
    // The collection's contains() is at least as fast as ImmutableList's
    // and is often faster.
    return delegateCollection().contains(target);
  }

  @Override
  public int size() {
    return delegateCollection().size();
  }

  @Override
  public boolean isEmpty() {

  abstract ImmutableCollection<E> delegateCollection();

  @Override
  public boolean contains(@CheckForNull Object target) {
    // The collection's contains() is at least as fast as ImmutableList's
    // and is often faster.
    return delegateCollection().contains(target);
  }

  @Override
  public int size() {
    return delegateCollection().size();
  }

  @Override
  public boolean isEmpty() {

 * (or {@link FluentFuture#transform(com.google.common.base.Function, Executor)
 * FluentFuture.transform}), but you will often find it easier to use a framework. Frameworks
 * automate the process, often adding features like monitoring, debugging, and cancellation.
 * Examples of frameworks include:
 *
 * <ul>
 *   <li><a href="https://dagger.dev/producers.html">Dagger Producers</a>

   *   <li>Otherwise, return an instance of {@link ClusterException} that wraps the first exception
   *       in the {@code exceptions} collection.
   * </ul>
   *
   * <p>Though this method takes any {@link Collection}, it often makes most sense to pass a {@link
   * java.util.List} or some other collection that preserves the order in which the exceptions got
   * added.
   *
   * @throws NullPointerException if {@code exceptions} is null