## 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.

 * (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>

   | * 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

 * (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>

 * (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>

**`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() {

include out/.env
# An export free of arguments in a Makefile places all variables in the Makefile into the
# environment. This behavior may be surprising to many that use shell often, which simply
# displays the existing environment
export

export GOBIN ?= $(GOPATH)/bin
include Makefile.core.mk

// so there is no risk of polluting the entire cache with data accessed once.
// Another goal of DirectIO is to minimize the mutation of data by the kernel
// before issuing IO to underlying devices. ZFS users often enable features like
// compression and checksumming which currently necessitates mutating data in
// the kernel.
//
// DirectIO semantics for a filesystem like ZFS would be quite different than