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.
Additionally, it has a fake client variant, that does the same thing but with fake clients for use in unit tests.

# ADR-0002 - Avoid using Java serialization

## 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.

# For most projects, this workflow file will not need changing; you simply need
# to commit it to your repository.
#
# You may wish to alter this file to override the set of languages analyzed,
# or to provide custom queries or build logic.
name: "CodeQL"

on:
  push:
    branches:
    - master
    - "*.x"
  pull_request:
    branches:
    - master
    - "*.x"
  schedule:
    - cron: '0 0 * * 4'

jobs:
  analyze:

  # make sure we grab the actual windows path, instead of cygwin's path.
  if ! is_cygwin; then
    echo "$(pwd -P)/$TARGET_FILE"
  else
    echo $(cygwinpath "$(pwd -P)/$TARGET_FILE")
  fi
)
}

# TODO - Do we need to detect msys?

# Uses uname to detect if we're in the odd cygwin environment.
is_cygwin() {
  local os=$(uname -s)
  case "$os" in
    CYGWIN*) return 0 ;;
    *)  return 1 ;;
  esac
}

<abbr title="A utility/system to store computed/generated values, to reuse them instead of computing them again.">"cache"</abbr> and pass it to all the "dependants" that need it in that specific request, instead of calling the dependency multiple times for the same request.

In an advanced scenario where you know you need the dependency to be called at every step (possibly multiple times) in the same request instead of using the "cached" value, you can set the parameter `use_cache=False`...

### Short

It has sensible **defaults** for everything, with optional configurations everywhere. All the parameters can be fine-tuned to do what you need and to define the API you need.

But by default, it all **"just works"**.

### Validation

* Validation for most (or all?) Python **data types**, including:
    * JSON objects (`dict`).

`Cluster` is pushed, so this optimization is intentionally turned off in this specific case.

Finally, we determine which subset of the type we need to generate. XDS has two modes - "State of the World (SotW)" and "Delta". In SotW, we generally need to generate all resources of the type, even if only one changed. Note that we actually need to *generate* all of them, typically, as we do not store previously generated resources (mostly because they are generated per-client). This also means...

# Gradle Wrapper overwrites some files when it runs.
# To avoid modifying the Git client, we copy everything we need to another directory.
# That provides general hygiene, including avoiding release errors:
#
# Preparing to update Javadoc and JDiff for the release...

Directory for files of schema info

Files are auto-generated by DBFlute tasks.

        if (Objects.equal(key, keys[next])) {
          int oldValue = values[next];

          if (last == UNSET) {
            // we need to update the root link from table[]
            table[tableIndex] = getNext(entries[next]);
          } else {
            // we need to update the link from the chain
            entries[last] = swapNext(entries[last], getNext(entries[next]));
          }