## Structure

Each platform and module has its own source directory under [platforms/](../platforms).
In these source directories, you will find the Gradle projects that make up the platform or module.

The platforms and modules are defined using a DSL in [settings.gradle.kts](../settings.gradle.kts)

	}
	pool := &ReplicationPool{
		workers:         make([]chan ReplicationWorkerOperation, 0, workers),
		lrgworkers:      make([]chan ReplicationWorkerOperation, 0, LargeWorkerCount),
		mrfReplicaCh:    make(chan ReplicationWorkerOperation, 100000),
		mrfWorkerKillCh: make(chan struct{}, failedWorkers),
		resyncer:        newresyncer(),
		mrfSaveCh:       make(chan MRFReplicateEntry, 100000),

and you might not need to specify hard memory limits. But if you are **using a lot of memory** (for example with **machine learning** models), you should check how much memory you are consuming and adjust the **number of containers** that runs in **each machine** (and maybe add more machines to your cluster).

If you run **multiple processes per container** (for example with the official Docker image) you will have to make sure that the number of processes started doesn't **consume more...

   * turn, and does not create any threads of its own.
   *
   * <p>After execution begins on a thread from the {@code delegate} {@link Executor}, tasks are
   * polled and executed from a task queue until there are no more tasks. The thread will not be
   * released until there are no more tasks to run.
   *
   * <p>If a task is submitted while a thread is executing tasks from the task queue, the thread

	//
	// Also create metric group maps and set the cache.
	metricsCache := newMetricsCache()
	mgMap := make(map[collectorPath]*MetricsGroup)
	bucketMGMap := make(map[collectorPath]*MetricsGroup)
	for _, mg := range allMetricGroups {
		if !strings.HasPrefix(string(mg.CollectorPath), clusterBasePath) {
			mg.AddExtraLabels(
				serverName, globalLocalNodeName,
				// poolIndex, strconv.Itoa(globalLocalPoolIdx),
			)
		}

## Simple usage

If you look at it, *path operation functions* are declared to be used whenever a *path* and *operation* matches, and then **FastAPI** takes care of calling the function with the correct parameters, extracting the data from the request.

Actually, all (or most) of the web frameworks work in this same way.

You never call those functions directly. They are called by your framework (in this case, **FastAPI**).

	// HealthCheckTimeout determines timeout for each call.
	HealthCheckTimeout time.Duration

	// MaxErrResponseSize is the maximum expected response size.
	// Should only be modified before any calls are made.
	MaxErrResponseSize int64

	// Avoid metrics update if set to true
	NoMetrics bool

	// TraceOutput will print debug information on non-200 calls if set.
	TraceOutput io.Writer // Debug trace output

4. Validate your changes before committing.\
Run the `./gradlew sanityCheck` task again to make sure there are no more errors.

#### Filtering changes by severity

There is a somewhat non-obvious filter present on the page that allows you to control which type of messages are displayed.

   * proxy server can issue an auth challenge and then close the connection.
   *
   * @return the next plan to attempt, or null if no further attempt should be made either because
   *     we've successfully connected or because no further attempts should be made.
   */
  @Throws(IOException::class)
  internal fun connectTunnel(): ConnectResult {
    val nextTunnelRequest =
      createTunnel()

3.2 When the Program is Distributed as Source Code:

  a) it must be made available under this Agreement, or if the
  Program (i) is combined with other material in a separate file or
  files made available under a Secondary License, and (ii) the initial
  Contributor attached to the Source Code the notice described in
  Exhibit A of this Agreement, then the Program may be made available
  under the terms of such Secondary Licenses, and