startedCrawlerNum++;
                activeCrawlerNum++;
                ThreadUtil.sleep(crawlingExecutionInterval);
                continue;
            }

            // check status
            for (int i = 0; i < startedCrawlerNum; i++) {
                if (!dataCrawlingThreadList.get(i).isRunning() && Constants.RUNNING.equals(dataCrawlingThreadStatusList.get(i))) {

* The process can be **terminated** (or "killed") by you, or by the operating system. At that point, it stops running/being executed, and it can **no longer do things**.
* Each application that you have running on your computer has some process behind it, each running program, each window, etc. And there are normally many processes running **at the same time** while a computer is on.

check: test
test: verifiers build ## builds minio, runs linters, tests
	@echo "Running unit tests"
	@MINIO_API_REQUESTS_MAX=10000 CGO_ENABLED=0 go test -v -tags kqueue,dev ./...

test-root-disable: install-race
	@echo "Running minio root lockdown tests"
	@env bash $(PWD)/buildscripts/disable-root.sh

test-ilm: install-race
	@echo "Running ILM tests"
	@env bash $(PWD)/docs/bucket/replication/setup_ilm_expiry_replication.sh

And the **container** itself (in contrast to the **container image**) is the actual running instance of the image, comparable to a **process**. In fact, a container is running only when it has a **process running** (and normally it's only a single process). The container stops when there's no process running in it.

## Container Images

// Package-wide variables from generator "generated".
option go_package = "k8s.io/api/node/v1beta1";

// Overhead structure represents the resource overhead associated with running a pod.
message Overhead {
  // podFixed represents the fixed resource overhead associated with running a pod.
  // +optional
  map<string, k8s.io.apimachinery.pkg.api.resource.Quantity> podFixed = 1;
}

// Package-wide variables from generator "generated".
option go_package = "k8s.io/api/node/v1";

// Overhead structure represents the resource overhead associated with running a pod.
message Overhead {
  // podFixed represents the fixed resource overhead associated with running a pod.
  // +optional
  map<string, k8s.io.apimachinery.pkg.api.resource.Quantity> podFixed = 1;
}

    + row.withPanels([
      panels.timeSeries.simple('Pilot Versions', queries.istioBuild, 'Version number of each running instance'),
    ]),
  ], panelHeight=5)
  + grid.makeGrid([
    row.new('Resource Usage')
    + row.withPanels([
      panels.timeSeries.bytes('Memory Usage', queries.goMemoryUsage, 'Memory usage of each running instance'),

research](https://scholar.google.com/scholar?q=gpu+side+channel) shows that it
might be possible to use side channel attacks on the GPU to leak data from other
running models or processes in the same system. GPUs can also have
implementation bugs that might allow attackers to leave malicious code running
and leak or tamper with applications from other users. Please report
vulnerabilities to the vendor of the affected hardware accelerator.

Let's check back those deployment concepts from before:

* Security - HTTPS
* Running on startup
* Restarts
* **Replication (the number of processes running)**
* Memory
* Previous steps before starting

Up to this point, with all the tutorials in the docs, you have probably been running a **server program**, for example, using the `fastapi` command, that runs Uvicorn, running a **single process**.

  // The total number of nodes that should be running the daemon
  // pod (including nodes correctly running the daemon pod).
  // More info: https://kubernetes.io/docs/concepts/workloads/controllers/daemonset/
  optional int32 desiredNumberScheduled = 3;

  // numberReady is the number of nodes that should be running the daemon pod and have one
  // or more of the daemon pod running with a Ready Condition.
  optional int32 numberReady = 4;