This is a cache of https://docs.openshift.com/container-platform/4.9/applications/deployments/managing-deployment-processes.html. It is a snapshot of the page at 2024-11-22T18:43:20.630+0000.
Managing <strong>deployment</strong> processes - <strong>deployment</strong>s | Building applications | OpenShift Container Platform 4.9
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Managing deployment processes

Managing deploymentConfig objects

deploymentConfig objects can be managed from the OpenShift Container Platform web console’s Workloads page or using the oc CLI. The following procedures show CLI usage unless otherwise stated.

Starting a deployment

You can start a rollout to begin the deployment process of your application.

Procedure

  1. To start a new deployment process from an existing deploymentConfig object, run the following command:

    $ oc rollout latest dc/<name>

    If a deployment process is already in progress, the command displays a message and a new replication controller will not be deployed.

Viewing a deployment

You can view a deployment to get basic information about all the available revisions of your application.

Procedure

  1. To show details about all recently created replication controllers for the provided deploymentConfig object, including any currently running deployment process, run the following command:

    $ oc rollout history dc/<name>

  2. To view details specific to a revision, add the --revision flag:

    $ oc rollout history dc/<name> --revision=1

  3. For more detailed information about a deploymentConfig object and its latest revision, use the oc describe command:

    $ oc describe dc <name>

Retrying a deployment

If the current revision of your deploymentConfig object failed to deploy, you can restart the deployment process.

Procedure

  1. To restart a failed deployment process:

    $ oc rollout retry dc/<name>

    If the latest revision of it was deployed successfully, the command displays a message and the deployment process is not retried.

    Retrying a deployment restarts the deployment process and does not create a new deployment revision. The restarted replication controller has the same configuration it had when it failed.

Rolling back a deployment

Rollbacks revert an application back to a previous revision and can be performed using the REST API, the CLI, or the web console.

Procedure

  1. To rollback to the last successful deployed revision of your configuration:

    $ oc rollout undo dc/<name>

    The deploymentConfig object’s template is reverted to match the deployment revision specified in the undo command, and a new replication controller is started. If no revision is specified with --to-revision, then the last successfully deployed revision is used.

  2. Image change triggers on the deploymentConfig object are disabled as part of the rollback to prevent accidentally starting a new deployment process soon after the rollback is complete.

    To re-enable the image change triggers:

    $ oc set triggers dc/<name> --auto

deployment configs also support automatically rolling back to the last successful revision of the configuration in case the latest deployment process fails. In that case, the latest template that failed to deploy stays intact by the system and it is up to users to fix their configurations.

Executing commands inside a container

You can add a command to a container, which modifies the container’s startup behavior by overruling the image’s ENTRYPOINT. This is different from a lifecycle hook, which instead can be run once per deployment at a specified time.

Procedure

  1. Add the command parameters to the spec field of the deploymentConfig object. You can also add an args field, which modifies the command (or the ENTRYPOINT if command does not exist).

    spec:
  containers:
  - name: <container_name>
    image: 'image'
    command:
      - '<command>'
    args:
      - '<argument_1>'
      - '<argument_2>'
      - '<argument_3>'

    For example, to execute the java command with the -jar and /opt/app-root/springboots2idemo.jar arguments:

    spec:
  containers:
  - name: example-spring-boot
    image: 'image'
    command:
      - java
    args:
      - '-jar'
      - /opt/app-root/springboots2idemo.jar

Viewing deployment logs

Procedure

  1. To stream the logs of the latest revision for a given deploymentConfig object:

    $ oc logs -f dc/<name>

    If the latest revision is running or failed, the command returns the logs of the process that is responsible for deploying your pods. If it is successful, it returns the logs from a pod of your application.

  2. You can also view logs from older failed deployment processes, if and only if these processes (old replication controllers and their deployer pods) exist and have not been pruned or deleted manually:

    $ oc logs --version=1 dc/<name>

deployment triggers

A deploymentConfig object can contain triggers, which drive the creation of new deployment processes in response to events inside the cluster.

If no triggers are defined on a deploymentConfig object, a config change trigger is added by default. If triggers are defined as an empty field, deployments must be started manually.
Config change deployment triggers

The config change trigger results in a new replication controller whenever configuration changes are detected in the pod template of the deploymentConfig object.

If a config change trigger is defined on a deploymentConfig object, the first replication controller is automatically created soon after the deploymentConfig object itself is created and it is not paused.
Config change deployment trigger
triggers:
  - type: "ConfigChange"
Image change deployment triggers

The image change trigger results in a new replication controller whenever the content of an image stream tag changes (when a new version of the image is pushed).

Image change deployment trigger
triggers:
  - type: "ImageChange"
    imageChangeParams:
      automatic: true (1)
      from:
        kind: "ImageStreamTag"
        name: "origin-ruby-sample:latest"
        namespace: "myproject"
      containerNames:
        - "helloworld"
1 If the imageChangeParams.automatic field is set to false, the trigger is disabled.

With the above example, when the latest tag value of the origin-ruby-sample image stream changes and the new image value differs from the current image specified in the deploymentConfig object’s helloworld container, a new replication controller is created using the new image for the helloworld container.

If an image change trigger is defined on a deploymentConfig object (with a config change trigger and automatic=false, or with automatic=true) and the image stream tag pointed by the image change trigger does not exist yet, the initial deployment process will automatically start as soon as an image is imported or pushed by a build to the image stream tag.

Setting deployment triggers

Procedure

  1. You can set deployment triggers for a deploymentConfig object using the oc set triggers command. For example, to set a image change trigger, use the following command:

    $ oc set triggers dc/<dc_name> \
    --from-image=<project>/<image>:<tag> -c <container_name>

Setting deployment resources

A deployment is completed by a pod that consumes resources (memory, CPU, and ephemeral storage) on a node. By default, pods consume unbounded node resources. However, if a project specifies default container limits, then pods consume resources up to those limits.

The minimum memory limit for a deployment is 12 MB. If a container fails to start due to a Cannot allocate memory pod event, the memory limit is too low. Either increase or remove the memory limit. Removing the limit allows pods to consume unbounded node resources.

You can also limit resource use by specifying resource limits as part of the deployment strategy. deployment resources can be used with the recreate, rolling, or custom deployment strategies.

Procedure

  1. In the following example, each of resources, cpu, memory, and ephemeral-storage is optional:

    type: "Recreate"
resources:
  limits:
    cpu: "100m" (1)
    memory: "256Mi" (2)
    ephemeral-storage: "1Gi" (3)
    1 cpu is in CPU units: 100m represents 0.1 CPU units (100 * 1e-3).
    2 memory is in bytes: 256Mi represents 268435456 bytes (256 * 2 ^ 20).
    3 ephemeral-storage is in bytes: 1Gi represents 1073741824 bytes (2 ^ 30).

    However, if a quota has been defined for your project, one of the following two items is required:

    • A resources section set with an explicit requests:

        type: "Recreate"
  resources:
    requests: (1)
      cpu: "100m"
      memory: "256Mi"
      ephemeral-storage: "1Gi"
      1 The requests object contains the list of resources that correspond to the list of resources in the quota.

    • A limit range defined in your project, where the defaults from the LimitRange object apply to pods created during the deployment process.

    To set deployment resources, choose one of the above options. Otherwise, deploy pod creation fails, citing a failure to satisfy quota.

Additional resources

Scaling manually

In addition to rollbacks, you can exercise fine-grained control over the number of replicas by manually scaling them.

Pods can also be auto-scaled using the oc autoscale command.
Procedure

  1. To manually scale a deploymentConfig object, use the oc scale command. For example, the following command sets the replicas in the frontend deploymentConfig object to 3.

    $ oc scale dc frontend --replicas=3

    The number of replicas eventually propagates to the desired and current state of the deployment configured by the deploymentConfig object frontend.

Accessing private repositories from deploymentConfig objects

You can add a secret to your deploymentConfig object so that it can access images from a private repository. This procedure shows the OpenShift Container Platform web console method.

Procedure

  1. Create a new project.

  2. From the Workloads page, create a secret that contains credentials for accessing a private image repository.

  3. Create a deploymentConfig object.

  4. On the deploymentConfig object editor page, set the Pull Secret and save your changes.

Assigning pods to specific nodes

You can use node selectors in conjunction with labeled nodes to control pod placement.

Cluster administrators can set the default node selector for a project in order to restrict pod placement to specific nodes. As a developer, you can set a node selector on a Pod configuration to restrict nodes even further.

Procedure

  1. To add a node selector when creating a pod, edit the Pod configuration, and add the nodeSelector value. This can be added to a single Pod configuration, or in a Pod template:

    apiVersion: v1
kind: Pod
spec:
  nodeSelector:
    disktype: ssd
...

    Pods created when the node selector is in place are assigned to nodes with the specified labels. The labels specified here are used in conjunction with the labels added by a cluster administrator.

    For example, if a project has the type=user-node and region=east labels added to a project by the cluster administrator, and you add the above disktype: ssd label to a pod, the pod is only ever scheduled on nodes that have all three labels.

    Labels can only be set to one value, so setting a node selector of region=west in a Pod configuration that has region=east as the administrator-set default, results in a pod that will never be scheduled.

Running a pod with a different service account

You can run a pod with a service account other than the default.

Procedure

  1. Edit the deploymentConfig object:

    $ oc edit dc/<deployment_config>

  2. Add the serviceAccount and serviceAccountName parameters to the spec field, and specify the service account you want to use:

    spec:
  securityContext: {}
  serviceAccount: <service_account>
  serviceAccountName: <service_account>