@Marvin how can I make sure k8s is deleting the completed pods on my cluster?

To ensure that completed Kubernetes pods are automatically deleted, you can use the

ttlSecondsAfterFinished

field in your pod or job spec. This field specifies the time to live (TTL) for a finished pod or job, after which it will be eligible for garbage collection. Here is a brief example of how you might configure this in a job spec:

yaml
apiVersion: batch/v1
kind: Job
metadata:
  name: example-job
spec:
  template:
    spec:
      containers:
      - name: example
        image: busybox
        command: ["echo", "Hello World"]
      restartPolicy: Never
  ttlSecondsAfterFinished: 100  # Deletes the job 100 seconds after it completes

In this example, the job will be deleted 100 seconds after it completes. Ensure that your Kubernetes version supports this feature, as it might not be available in older versions. For more details, you can refer to the Kubernetes documentation on TTL Controller for Finished Resources.

@Marvin Ok but is this a setting on the worker or how can I say this to the engine?

The

ttlSecondsAfterFinished

setting is not configured on the worker or engine; rather, it is specified directly in the Kubernetes manifest for the job or pod. This field is part of the job or pod specification and is managed by the Kubernetes control plane itself, specifically by the TTL Controller, which is responsible for cleaning up finished resources after the specified TTL period. Here's a quick breakdown of how it works: 1. Job or Pod Specification: You include the

ttlSecondsAfterFinished

field in the job or pod spec when you define it. This tells Kubernetes how long to wait after the job or pod has completed before it should be deleted. 2. Kubernetes Control Plane: The TTL Controller, which is part of the Kubernetes control plane, monitors completed jobs or pods. Once the specified TTL has elapsed, the controller will delete the resource. 3. No Worker Configuration Needed: You don't need to configure this setting on individual workers or nodes; it's managed at the cluster level by Kubernetes. By specifying this field in your job or pod spec, you communicate directly with the Kubernetes engine on how to handle completed resources.

@Marvin can I change the way of how k8s give names to the pods created?

In Kubernetes, the naming of pods is primarily controlled by the Kubernetes API server and is based on the resource name you provide. However, there are a few ways you can influence or change how pod names are generated: 1. Direct Naming: When you create a pod directly, you specify the name in the metadata section of the pod manifest:

yaml
   apiVersion: v1
   kind: Pod
   metadata:
     name: my-custom-pod-name
   spec:
     containers:
     - name: my-container
       image: my-image

2. Controller-Generated Names: When using controllers like Deployments, ReplicaSets, or Jobs, you typically specify a name for the controller, and Kubernetes generates pod names based on this name. For example, if you name a Deployment

my-deployment

, the pods might be named

my-deployment-<random-suffix>

. 3. Customizing Names with Labels and Annotations: While you can't directly control the suffix added to pod names by controllers, you can use labels and annotations to add additional metadata that can help identify pods. This doesn't change the pod name but can make it easier to organize and manage pods. 4. StatefulSets: If you need more control over pod naming, consider using a StatefulSet. StatefulSets provide stable, unique pod names that follow a predictable pattern:

<statefulset-name>-<ordinal>

. This is useful for applications that require stable network identities. In summary, while you can't fully customize the random suffix added to pod names by controllers, you can influence the base name and use other Kubernetes features like StatefulSets for more predictable naming patterns.

@Marvin prefect worker give random names for the created jobs. Is it possible to control this?

In Prefect, the naming of jobs created by workers can be influenced by configuring the job template associated with a work pool. Each work pool has a base job template that determines the behavior of the worker executing flow runs, and this includes aspects like naming. Here's how you can potentially control job names: 1. Base Job Template: Each work pool has a base job template that acts as a contract defining the configuration passed to the worker for each flow run. This includes a

job_configuration

section and a

variables

section. 2. Job Configuration: The

job_configuration

section can include placeholders that reference values provided in the

variables

section or use hard-coded values. You can use this to influence the naming convention by setting up a pattern or including specific identifiers. 3. Customization: The

variables

section allows deployment creators to customize worker behavior per deployment or flow run. This can include setting custom fields that may be used in the job name. To implement a custom naming convention, you would need to define a job template with specific placeholders or hard-coded values that dictate how the job names are structured. For more details on configuring work pools and job templates, you can refer to the Prefect documentation on Work Pools.