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Kubernetes

Lithops with kubernetes as serverless compute backend.

Configuration

  1. Edit your Lithops config and add the following keys:
  lithops:
      backend : k8s
  1. Make sure you have a kubernetes cluster configuration file.

    • Option 1: You have the config file in ~/.kube/config

    • Option 2: You have the config file in another location, and you exported the KUBECONFIG variable:

      export KUBECONFIG=<path-to-kube-config-file>

    • Option 3: You have the config file in another location, and you set the kubecfg_path var in the Lithops config:

      k8s:
    kubecfg_path: <path-to-kube-config-file>

Configure a private container registry for your runtime

Configure Docker hub

To configure Lithops to access a private repository in your docker hub account, you need to extend the kubernetes config and add the following keys:

k8s:
    ....
    docker_server    : docker.io
    docker_user      : <Docker hub Username>
    docker_password  : <DOcker hub access TOEKN>

Configure IBM Container Registry

To configure Lithops to access to a private repository in your IBM Container Registry, you need to extend the kubernetes config and add the following keys:

k8s:
    ....
    docker_server    : us.icr.io
    docker_user      : iamapikey
    docker_password  : <IBM IAM API KEY>
    docker_namespace : <namespace>  # namespace name from https://cloud.ibm.com/registry/namespaces

Summary of configuration keys for kubernetes:

Group Key Default Mandatory Additional info
k8s kubecfg_path no Path to kubecfg file. Mandatory if config file not in ~/.kube/config or KUBECONFIG env var not present
k8s kubecfg_context no kubernetes context to use from your kubeconfig file. It will use the default active context if not provided
k8s namespace default no Kubernetes namespace to use for lithops execution
k8s docker_server docker.io no Container registry URL
k8s docker_user no Container registry user name
k8s docker_password no Container registry password/token. In case of Docker hub, login to your docker hub account and generate a new access token here
k8s rabbitmq_executor False no Alternative K8s backend accelerating parallel function execution (map) thanks to rabbitmq group calls and warm-state pods of higher granularity. For more information here.
k8s max_workers 100 no Max number of workers per FunctionExecutor()
k8s worker_processes 1 no Number of Lithops processes within a given worker. This can be used to parallelize function activations within a worker. It is recommendable to set this value to the same number of CPUs of the container.
k8s runtime no Docker image name.
k8s runtime_cpu 1 no CPU limit. Default 1vCPU
k8s runtime_memory 512 no Memory limit in MB. Default 512MB
k8s runtime_timeout 600 no Runtime timeout in seconds. Default 600 seconds

Test Lithops

Once you have your compute and storage backends configured, you can run a hello world function with:

lithops hello -b k8s -s ibm_cos

Viewing the execution logs

You can view the function executions logs in your local machine using the lithops client:

lithops logs poll