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gcp_functions.md

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Google Cloud Functions

Lithops with GCP Functions as serverless compute backend.

Installation

  1. Install Google Cloud Platform backend dependencies:
$ python3 -m install lithops[gcp]

  1. Login to Google Cloud Console (or sign up if you don't have an account).

  2. Create a new project. Name it lithops or similar.

  3. Navigate to IAM & Admin > Service Accounts.

  4. Click on Create Service Account. Name the service account lithops-executor or similar. Then click on Create.

  5. Add the following roles to the service account:

  • Service Account User
  • Cloud Functions Admin
  • Pub/Sub Admin
  • Storage Admin

  1. Click on Continue. Then, click on Create key. Select JSON and then Create. Download the JSON file to a secure location in you computer. Click Done.

  2. Enable Google Cloud Build API: Navigate to APIs & services tab on the menu. Click ENABLE APIS AND SERVICES. Look for "Cloud Build API" at the search bar. Click Enable.

Configuration

  1. Edit your lithops config and add the following keys:
    lithops:
        backend: gcp_functions

    gcp:
        project_name : <PROJECT_NAME>
        service_account : <SERVICE_ACCOUNT_EMAIL>
        credentials_path : <FULL_PATH_TO_CREDENTIALS_JSON>
        region : <REGION_NAME>

Summary of configuration keys for Google:

Google Cloud Platform:

Group Key Default Mandatory Additional info
gcp project_name yes Project name introduced in step 3 (e.g. lithops)
gcp service_account yes Service account email of the service account created on step 5 (e.g. [email protected])
gcp credentials_path yes Absolute path of your JSON key file downloaded in step 7 (e.g. /home/myuser/lithops-invoker1234567890.json)
gcp region yes Region of the bucket created at step 8. Functions and pub/sub queue will be created in the same region (e.g. us-east1)

Google Cloud Functions

Group Key Default Mandatory Additional info
gcp_functions max_workers 1000 no Max number of workers per FunctionExecutor()
gcp_functions worker_processes 1 no Number of Lithops processes within a given worker. This can be used to parallelize function activations within a worker
gcp_functions runtime no Runtime name already deployed in the service
gcp_functions runtime_memory 256 no Memory limit in MB. Default 256MB
gcp_functions runtime_timeout 300 no Runtime timeout in seconds. Default 5 minutes
gcp_functions invoke_pool_threads 1000 no Number of concurrent threads used for invocation