Google Cloud Run#

Lithops with GCP Cloud Run 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 Accounts –> Service Account User

  • Cloud Run –> Cloud Run Admin

  • Cloud Storage –>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 the 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.

  3. Enable the Cloud Run API : Navigate to APIs & services tab on the menu. Click ENABLE APIS AND SERVICES. Look for “Cloud Run API” at the search bar. Click Enable.

Configuration#

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

    lithops:
        backend: gcp_cloudrun

    gcp:
        region : <REGION_NAME>
        credentials_path : <FULL_PATH_TO_CREDENTIALS_JSON>

Summary of configuration keys for Google Cloud#

Google Cloud Platform:#

Group

Key

Default

Mandatory

Additional info

gcp

region

yes

Region name of the GCP services (e.g. us-east1)

gcp

credentials_path

yes

Absolute path of your JSON key file downloaded in step 7 (e.g. /home/myuser/lithops-invoker1234567890.json). Alternatively you can set GOOGLE_APPLICATION_CREDENTIALS environment variable. If not provided it will try to load the default credentials from the environment

Google Cloud Run#

Group

Key

Default

Mandatory

Additional info

gcp_cloudrun

region

no

Region name (e.g. us-east1). Lithops will use the region set under the gcp section if it is not set here

gcp_cloudrun

min_workers

0

no

Minimum number of workers of a given runtime to keep in warm status

gcp_cloudrun

max_workers

1000

no

Maximum number of workers to scale a given runtime

gcp_cloudrun

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.

gcp_cloudrun

runtime

no

Container image name

gcp_cloudrun

runtime_cpu

0.25

no

CPU limit. Default 0.25vCPU

gcp_cloudrun

runtime_memory

256

no

Memory limit in MB. Default 256Mi

gcp_cloudrun

runtime_timeout

300

no

Runtime timeout in seconds. Default 5 minutes

gcp_cloudrun

trigger

https

no

Currently it supports ‘https’ trigger

gcp_cloudrun

invoke_pool_threads

100

no

Number of concurrent threads used for invocation

gcp_cloudrun

runtime_include_function

False

no

If set to true, Lithops will automatically build a new runtime, including the function’s code, instead of transferring it through the storage backend at invocation time. This is useful when the function’s code size is large (in the order of 10s of MB) and the code does not change frequently

Test Lithops#

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

lithops hello -b gcp_cloudrun -s gcp_storage

Viewing the execution logs#

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

lithops logs poll