Claude Code SkillDevelopment

Cloud Run Basics

Manages Cloud Run services, jobs, and worker pools. Use when you need to deploy applications responding to HTTP requests (services), run event-triggered or scheduled tasks (jobs), or handle always-on pull-based background processing (worker pools).

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What's inside this skill

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Cloud Run Basics

Cloud Run is a fully managed application platform for running your code,

function, or container on top of Google's highly scalable infrastructure. It

abstracts away infrastructure management, providing three primary resource

types:

  • Services: Responds to HTTP requests sent to a unique and stable
endpoint, using stateless instances that autoscale based on a variety of key

metrics, also responds to events and functions.

  • Jobs: Executes parallelizable tasks that are executed manually, or on a
schedule, and run to completion.

  • Worker pools: Handles always-on background workloads such as pull-based
workloads, for example, Kafka consumers, Pub/Sub pull queues, or RabbitMQ

consumers.

Prerequisites

  • Enable the Cloud Run Admin API and Cloud Build APIs:

gcloud services enable run.googleapis.com cloudbuild.googleapis.com --quiet

  • If you are under a domain restriction organization policy restricting
unauthenticated invocations for your project, you will need to access your

deployed service as described under Testing private

services.

Required roles

You need the following roles to deploy your Cloud Run resource:

  • Cloud Run Admin (roles/run.admin) on the project
  • Cloud Run Source Developer (roles/run.sourceDeveloper) on the project
  • Service Account User (roles/iam.serviceAccountUser) on the service
identity

  • Logs Viewer (roles/logging.viewer) on the project

Cloud Build automatically uses the Compute Engine default service account as the

default Cloud Build service account to build your source code and Cloud Run

resource, unless you override this behavior.

For Cloud Build to build your sources, grant the Cloud Build service account the

Cloud Run Builder (roles/run.builder) role on your project:

gcloud projects add-iam-policy-binding PROJECT_ID \
    --member=serviceAccount:SERVICE_ACCOUNT_EMAIL_ADDRESS \
    --role=roles/run.builder \
    --quiet

Replace PROJECT_ID with your Google Cloud project ID and

SERVICE_ACCOUNT_EMAIL_ADDRESS with the email address of the Cloud Build

service account.

Deploy a Cloud Run service

You can deploy your service to Cloud Run by using a container image or deploy

directly from source code using a single Google Cloud CLI command.

CRITICAL RULE: Any deployed code MUST listen on 0.0.0.0 (not 127.0.0.1)
and use the injected $PORT environment variable (defaults to 8080), or it will
crash on boot.

Deploy a container image to Cloud Run

Cloud Run imports your container image during deployment. Cloud Run keeps this

copy of the container image as long as it is used by a serving revision.

Container images are not pulled from their container repository when a new Cloud

Run instance is started.

Supported container images

You can directly use container images stored in the Artifact

Registry, or

Docker Hub. Google recommends the use of Artifact

Registry since Docker Hub images are

cached

for up to one hour.

You can use container images from other public or private registries (like JFrog

Artifactory, Nexus, or GitHub Container Registry), by setting up an Artifact

Registry remote

repository.

You should only consider Docker Hub for deploying

popular container images such as Docker Official

Images or Docker

Sponsored OSS images. For

higher availability, Google recommends deploying these Docker Hub images using

an Artifact Registry remote

repository.

To deploy a container image, run the following command:

gcloud run deploy SERVICE_NAME \
        --image IMAGE_URL \
        --region us-central1 \
        --allow-unauthenticated \
        --quiet

Replace the following:

  • SERVICE_NAME: the name of the service you want to deploy to. Service names
must be 49 characters or less and must be unique per region and project. If

the service does not exist yet, this command creates the service during the

deployment. You can omit this parameter entirely, but you will be prompted

for the service name if you omit it.

  • IMAGE_URL: a reference to the container image, for example,
us-docker.pkg.dev/cloudrun/container/hello:latest. If you use Artifact

Registry, the repository REPO_NAME must already be created. The URL follows

the format of LOCATION-docker.pkg.dev/PROJECT_ID/REPO_NAME/PATH:TAG. Note

that if you don't supply the --image flag, the deploy command will attempt

to deploy from source code.

Deploy from source code

There are two different ways to deploy your service from source:

  • Deploy from source with build (default): This option uses Google Cloud's
buildpacks and Cloud Build to automatically build container images from your

source code without having to install Docker on your machine or set up

buildpacks or Cloud Build. By default, Cloud Run uses the default machine

type provided by Cloud Build.

* To deploy from source with automatic base image updates enabled, run the

following command:

gcloud run deploy SERVICE_NAME --source . \
         --base-image BASE_IMAGE \
         --automatic-updates \
         --quiet

Cloud Run only supports automatic base images that use Google Cloud's

buildpacks base

images.

* To deploy from source using a Dockerfile, run the following command:

gcloud run deploy SERVICE_NAME --source . --quiet

When you provide a Dockerfile, Cloud Build runs it in the cloud, and

deploys the service.

  • Deploy from source without build (Preview): This option deploys artifacts
directly to Cloud Run, bypassing the Cloud Build step. This allows for rapid

deployment times. To deploy from source without build, run the following

command:

gcloud beta run deploy SERVICE_NAME \
     --source APPLICATION_PATH \
     --no-build \
     --base-image=BASE_IMAGE \
     --command=COMMAND \
     --args=ARG \
     --quiet

Replace the following:

* SERVICE_NAME: the name of your Cloud Run service.

* APPLICATION_PATH: the location of your application on the local file

system.

* BASE_IMAGE: the runtime base image

you want to use for your application. For example,

us-central1-docker.pkg.dev/serverless-runtimes/google-24-full/runtimes/nodejs24.

You can also deploy a pre-compiled binary without configuring additional

language-specific runtime components using the OS only base image, such

as osonly24.

* COMMAND: the command that the container starts up with.

* ARG: an argument you send to the container command. If you use multiple

arguments, specify each on its own line.

For examples on deploying from source without build, see Examples of

deploying from source without

build.

Create and execute a Cloud Run job

To create a new job, run the following command:

gcloud run jobs create JOB_NAME --image IMAGE_URL OPTIONS --quiet

Alternatively, use the deploy command:

gcloud run jobs deploy JOB_NAME --image IMAGE_URL OPTIONS --quiet

Replace the following:

  • JOB_NAME: the name of the job you want to create. If you omit this
parameter, you will be prompted for the job name when you run the command.

  • IMAGE_URL: a reference to the container image—for example,
us-docker.pkg.dev/cloudrun/container/job:latest.

  • Optionally, replace OPTIONS with any of the following flags:

* --tasks: Accepts integers greater or equal to 1. Defaults to 1;

maximum is 10,000. Each task is provided the environment variables

CLOUD_RUN_TASK_INDEX with a value between 0 and the number of tasks

minus 1, along with CLOUD_RUN_TASK_COUNT, which is the number of

tasks.

* --max-retries: The number of times a failed task is retried. Once any

task fails beyond this limit, the entire job is marked as failed. For

example, if set to 1, a failed task will be retried once, for a total of

two attempts. The default is 3. Accepts integers from 0 to 10.

* --task-timeout: Accepts a duration like "2s". Defaults to 10 minutes;

maximum is 168 hours (7 days). For tasks using GPUs, the maximum

available timeout is 1 hour.

* --parallelism: The maximum number of tasks that can execute in

parallel. By default, tasks will be started as quickly as possible in

parallel.

* --execute-now: If set, immediately after the job is created, a job

execution is started. Equivalent to calling gcloud run jobs create

followed by gcloud run jobs execute.

In addition to these preceding options, you also specify more configuration

such as environment variables or memory limits.

For a full list of available options when creating a job, refer to the gcloud

run jobs

create

command line documentation.

Wait for the job creation to finish. You'll see a success message upon a

successful completion.

To execute an existing job, run the following command:

gcloud run jobs execute JOB_NAME --quiet

If you want the command to wait until the execution completes, run the following

command:

gcloud run jobs execute JOB_NAME --wait --region=REGION --quiet

Replace the following:

  • JOB_NAME: the name of the job.
  • REGION: the region in which the resource can be found. For example,
europe-west1. Alternatively, set the run/region property.

Deploy a worker pool

You can deploy a Cloud Run worker pool using container images or deploy directly

from the source.

Deploy a container image

You can specify a container image with a tag (for example,

us-docker.pkg.dev/my-project/container/my-image:latest) or with an exact

digest (for example,

us-docker.pkg.dev/my-project/container/my-image@sha256:41f34ab970ee...).

Supported container images

You can directly use container images stored in the Artifact

Registry, or

Docker Hub. Google recommends the use of Artifact

Registry since Docker Hub images are

cached

for up to one hour.

You can use container images from other public or private registries (like JFrog

Artifactory, Nexus, or GitHub Container Registry), by setting up an Artifact

Registry remote

repository.

You should only consider Docker Hub for deploying

popular container images such as Docker Official

Images or Docker

Sponsored OSS images. For

higher availability, Google recommends deploying these Docker Hub images using

an [Artifact Registry remo

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