cloud-run-basics
Configures and manages Google Cloud Run services, jobs, and background workers.
Install
mkdir -p .claude/skills/cloud-run-basics && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/16432" && unzip -o skill.zip -d .claude/skills/cloud-run-basics && rm skill.zipInstalls to .claude/skills/cloud-run-basics
Activation
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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).Key capabilities
- →Deploy HTTP services
- →Run event-triggered tasks
- →Run scheduled tasks
- →Handle always-on pull-based background processing
- →Deploy container images to Cloud Run
- →Deploy from source code using buildpacks
How it works
The skill uses `gcloud run deploy` to deploy container images or source code to Cloud Run, which then manages the underlying infrastructure.
Inputs & outputs
When to use cloud-run-basics
- →Deploying a containerized web service
- →Scheduling background processing jobs
- →Setting up an event-triggered worker
- →Managing service scalability
About this skill
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 ofLOCATION-docker.pkg.dev/PROJECT_ID/REPO_NAME/PATH:TAG. Note that if you don't supply the--imageflag, 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 \ --quietCloud 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 . --quietWhen 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 \ --quietReplace 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 asosonly24. - 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 variablesCLOUD_RUN_TASK_INDEXwith a value between 0 and the number of tasks minus 1, along withCLOUD_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 createfollowed bygcloud 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
Content truncated.
When not to use it
- →When code does not listen on 0.0.0.0
- →When code does not use the injected $PORT environment variable
- →When deploying Docker Hub images for higher availability without Artifact Registry
Prerequisites
Limitations
- →Deployed code MUST listen on 0.0.0.0.
- →Deployed code MUST use the injected $PORT environment variable.
- →Docker Hub images are cached for up to one hour.
How it compares
This workflow abstracts away infrastructure management for deploying applications, jobs, and worker pools, simplifying the deployment process.
Compared to similar skills
cloud-run-basics side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| cloud-run-basics (this skill) | 0 | 2mo | Review | Beginner |
| terraform-module-library | 7 | 5mo | No flags | Advanced |
| genkit-infra-expert | 1 | 1mo | Review | Advanced |
| exa-deploy-integration | 0 | 1mo | Review | Advanced |
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