tensology/decisionsai/cloud-run-basics
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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).
Install
npx vskill@latest install tensology/decisionsai/cloud-run-basicsSKILL.md
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:
``bash 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:
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 willcrash 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:
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:
``bash 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:
``bash 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:
``bash 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:
Alternatively, use the deploy command:
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:
If you want the command to wait until the execution completes, run the following command:
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.
This is the start of the file. Read the full SKILL.md on GitHub.
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