Build Cloud Run Jobs with task count, parallelism, retries, env/secrets, and scheduling in gcloud and Terraform.
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No environment variables configured.
No secrets configured.
Cloud Scheduler cron expression
Output will appear here...Cloud Run Jobs run tasks to completion and then exit, ideal for batch processing, data pipelines, and scheduled work. Cloud Run Services handle HTTP requests and run continuously. Jobs don't need to listen on a port and are billed only while tasks execute.
Each job execution creates task count independent tasks. The parallelism setting controls how many tasks run concurrently. Each task gets a CLOUD_RUN_TASK_INDEX (0 to N-1) and CLOUD_RUN_TASK_COUNT environment variable for work distribution.
Failed tasks are retried up to max retries times. A task is considered failed if the container exits with a non-zero code or exceeds the timeout. Use exit code 0 for success.
Use Cloud Scheduler to trigger job executions on a cron schedule. The scheduler invokes the Cloud Run Admin API to start a job execution. Requires OAuth authentication with a service account that has the roles/run.invoker role.
Cloud Run Jobs: serverless, fast startup, up to 24h timeout, simpler container model, good for moderate batch work. Cloud Batch: supports GPUs, longer runtimes, VM-level configuration, MPI workloads, better for HPC and large-scale batch computing.
The Cloud Run Jobs Builder helps you configure Cloud Run Jobs with task count, parallelism, retry policies, environment variables, secret references, and scheduling. Unlike Cloud Run services that respond to HTTP requests, jobs run to completion and are ideal for batch processing, data migrations, and scheduled tasks. The tool generates gcloud CLI commands and Terraform configurations.
Disclaimer: This tool runs entirely in your browser. No data is sent to our servers. Always verify outputs before using them in production. AWS, Azure, and GCP are trademarks of their respective owners.