Workflows are automatically replicated across multiple zones and checkpoint state after each step, ensuring executions continue even after outages. Failures in other services are handled through default and customizable retry policies, timeouts, and custom error handling.

Specify workflows in YAML or JSON with named steps, making them easy to visualize, understand, and observe. These machine-readable formats support programmatic generation and parsing of workflows.

Wait for a given period to implement polling. Connectors provide blocking steps for many Google Cloud services with long-running operations. Simply write your steps and know each is complete before the next runs.

Workflow executions are low-latency, supporting both real-time and batch processing. Through Eventarc, workflows can be executed when events occur, such as when a file is uploaded to Cloud Storage or when a Pub/Sub message is published.

Create unique callback URLs inside your workflow. Then wait (with a configurable timeout of up to one year) for the URL to be called, receiving the HTTP request data in your workflow. Useful for waiting for external systems and implementing human-in-the-loop processes.

Workflows run in a sandboxed environment and have no code dependencies that will require security patches. Store and retrieve secrets with Secret Manager.

Orchestrate work of any Google Cloud product without worrying about authentication. Use a proper service account and let Workflows do the rest.

Fast scheduling of workflow executions and transitions between steps. Predictable performance with no cold starts.

Deploy in seconds to support a fast developer experience and quick production changes.

Out-of-the-box integration with Cloud Logging with automatic and custom entries provides insight into each workflow execution. Cloud Monitoring tracks execution volume, error rates, and execution time.