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This section describes Google Cloud options you can use to schedule
workflows.
Dataproc Workflow Templates
Dataproc Workflow templates
provide a flexible and easy-to-use mechanism for managing and executing workflows. A Workflow Template is a reusable workflow configuration. It defines a graph of jobs with information on where to run those jobs.
Cloud Scheduler
Cloud Scheduler is a fully managed enterprise-grade cron job scheduler.
It allows you to schedule virtually any job, including batch, big data jobs,
and Cloud infrastructure operations. It provides simple time-based
scheduling, for example, daily or hourly, without requiring you to write code.
Advantages:
Enables time-based instantiation of workflow templates based on familiar
cron expressions
Cloud Run functions is a lightweight compute solution you can use to create
single-purpose, stand-alone functions that respond to Cloud events without
the need to manage a server or runtime environment. You can use
Cloud Run functions to launch Workflows in response to Pub/Sub
events or file changes in Cloud Storage. You can use Cloud Run functions
with Cloud Scheduler for workflows that require the calculation of
time-based parameters.
Advantages:
Enables workflow instantiation in response to data events, such as new files in
Cloud Storage or Pub/Sub events.
Minimal coding required using Dataproc
Go,
Node.js, or
Python
client libraries
Dynamically generate workflows and workflow parameters
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Hard to understand","hardToUnderstand","thumb-down"],["Incorrect information or sample code","incorrectInformationOrSampleCode","thumb-down"],["Missing the information/samples I need","missingTheInformationSamplesINeed","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2025-08-25 UTC."],[[["\u003cp\u003eDataproc Workflow Templates offer a reusable configuration for defining and executing a graph of jobs within workflows.\u003c/p\u003e\n"],["\u003cp\u003eCloud Scheduler is a managed cron job scheduler enabling time-based scheduling of workflows without the need to write any code.\u003c/p\u003e\n"],["\u003cp\u003eCloud Run functions allow for workflow instantiation in response to events like new files in Cloud Storage or Pub/Sub events, requiring minimal coding.\u003c/p\u003e\n"],["\u003cp\u003eCloud Composer is a managed Apache Airflow service that supports both time- and event-based scheduling, offering dynamic workflow generation and integration across various Google Cloud products.\u003c/p\u003e\n"]]],[],null,["# Workflow scheduling solutions\n\nThis section describes Google Cloud options you can use to schedule\nworkflows.\n\nDataproc Workflow Templates\n---------------------------\n\nDataproc [Workflow templates](/dataproc/docs/concepts/workflows/overview)\nprovide a flexible and easy-to-use mechanism for managing and executing workflows. A Workflow Template is a reusable workflow configuration. It defines a graph of jobs with information on where to run those jobs.\n\nCloud Scheduler\n---------------\n\nCloud Scheduler is a fully managed enterprise-grade cron job scheduler.\nIt allows you to schedule virtually any job, including batch, big data jobs,\nand Cloud infrastructure operations. It provides simple time-based\nscheduling, for example, daily or hourly, without requiring you to write code.\n\n**Advantages:**\n\n- Enables time-based instantiation of workflow templates based on familiar\n cron expressions\n\n- No code to write\n\nTutorial: [Workflow using Cloud Scheduler](/dataproc/docs/tutorials/workflow-scheduler)\n\nCloud Functions\n---------------\n\nCloud Run functions is a lightweight compute solution you can use to create\nsingle-purpose, stand-alone functions that respond to Cloud events without\nthe need to manage a server or runtime environment. You can use\nCloud Run functions to launch Workflows in response to Pub/Sub\nevents or file changes in Cloud Storage. You can use Cloud Run functions\nwith Cloud Scheduler for workflows that require the calculation of\ntime-based parameters.\n\n**Advantages:**\n\n- Enables workflow instantiation in response to data events, such as new files in\n Cloud Storage or Pub/Sub events.\n\n- Minimal coding required using Dataproc\n [Go](https://github.com/googleapis/google-cloud-go),\n [Node.js](https://github.com/googleapis/google-cloud-node), or\n [Python](https://github.com/googleapis/google-cloud-python)\n client libraries\n\n- Dynamically generate workflows and workflow parameters\n\nTutorial: [Workflow using Cloud Run functions](/dataproc/docs/tutorials/workflow-function)\n\nCloud Composer\n--------------\n\nCloud Composer is a managed Apache Airflow service you can use\nto create, schedule, monitor, and manage workflows.\n\n**Advantages:**\n\n- Supports time- and event-based scheduling\n\n- Simplified calls to Dataproc using Operators\n\n- Dynamically generate workflows and workflow parameters\n\n- Build data flows that span multiple Google Cloud products\n\nTutorial: [Workflow using Cloud Composer](/dataproc/docs/tutorials/workflow-composer)"]]
