> ## Documentation Index > Fetch the complete documentation index at: https://docs.prophecy.ai/llms.txt > Use this file to discover all available pages before exploring further. # Scheduling > Automate your pipeline runs using schedules Prophecy supports the following ways to automate pipeline execution. * **Built-in scheduler**: Use [Prophecy Automate](/data-analysis/administration/platform/architecture) to orchestrate pipelines from the UI. * **Pipeline gem**: Configure the [Pipeline gem](/data-analysis/production/scheduling/pipeline-trigger-gem) to start pipeline runs from a gem. * **API**: Call the [Trigger Pipeline API](/api-reference/pipelines/trigger-pipeline-run) to start pipelines from external systems. This page describes how to use the **built-in scheduler** in SQL projects. ## Overview In Prophecy, a schedule automates the execution of a single pipeline in a project. Scheduled pipelines run in [fabrics](/data-analysis/environment/fabrics/prophecy-fabrics) (execution environments) that are defined during project publication. Each schedule defines: * When the pipeline should run. Prophecy supports time-based or file-based [triggers](/data-analysis/production/scheduling/triggers). * Optional [email alerts](/data-analysis/production/scheduling/alerts) to report the outcome of the pipeline run. To schedule multiple pipelines, create a separate schedule for each one. You can enable or disable schedules individually, but enabling a schedule doesn't activate it. An enabled schedule becomes active **only when the parent project is published**. Similarly, disabling a schedule also requires republishing the project, since schedule status is part of the deployment configuration. ## Schedule activation Enabling a schedule in your project doesn't immediately activate it. For a schedule to take effect, you must first [publish the project](/data-analysis/production/publication). This is because publishing defines how and where scheduled pipelines are deployed and executed. When you publish a project, you do two key things: * Select one or more fabrics. These are the environments where scheduled pipelines will run. A separate deployment is created for each fabric — publishing to one fabric does not affect other deployments. If you do not select any fabrics during project publication, **no deployments will be created**. As a result, no scheduled executions will occur, even if a schedule has been configured. * Specify the project version. This version will be deployed to the fabric. You can either create a new version or deploy a previously published version. Scheduling flow ## Monitor scheduled pipelines You and your team members might have many scheduled pipelines in your Prophecy environment. The [Observability](/data-analysis/production/monitoring) interface in Prophecy includes the following information: * List of deployed projects * List of pipeline schedules per fabric * History of pipeline runs and run status You'll only see information about projects owned by your teams. ## Authentication lifespan Scheduled pipelines run without human intervention, which makes them vulnerable to failures caused by expired or invalid credentials. If Prophecy cannot authenticate a connection used by the pipeline due to an error such as an expired token or deleted user, the pipeline run will fail. This risk increases in complex environments where: * Pipelines depend on multiple external data sources. * The same schedule is deployed across multiple fabrics. * Fabrics store different credentials for the same connection. To ensure reliable scheduled runs, only deploy to fabrics that use connection credentials that won't expire unexpectedly. For Databricks connections, [consider using a service principal](/data-analysis/environment/connections/databricks#authentication-methods) for authentication. Service principals are designed for authorizing access to Databricks resources when running unattended processes. ## What's next To learn more about using the Prophecy-native scheduler, explore the following pages. * [Set up schedule](/data-analysis/production/scheduling/schedule-setup) * [Schedule trigger types](/data-analysis/production/scheduling/triggers) * [Email alerts](/data-analysis/production/scheduling/alerts) * [Pipeline gem](/data-analysis/production/scheduling/pipeline-trigger-gem)