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| type | title | linkTitle | weight | description |
|---|---|---|---|---|
| docs | Distributed Scheduler overview | Overview | 1000 | Overview of the distributed scheduler API building block |
The Distributed Scheduler API works as an orchestrator for scheduling jobs in the future, either at a specific time or a specific interval. The scheduler helps you with jobs like:
- Scalable actor reminders
- Scheduling any Dapr API to run at specific times or intervals, like when:
- Sending pub/sub messages
- Calling service invocations and input bindings
- Saving state to a state store
The Distributed Scheduler consists of two parts that work together to seamlessly schedule jobs across all of Dapr's API building blocks:
- The Distributed Scheduler building block
- [The Distributed Scheduler control plane service]({{< ref scheduler.md >}})
This article covers the Distributed Scheduler API building block.
How it works
The Scheduler building block is a job orchestrator, not executor. The design guarantees at least once job execution with a bias towards durability and horizontal scaling over precision. This means:
- Guaranteed: A job is never invoked before the schedule is due.
- Not guaranteed: A ceiling time on when the job is invoked after the due time is reached.
Features
Delayed pub/sub
The Distributed Scheduler building block enables you to delay your pub/sub messaging. You can publish a message in a future specific time -- for example, a week from today, or a specific UTC date/time.
Scheduled service invocation
The Distributed Scheduler building block provides the [service invocation]({{< ref service-invocation-overview.md >}}) building block with an orchestrator that schedules method calls between applications.
Schedule jobs across multiple replicas
The Scheduler service enables the scheduling of jobs to scale across multiple replicas, while guaranteeing that a job is only triggered by 1 scheduler service instance.
Actor reminders
The [Dapr Workflow building block]({{< ref workflow-overview.md >}}) is built on top of Actor Reminders. The Distributed Scheduler building block improves the performance and scale of actor reminders, which present scale limitation issues.
Store job details separately from user-associated data
If a user would like to store their user associated data in a specific state store of their choosing, then they can provision a state store using the Dapr State Management Building Block and set jobStateStore as true in the state store component’s metadata section. Having the jobStateStore set to true means that their user associate data will be stored in the state store of their choosing, but their job details will still be stored in the embedded etcd. If the jobStateStore is not configured, then the embedded etcd will be used to store both the job details and the user associated data.
Try out the Distributed Scheduler
You can try out the Distributed Scheduler building block directly in your application. After [Dapr is installed]({{< ref install-dapr-cli.md >}}), you can begin using the Distributed Scheduler API, starting with [the How-to: Set up a Scheduler guide]({{< ref howto-use-scheduler.md >}}).
Next steps
- [Learn how to use the distributed scheduler in your environment]({{< ref howto-use-scheduler.md >}})
- [Learn more about the Scheduler control plane service]({{< ref scheduler.md >}})
- [Distributed Scheduler API reference]({{< ref scheduler_api.md >}})