Dapr Jobs lets an application schedule a future trigger; it does not run the application’s task for it. The Dapr Scheduler service persists and delivers that trigger, and your application handles the resulting invocation. Dapr documents at-least-once execution—not exactly-once delivery—and does not promise a maximum delay after a job becomes due. It fits durable future-work triggers when those limits suit your use case and your handler can safely tolerate retries.
What the Dapr Jobs API and Scheduler each do
The Jobs API is the application-facing way to create, query, and manage scheduled jobs. A job has a name and a schedule, a due time, or both. When it is due, Dapr Scheduler routes a trigger to the application; the application’s handler performs the actual work. The API and service arrange and deliver the invocation, but they do not execute your business logic on your behalf. See the Dapr Jobs overview.
Scheduler is shared Dapr infrastructure, not a separate timer process dedicated to one job. It also manages Actor Reminders and Workflow-related jobs. Its replicas are peers: jobs are distributed among available replicas for trigger load balancing. By default, a trigger is sent to one randomly load-balanced replica of the same app ID that scheduled it. If work must run on an exact actor host, Dapr describes actor reminders as an alternative pattern. See the Scheduler service overview.
When Dapr Jobs is a good fit—and when it is not
Jobs can suit one-time or recurring future work when you already use Dapr, need a durable scheduled trigger, and can make the application handler resilient to repeated invocations. Your application remains responsible for completing the task and for any task-specific state or idempotency safeguards.
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Do not treat it as a precision timer or as a guarantee that work will start within a fixed lateness window. Dapr says a job is never invoked before it is due, but does not specify a maximum delay after the due time. Sub-second duration schedules are a documented capability, not a promise that your handler will run with sub-second precision. Compare any scheduler against your requirements for tolerated lateness, duplicate delivery, persistence and recovery, routing locality, schedule/time-zone behavior, and deployment operations.
How to define a Dapr job
The Jobs API accepts a named job with schedule, dueTime, or both; at least one is required. The Jobs API reference documents these schedule forms:
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- Cron: Six fields for seconds, minutes, hours, day of month, month, and day of week. Cron schedules have second-level granularity.
- Human-readable recurring periods: Examples include
@every 1h30m,@daily, and@hourly. - One-time due times: RFC3339 timestamps, Go duration strings relative to job creation, or non-repeating ISO8601 forms.
- Additional behavior: The API supports repeat counts, TTL/expiration, overwrite behavior, and failure policies.
For duration-based schedules, Dapr documents sub-second precision, such as 500ms; actual trigger resolution can vary by runtime. This describes accepted scheduling capability, not a punctuality or latency guarantee.
Account for time zones explicitly
An RFC3339 timestamp can include a time zone. If it does not, Dapr uses the server’s local time, so an unqualified timestamp does not inherently mean UTC. Include an explicit zone in timestamps when the intended schedule must not depend on the Scheduler server’s local setting. See the Jobs features and concepts.
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Choose names and overwrite behavior deliberately
Job names are case-sensitive and intended to be unique across services using the Dapr runtime. Only one job can occupy a given name: creating a duplicate fails unless overwrite is enabled. With overwrite enabled, the newly submitted job becomes the recorded job for that name. See the Jobs features and concepts and Jobs overview.
What happens when a job is due or the app is unavailable
Dapr documents at-least-once execution. A trigger can therefore be delivered more than once, and application code should be safe to invoke again. Where duplicate work would have consequences, use application-level idempotency or equivalent safeguards rather than relying on exactly-once delivery. The due-time guarantee is one-sided: a job will not be invoked early, but Dapr does not guarantee a maximum post-due delay. See the Jobs overview.
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For a client-side error when a trigger is delivered, Scheduler’s documented default is to retry at one-second intervals, up to three retries. If a suitable sidecar is unavailable at trigger time, Scheduler stages the job until one becomes available. These behaviors make application and Scheduler availability part of the same execution path; monitor both, and do not infer a fixed completion deadline from retries or staging. See the Scheduler service overview and Jobs API reference.
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Scheduler uses embedded Etcd by default to persist jobs and related data. In Kubernetes, it is deployed in high-availability mode, but its replicas are not intended to be scaled up or down freely: changing replica count risks data loss with the embedded-store design. Plan capacity and high-availability changes carefully; Dapr also supports configuration with external Etcd. Consult the Scheduler overview.
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Check the actual Kubernetes PVC, especially after upgrades
For fresh Kubernetes installs on Dapr v1.18 and later, the Scheduler database uses a 16Gi PVC with the cluster’s default StorageClass. A cluster upgraded from before v1.18 may retain its previous PVC size, commonly 1Gi, because the StatefulSet volume claim template is immutable. The fresh-install default therefore does not establish the size of an upgraded cluster’s existing volume.
Inspect the deployed StatefulSet, PVC, and StorageClass rather than assuming the current default applies. Configure storage where the default is unsuitable. Dapr’s Scheduler persistence guide covers the version-sensitive sizing behavior; the Kubernetes hosting overview provides broader deployment context.
Quick Recap
Production implementation checklist
- Use the production-facing API path: Dapr recommends language SDKs using gRPC for production; its HTTP API is intended for development and testing. Confirm the relevant SDK documentation for your language and deployed runtime version. See the Jobs API reference.
- Make handlers retry-safe: At-least-once execution means the task may be invoked multiple times.
- Set the time zone in the timestamp: Do not rely on the server’s local zone when you intend a particular zone.
- Verify storage on Kubernetes: Check the actual PVC and StorageClass, particularly on clusters upgraded from before v1.18.
- Use Scheduler’s CLI for job operations: Dapr documents commands to list, inspect, back up, and delete scheduled jobs. Check the CLI reference matching your deployed version for exact command syntax.
- Confirm version-specific details: Defaults can change between runtime releases; validate operational settings and SDK behavior against the version you deploy.
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