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Durable workflows preserve an application process’s state and progress across failures by recording its execution history and replaying workflow code against that record. Temporal’s model separates the durable Temporal Service, which stores and supervises executions, from application Workers, which run the code. The key implementation requirement is deterministic workflow logic: replay must produce the commands the existing history expects.
What is a durable workflow?
A durable workflow is a long-running application process whose progress can resume after a Worker crash, server outage, or other interruption. Temporal calls this capability Durable Execution. Its documentation describes Temporal as “a scalable and reliable runtime for durable function executions called Temporal Workflow Executions.”
Rather than relying only on a process’s in-memory state, Temporal records the workflow’s execution as an Event History. That history is the durable account of what has happened, including events associated with workflow decisions and completed work. A Worker can use it to reconstruct the workflow’s state when processing resumes.
How the history-and-replay loop works
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A Worker runs workflow code. Application code is hosted by Worker Processes and uses a Temporal SDK.
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The workflow requests work. For example, it may schedule an Activity or start a Timer. The workflow’s operation produces a Command for the Temporal Service.
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The Service records events. The Temporal Service supervises the execution and persists its Event History. The history records outcomes and other execution events rather than relying on the Worker to retain them in memory.
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A Workflow Task is processed. When a Worker processes a later task, it replays the workflow code against the recorded history. Replay rebuilds the workflow’s state by reproducing its prior decisions.
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Recorded results let execution continue. Completed Activity and Timer outcomes are supplied from history during replay. The workflow can then advance to its next decision and generate new commands.
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This is why replay is not simply restarting a function from its first line with an empty state. The code runs again, but the Event History provides the recorded context needed to reconstruct where the execution had reached.
What the Temporal Service and Workers do
| Component | Role | Who operates it |
|---|---|---|
| Temporal Service | Supervises workflow executions and persists their histories. Temporal documentation describes a service as consisting of the Temporal Server and a database. | The team, when self-hosting; Temporal, when using Temporal Cloud. |
| Worker Processes | Host and execute application workflow and Activity code using Temporal SDKs, and process Workflow Tasks. | The application team operates the Workers. |
The separation matters operationally: the Service retains the durable record, while Workers execute the application’s logic. A Worker interruption therefore does not, by itself, erase the execution history needed for later replay.
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Why deterministic workflow code is essential
Replay assumes that workflow code will make the same decisions, in the same order, when given the same recorded history. Those decisions lead to Commands, such as scheduling an Activity or Timer. If changed code or a nondeterministic branch emits a command sequence that does not match the history, the execution can fail with a nondeterminism error. Temporal explains this constraint in its workflow documentation.
Keep uncontrolled external I/O out of workflow logic. Calls to a payment processor, database, or third-party API belong in Activities or other SDK-supported operations, not as arbitrary side effects inside code that may be replayed. Temporal SDKs provide replay-safe APIs for matters such as time and randomness, as well as mechanisms for handling external information.
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Replay protects the workflow’s ability to reconstruct its own state; it does not make an external side effect exactly-once. An API call may have succeeded even if the Worker failed before recording or observing its outcome. Design Activities and external integrations with retries and idempotency in mind—for example, use an idempotency key where the external system supports one, and define how to reconcile uncertain outcomes.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.When durable workflows are useful
The model is most useful when a process must retain its state through delays, retries, or interruptions rather than finish in one short-lived request. Temporal’s materials describe mission-critical business processes, long-running agents that call tools and wait for human approval, and multi-step pipelines that need isolated retries and resumption.
- Long waits: A process can wait for a timer, an external event, or human approval without depending on one continuously running application process.
- Multi-step work: A pipeline can resume from its recorded progress and retry a unit of work rather than treating the entire process as one fragile operation.
- Tool-using agents: An agent can preserve its workflow state while coordinating tool calls and approval steps.
Durability is not a substitute for choosing appropriate boundaries. For many workflows, one Workflow coordinating Activities is a sensible starting point. Temporal advises using Child Workflows when there is a clear reason to partition work, such as separate ownership, resource boundaries, or a large workload. Child executions add events to histories, and histories have limits, so decomposition also has costs. See Temporal’s guidance on Child Workflows.
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Self-hosting or Temporal Cloud?
The choice concerns who operates the Temporal Service, not whether application code still needs Workers. With self-hosting, the team runs the Temporal Server and database and has more direct control over that infrastructure. Temporal Cloud is Temporal’s managed service option for the Service; the application team continues to operate its Worker Processes.
| Deployment | Service and database operations | Infrastructure control | Worker operations |
|---|---|---|---|
| Self-hosted Temporal Service | The team operates the Temporal Server and database. | The team manages the deployment environment directly. | The application team operates Workers. |
| Temporal Cloud | Temporal provides the managed Temporal Service. | The service is managed rather than operated entirely on the team’s own infrastructure. | The application team still operates Workers. |
Choose based on the team’s capacity and requirements for operating infrastructure versus using a managed Service. The cited documentation does not establish current Cloud pricing, region availability, or a complete security comparison, so those details should be checked against current Temporal materials before making a deployment decision.
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