A durable execution engine for running tasks durably and resiliently.
Tasks can range from being a simple function to a complex workflow. The tasks are resilient to logic failures, process failures, network connectivity issues, and other transient errors. The tasks logic should be idempotent as they may be executed multiple times if there is a process failure or if the task is retried.
Use DurableExecutor
directly to enqueue and execute tasks within the same process. This is the
simplest way to use durable-execution for local or single-process scenarios.
A durable executor can also be started as its own separate server process or just as a separate module. Tasks can be enqueued with RPC calls to the durable executor process. Utilities to create a typesafe implementation of the durable executor server are provided in the durable-execution-orpc-utils package using the oRPC library.
npm install effect durable-execution
pnpm add effect durable-execution
Create a storage implementation that implements the TaskExecutionsStorage type. The implementation should support async transactions that allow running multiple transactions in parallel.
src/in-memory-storage.ts
file for testing and simple use cases
If using effect, use the makeEffectDurableExecutor
function to create the executor with first
class support for effect. See
makeEffectDurableExecutor
for more details.
import { childTask, DurableExecutor } from 'durable-execution'
import { Schema } from 'effect'
const executor = await DurableExecutor.make(storage)
async function app() {
// ... use the durable executor to enqueue functions and workflows
}
// Start the durable executor
await executor.start()
// Run the app
await app()
// Shutdown the durable executor when the app is done
await executor.shutdown()
const extractFileTitle = executor
.inputSchema(Schema.Struct({ filePath: Schema.String }))
.task({
id: 'extractFileTitle',
timeoutMs: 30_000, // 30 seconds
run: async (ctx, input) => {
// ... extract the file title
return {
title: 'File Title',
}
},
})
const summarizeFile = executor
.validateInput(async (input: { filePath: string }) => {
// Example validation function - implement your own validation logic
if (!isValidFilePath(input.filePath)) {
throw new Error('Invalid file path')
}
return {
filePath: input.filePath,
}
})
.task({
id: 'summarizeFile',
timeoutMs: 30_000, // 30 seconds
run: async (ctx, input) => {
// ... summarize the file
return {
summary: 'File summary',
}
},
})
const uploadFile = executor
.inputSchema(Schema.Struct({ filePath: Schema.String, uploadUrl: Schema.String }))
.parentTask({
id: 'uploadFile',
timeoutMs: 60_000, // 1 minute
runParent: async (ctx, input) => {
// ... upload file to the given uploadUrl
// Extract the file title and summarize the file in parallel
return {
output: {
filePath: input.filePath,
uploadUrl: input.uploadUrl,
fileSize: 100,
},
children: [
childTask(extractFileTitle, { filePath: input.filePath }),
childTask(summarizeFile, { filePath: input.filePath }),
],
}
},
finalize: {
id: 'uploadFileFinalize',
timeoutMs: 60_000, // 1 minute
run: async (ctx, { output, children }) => {
// ... combine the output of the run function and children tasks
return {
filePath: output.filePath,
uploadUrl: output.uploadUrl,
fileSize: 100,
title: 'File Title',
summary: 'File summary',
}
}
},
})
async function app() {
// Enqueue task and manage its execution lifecycle
const uploadFileHandle = await executor.enqueueTask(uploadFile, {
filePath: 'file.txt',
uploadUrl: 'https://example.com/upload',
})
const uploadFileExecution = await uploadFileHandle.getExecution()
const uploadFileFinishedExecution = await uploadFileHandle.waitAndGetFinishedExecution()
await uploadFileHandle.cancel()
console.log(uploadFileExecution)
}
const taskA = executor.task({
id: 'a',
timeoutMs: 1000,
run: (ctx, input: { name: string }) => {
// ... do some synchronous work
return `Hello, ${input.name}!`
},
})
// Input: { name: 'world' }
// Output: 'Hello, world!'
const taskA = executor.task({
id: 'a',
timeoutMs: 1000,
run: async (ctx, input: { name: string }) => {
// ... do some asynchronous work
await sleep(1)
return `Hello, ${input.name}!`
},
})
// Input: { name: 'world' }
// Output: 'Hello, world!'
To validate input, use the validateInput
method before the task
method.
const taskA = executor
.validateInput((input: { name: string }) => {
if (input.name !== 'world') {
throw new Error('Invalid input')
}
return input
})
.task({
id: 'a',
timeoutMs: 1000,
run: (ctx, input) => {
// ... do some work
return `Hello, ${input.name}!`
},
})
// Input: { name: 'world' }
// Output: 'Hello, world!'
The inputSchema
method supports any
Standard Schema compatible validation library (Zod, Yup, Joi, etc.)
or Effect Schema.
import { Schema } from 'effect'
const taskA = executor.inputSchema(Schema.Struct({ name: Schema.String })).task({
id: 'a',
timeoutMs: 1000,
run: (ctx, input) => {
// ... do some work
return `Hello, ${input.name}!`
},
})
// Input: { name: 'world' }
// Output: 'Hello, world!'
let totalAttempts = 0
const taskA = executor.task({
id: 'a',
retryOptions: {
maxAttempts: 5,
baseDelayMs: 100,
delayMultiplier: 1.5,
maxDelayMs: 1000,
},
timeoutMs: 1000,
run: (ctx, input: { name: string }) => {
totalAttempts++
if (ctx.attempt < 2) {
throw new Error('Failed')
}
return {
totalAttempts,
output: `Hello, ${input.name}!`,
}
},
})
// Input: { name: 'world' }
// Output: {
// totalAttempts: 3,
// output: 'Hello, world!',
// }
The run function is passed a context object that contains information about the task execution. See the TaskRunContext type for more details.
const taskA = executor.task({
id: 'a',
timeoutMs: 1000,
run: (ctx) => {
return {
taskId: ctx.taskId,
executionId: ctx.executionId,
attempt: ctx.attempt,
prevError: ctx.prevError,
}
},
})
// Input: undefined
// Output: {
// taskId: 'a',
// executionId: 'te_...',
// attempt: 0,
// prevError: undefined,
// }
flowchart TD
parentTask --> taskA
parentTask --> taskB
const taskA = executor.task({
id: 'a',
timeoutMs: 1000,
run: (ctx, input: { name: string }) => {
return `Hello from task A, ${input.name}!`
},
})
const taskB = executor.task({
id: 'b',
timeoutMs: 1000,
run: (ctx, input: { name: string }) => {
return `Hello from task B, ${input.name}!`
},
})
const parentTask = executor.parentTask({
id: 'parent',
timeoutMs: 1000,
runParent: (ctx, input: { name: string }) => {
return {
output: `Hello from parent task, ${input.name}!`,
children: [
childTask(taskA, { name: input.name }),
childTask(taskB, { name: input.name }),
],
}
},
})
// Input: { name: 'world' }
// Output: {
// output: 'Hello from parent task, world!',
// childrenOutputs: [
// { output: 'Hello from task A, world!' },
// { output: 'Hello from task B, world!' },
// ],
// }
flowchart TD
parentTask --> taskA
parentTask --> taskB
The finalize
task is run after the runParent
function and all the children tasks complete. It
is useful for combining the output of the runParent
function and children tasks. The output of
the finalize
task is the output of the parent task.
Critical: The finalize
function/task receives outputs from all children, including those that
have failed. This behaves similar to Promise.allSettled()
- you get the results regardless of
individual child success or failure. This allows you to implement custom error handling logic, such
as failing the parent only if critical children fail, or providing partial results. As a caveat,
always check the status of child executions in the finalize function/task.
const taskA = executor.task({
id: 'a',
timeoutMs: 1000,
run: (ctx, input: { name: string }) => {
return `Hello from task A, ${input.name}!`
},
})
const taskB = executor.task({
id: 'b',
timeoutMs: 1000,
run: (ctx, input: { name: string }) => {
return `Hello from task B, ${input.name}!`
},
})
const parentTask = executor.parentTask({
id: 'parent',
timeoutMs: 1000,
runParent: (ctx, input: { name: string }) => {
return {
output: `Hello from parent task, ${input.name}!`,
children: [
childTask(taskA, { name: input.name }),
childTask(taskB, { name: input.name }),
],
}
},
finalize: {
id: 'onParentRunAndChildrenComplete',
timeoutMs: 1000,
run: (ctx, { output, children }) => {
const child1 = children[0]!
const child2 = children[1]!
// The finalize function receives all children executions, including failed ones.
// This allows you to implement custom error handling logic.
if (child1.status !== 'completed' || child2.status !== 'completed') {
throw DurableExecutionError.nonRetryable('Children failed')
}
return {
parentOutput: output,
taskAOutput: child1.output as string,
taskBOutput: child2.output as string,
}
},
},
})
// Input: { name: 'world' }
// Output: {
// parentOutput: 'Hello from parent task, world!',
// taskAOutput: 'Hello from task A, world!',
// taskBOutput: 'Hello from task B, world!',
// }
The finalize
function receives results from all children, including failed ones, similar to
Promise.allSettled()
. This allows you to implement custom error handling logic.
const taskA = executor.task({
id: 'a',
timeoutMs: 1000,
run: (ctx, input: { name: string }) => {
return `Hello from task A, ${input.name}!`
},
})
const taskB = executor.task({
id: 'b',
timeoutMs: 1000,
run: () => {
throw new Error('Failed')
},
})
const parentTask = executor.parentTask({
id: 'parent',
timeoutMs: 1000,
runParent: (ctx, input: { name: string }) => {
return {
output: `Hello from parent task, ${input.name}!`,
children: [
childTask(taskA, { name: input.name }),
childTask(taskB),
],
}
},
finalize: {
id: 'onParentRunAndChildrenComplete',
timeoutMs: 1000,
run: (ctx, { output, children }) => {
const child1 = children[0]!
const child2 = children[1]!
// The finalize function receives all children executions, including failed ones.
// This allows you to implement custom error handling logic.
if (child1.status !== 'completed' || child2.status !== 'completed') {
throw DurableExecutionError.nonRetryable('Children failed')
}
return {
parentOutput: output,
taskAOutput: child1.output as string,
taskBOutput: child2.output as string,
}
},
},
})
// Input: { name: 'world' }
// Finished execution: {
// status: 'finalize_failed',
// error: {
// errorType: 'generic',
// message: 'Children failed',
// isRetryable: false,
// },
// ... other fields
// }
const taskA = executor.task({
id: 'a',
timeoutMs: 1000,
run: (ctx, input: { name: string }) => {
return `Hello from task A, ${input.name}!`
},
})
const taskB = executor.task({
id: 'b',
timeoutMs: 1000,
run: () => {
throw new Error('Failed')
},
})
const resilientParentTask = executor.parentTask({
id: 'resilientParent',
timeoutMs: 1000,
runParent: (ctx, input: { name: string }) => {
return {
output: `Hello from parent task, ${input.name}!`,
children: [
childTask(taskA, { name: input.name }),
childTask(taskB),
],
}
},
finalize: {
id: 'resilientFinalize',
timeoutMs: 1000,
run: (ctx, { output, children }) => {
const results = children.map((child, index) => ({
index,
success: child.status === 'completed',
result: child.status === 'completed' ? child.output : child.error?.message
}))
const successfulResults = results.filter(r => r.success)
// Continue even if some children failed.
return {
parentOutput: output,
successfulCount: successfulResults.length,
totalCount: children.length,
results
}
},
},
})
// Input: { name: 'world' }
// Output: {
// parentOutput: 'Hello from parent task, world!',
// successfulCount: 1,
// totalCount: 2,
// results: [
// { index: 0, success: true, result: 'Hello from task A, world!' },
// { index: 1, success: false, result: 'Failed' }
// ],
// }
flowchart LR
taskA --> taskB
taskB --> taskC
Using the sequentialTasks
method in the
DurableExecutor class,
you can create a sequential task that runs a list of tasks sequentially.
The tasks list must be a list of tasks that are compatible with each other. The input of any task must be the same as the output of the previous task. The output of the last task will be the output of the sequential task.
The tasks list cannot be empty.
const taskA = executor.task({
id: 'a',
timeoutMs: 1000,
run: (ctx, input: { name: string }) => {
return {
name: input.name,
taskAOutput: `Hello from task A, ${input.name}!`,
}
},
})
const taskB = executor.task({
id: 'b',
timeoutMs: 1000,
run: (ctx, input: { name: string; taskAOutput: string }) => {
return {
name: input.name,
taskAOutput: input.taskAOutput,
taskBOutput: `Hello from task B, ${input.name}!`,
}
},
})
const taskC = executor.task({
id: 'c',
timeoutMs: 1000,
run: (ctx, input: { name: string; taskAOutput: string; taskBOutput: string }) => {
return {
taskAOutput: input.taskAOutput,
taskBOutput: input.taskBOutput,
taskCOutput: `Hello from task C, ${input.name}!`,
}
},
})
const task = executor.sequentialTasks('seq', [taskA, taskB, taskC])
// Input: { name: 'world' }
// Output: {
// taskAOutput: 'Hello from task A, world!',
// taskBOutput: 'Hello from task B, world!',
// taskCOutput: 'Hello from task C, world!',
// }
Sequential tasks can also be implemented manually just by using the parentTask
method. Use the
dedicated sequentialTasks
method in production as described above. This example is useful only to
understand the flexibility of the parentTask
method.
The finalize
task can itself be a parent task with parallel children. This property can be used
to spawn parallel children from the task runParent
function and then using the finalize
task
to run a sequential task.
const taskC = executor.task({
id: 'c',
timeoutMs: 1000,
run: (ctx, input: { name: string }) => {
return `Hello from task C, ${input.name}!`
},
})
const taskB = executor.parentTask({
id: 'b',
timeoutMs: 1000,
runParent: (ctx, input: { name: string }) => {
return {
output: {
name: input.name,
taskBOutput: `Hello from task B, ${input.name}!`,
},
}
},
finalize: {
id: 'taskBFinalize',
timeoutMs: 1000,
runParent: (ctx, { output }) => {
return {
output: output.taskBOutput,
children: [childTask(taskC, { name: output.name })],
}
},
finalize: {
id: 'taskBFinalizeNested',
timeoutMs: 1000,
run: (ctx, { output, children }) => {
const child = children[0]!
if (child.status !== 'completed') {
throw DurableExecutionError.nonRetryable('Child failed')
}
return {
taskBOutput: output,
taskCOutput: child.output as string,
}
},
},
},
})
const taskA = executor.parentTask({
id: 'a',
timeoutMs: 1000,
runParent: (ctx, input: { name: string }) => {
return {
output: {
name: input.name,
taskAOutput: `Hello from task A, ${input.name}!`,
},
}
},
finalize: {
id: 'taskAFinalize',
timeoutMs: 1000,
runParent: (ctx, { output }) => {
return {
output: output.taskAOutput,
children: [childTask(taskB, { name: output.name })],
}
},
finalize: {
id: 'taskAFinalizeNested',
timeoutMs: 1000,
run: (ctx, { output, children }) => {
const child = children[0]!
if (child.status !== 'completed') {
throw DurableExecutionError.nonRetryable('Child failed')
}
const taskBOutput = child.output as {
taskBOutput: string
taskCOutput: string
}
return {
taskAOutput: output,
taskBOutput: taskBOutput.taskBOutput,
taskCOutput: taskBOutput.taskCOutput,
}
},
},
},
})
// Input: { name: 'world' }
// Output: {
// taskAOutput: 'Hello from task A, world!',
// taskBOutput: 'Hello from task B, world!',
// taskCOutput: 'Hello from task C, world!',
// }
Here dotted lines represent the sequential execution of the tasks.
flowchart TD
taskA -. sequential .-> taskB
taskA --> taskA1
taskA --> taskA2
taskB --> taskB1
taskB --> taskB2
Similar to the sequential tasks example with sequentialTasks
but with each task also having
parallel children.
const taskA1 = executor.task({
id: 'a1',
timeoutMs: 1000,
run: (ctx, input: { name: string }) => {
return `Hello from task A1, ${input.name}!`
},
})
const taskA2 = executor.task({
id: 'a2',
timeoutMs: 1000,
run: (ctx, input: { name: string }) => {
return `Hello from task A2, ${input.name}!`
},
})
const taskB1 = executor.task({
id: 'b1',
timeoutMs: 1000,
run: (ctx, input: { name: string }) => {
return `Hello from task B1, ${input.name}!`
},
})
const taskB2 = executor.task({
id: 'b2',
timeoutMs: 1000,
run: (ctx, input: { name: string }) => {
return `Hello from task B2, ${input.name}!`
},
})
const taskA = executor.parentTask({
id: 'a',
timeoutMs: 1000,
runParent: (ctx, input: { name: string }) => {
return {
output: {
name: input.name,
taskAOutput: `Hello from task A, ${input.name}!`,
},
children: [
childTask(taskA1, { name: input.name }),
childTask(taskA2, { name: input.name }),
],
}
},
finalize: {
id: 'taskAFinalize',
timeoutMs: 1000,
run: (ctx, { output, children }) => {
const child1 = children[0]!
const child2 = children[1]!
if (child1.status !== 'completed' || child2.status !== 'completed') {
throw DurableExecutionError.nonRetryable('Children failed')
}
return {
name: output.name,
taskAOutput: output.taskAOutput,
taskA1Output: child1.output as string,
taskA2Output: child2.output as string,
}
},
},
})
const taskB = executor.parentTask({
id: 'b',
timeoutMs: 1000,
runParent: (
ctx,
input: { name: string; taskAOutput: string; taskA1Output: string; taskA2Output: string },
) => {
return {
output: {
taskAOutput: input.taskAOutput,
taskA1Output: input.taskA1Output,
taskA2Output: input.taskA2Output,
taskBOutput: `Hello from task B, ${input.name}!`,
},
children: [
childTask(taskB1, { name: input.name }),
childTask(taskB2, { name: input.name }),
],
}
},
finalize: {
id: 'taskBFinalize',
timeoutMs: 1000,
run: (ctx, { output, children }) => {
const child1 = children[0]!
const child2 = children[1]!
if (child1.status !== 'completed' || child2.status !== 'completed') {
throw DurableExecutionError.nonRetryable('Children failed')
}
return {
...output,
taskB1Output: child1.output as string,
taskB2Output: child2.output as string,
}
},
},
})
const task = executor.sequentialTasks('seq', [taskA, taskB])
// Input: { name: 'world' }
// Output: {
// taskAOutput: 'Hello from task A, world!',
// taskA1Output: 'Hello from task A1, world!',
// taskA2Output: 'Hello from task A2, world!',
// taskBOutput: 'Hello from task B, world!',
// taskB1Output: 'Hello from task B1, world!',
// taskB2Output: 'Hello from task B2, world!',
// }
flowchart TD
rootTask --> taskA
rootTask --> taskB1
taskA --> taskA1
taskA --> taskA2
taskA --> taskA3
taskB1 --> taskB2
taskB2 --> taskB3
Parallel and sequential tasks can be combined to create a tree of tasks.
const taskB1 = executor.task({
id: 'b1',
timeoutMs: 1000,
run: (ctx, input: { name: string }) => {
return {
name: input.name,
taskB1Output: `Hello from task B1, ${input.name}!`,
}
},
})
const taskB2 = executor.task({
id: 'b2',
timeoutMs: 1000,
run: (ctx, input: { name: string; taskB1Output: string }) => {
return {
name: input.name,
taskB1Output: input.taskB1Output,
taskB2Output: `Hello from task B2, ${input.name}!`,
}
},
})
const taskB3 = executor.task({
id: 'b3',
timeoutMs: 1000,
run: (ctx, input: { name: string; taskB1Output: string; taskB2Output: string }) => {
return {
taskB1Output: input.taskB1Output,
taskB2Output: input.taskB2Output,
taskB3Output: `Hello from task B3, ${input.name}!`,
}
},
})
const taskB = executor.sequentialTasks('b', [taskB1, taskB2, taskB3])
const taskA1 = executor.task({
id: 'a1',
timeoutMs: 1000,
run: (ctx, input: { name: string }) => {
return `Hello from task A1, ${input.name}!`
},
})
const taskA2 = executor.task({
id: 'a2',
timeoutMs: 1000,
run: (ctx, input: { name: string }) => {
return `Hello from task A2, ${input.name}!`
},
})
const taskA3 = executor.task({
id: 'a3',
timeoutMs: 1000,
run: (ctx, input: { name: string }) => {
return `Hello from task A3, ${input.name}!`
},
})
const taskA = executor.parentTask({
id: 'a',
timeoutMs: 1000,
runParent: (ctx, input: { name: string }) => {
return {
output: `Hello from task A, ${input.name}!`,
children: [
childTask(taskA1, { name: input.name }),
childTask(taskA2, { name: input.name }),
childTask(taskA3, { name: input.name }),
],
}
},
finalize: {
id: 'taskAFinalize',
timeoutMs: 1000,
run: (ctx, { output, children }) => {
const child1 = children[0]!
const child2 = children[1]!
const child3 = children[2]!
if (
child1.status !== 'completed' ||
child2.status !== 'completed' ||
child3.status !== 'completed'
) {
throw DurableExecutionError.nonRetryable('Children failed')
}
return {
taskAOutput: output,
taskA1Output: child1.output as string,
taskA2Output: child2.output as string,
taskA3Output: child3.output as string,
}
},
},
})
const rootTask = executor.parentTask({
id: 'root',
timeoutMs: 1000,
runParent: (ctx, input: { name: string }) => {
return {
output: `Hello from root task, ${input.name}!`,
children: [
childTask(taskA, { name: input.name }),
childTask(taskB, { name: input.name }),
],
}
},
finalize: {
id: 'rootFinalize',
timeoutMs: 1000,
run: (ctx, { output, children }) => {
const child1 = children[0]!
const child2 = children[1]!
if (child1.status !== 'completed' || child2.status !== 'completed') {
throw DurableExecutionError.nonRetryable('Children failed')
}
const taskAOutput = child1.output as {
taskAOutput: string
taskA1Output: string
taskA2Output: string
taskA3Output: string
}
const taskBOutput = child2.output as {
taskB1Output: string
taskB2Output: string
taskB3Output: string
}
return {
rootOutput: output,
taskAOutput: taskAOutput.taskAOutput,
taskA1Output: taskAOutput.taskA1Output,
taskA2Output: taskAOutput.taskA2Output,
taskA3Output: taskAOutput.taskA3Output,
taskB1Output: taskBOutput.taskB1Output,
taskB2Output: taskBOutput.taskB2Output,
taskB3Output: taskBOutput.taskB3Output,
}
},
},
})
// Input: { name: 'world' }
// Output: {
// rootOutput: 'Hello from root task, world!',
// taskAOutput: 'Hello from task A, world!',
// taskA1Output: 'Hello from task A1, world!',
// taskA2Output: 'Hello from task A2, world!',
// taskA3Output: 'Hello from task A3, world!',
// taskB1Output: 'Hello from task B1, world!',
// taskB2Output: 'Hello from task B2, world!',
// taskB3Output: 'Hello from task B3, world!',
// }
Recursive tasks require some type annotations to be able to infer the input and output types, since
we are using the same variable inside the runParent
function. Use the finalize
task to
coordinate the output of the recursive task and children tasks.
const recursiveTask: Task<{ index: number }, { count: number }> = executor
.inputSchema(Schema.Struct({ index: Schema.Int.pipe(Schema.greaterThanOrEqualTo(0)) }))
.parentTask({
id: 'recursive',
timeoutMs: 1000,
runParent: async (ctx, input) => {
await sleep(1)
return {
output: undefined,
children:
input.index >= 9 ? [] : [childTask(recursiveTask, { index: input.index + 1 })],
}
},
finalize: {
id: 'recursiveFinalize',
timeoutMs: 1000,
run: (ctx, { children }) => {
if (children.some((child) => child.status !== 'completed')) {
throw DurableExecutionError.nonRetryable('Children failed')
}
return {
count:
1 +
(children as Array<CompletedChildTaskExecution>).reduce(
(acc, child) => acc + (child.output as { count: number }).count,
0,
),
}
},
},
})
// Input: { index: 0 }
// Output: {
// count: 10,
// }
Looping tasks are useful when you want to run a task again and again until a condition is met.
let value: number | undefined
setTimeout(() => {
value = 10
}, 1000)
const iterationTask = executor.task({
id: 'iteration',
sleepMsBeforeRun: 100,
timeoutMs: 1000,
run: () => {
return value == null
? {
isDone: false,
}
: {
isDone: true,
output: value,
}
},
})
const loopingTask = executor.loopingTask('looping', iterationTask, 20, 100)
// Input: undefined
// Output: {
// isSuccess: true,
// output: 10,
// }
Looping tasks can also be implemented manually just by using the parentTask
method. Use the
dedicated loopingTask
method in production as described above. This example is useful only to
understand the flexibility of the parentTask
method.
The sleepMsBeforeRun
option is used to wait for a certain amount of time before attempting to get
the value again. The finalize
task is used to combine the output of the looping task and children
tasks.
let value: number | undefined
setTimeout(() => {
value = 10
}, 2000)
const loopingTask: Task<{ prevCount: number }, { count: number; value: number }> = executor
.inputSchema(Schema.Struct({ prevCount: Schema.Int.pipe(Schema.greaterThanOrEqualTo(0)) }))
.parentTask({
id: 'looping',
sleepMsBeforeRun: 100,
timeoutMs: 1000,
runParent: (ctx, input) => {
if (value != null) {
return {
output: {
isDone: true,
value,
prevCount: input.prevCount,
} as
| { isDone: false; value: undefined; prevCount: number }
| { isDone: true; value: number; prevCount: number },
}
}
return {
output: {
isDone: false,
value,
prevCount: input.prevCount,
} as
| { isDone: false; value: undefined; prevCount: number }
| { isDone: true; value: number; prevCount: number },
children: [childTask(loopingTask, { prevCount: input.prevCount + 1 })],
}
},
finalize: {
id: 'loopingFinalize',
timeoutMs: 1000,
run: (ctx, { output, children }) => {
if (output.isDone) {
return {
count: output.prevCount + 1,
value: output.value,
}
}
const child = children[0]!
if (child.status !== 'completed') {
throw DurableExecutionError.nonRetryable('Child failed')
}
return child.output as {
count: number
value: number
}
},
},
})
// Input: { prevCount: 0 }
// Output: {
// count: 15, // Can be anywhere between 10 and 20 depending on when tasks are picked
// value: 10,
// }
Sleeping tasks are useful for implementing webhook/event-driven workflows where you need to wait
for external signals. The task remains in a running
state until explicitly woken up via
wakeupSleepingTaskExecution()
with a completion status and output. This pattern is ideal for
integrating with payment providers, approval workflows, or any asynchronous external process.
For most use cases, you should use a parentTask
to set up any processing or background logic that
would wake up the sleeping task and return a sleepingTask
as a child that would be woken up
externally using a webhook or event.
// Specify the type of the output of the sleeping task
const waitForWebhookTask = executor.sleepingTask<string>({
id: 'wait_for_webhook',
timeoutMs: 60 * 60 * 1000, // 1 hour
})
// Use the sleeping task in a parent task
const parentTask = executor.parentTask({
id: 'parent',
timeoutMs: 1000,
runParent: async () => {
// Example API call - replace with your actual implementation
const entityId = await callApiThatSendsWebhookOrEventLater()
return {
output: 'parent_output',
children: [childTask(waitForWebhookTask, entityId)],
}
},
finalize: {
id: 'finalizeTask',
timeoutMs: 1000,
run: (ctx, { children }) => {
const child = children[0]!
if (child.status !== 'completed') {
throw new Error(`Webhook task failed: ${child.error.message}`)
}
return child.output
},
},
})
// Wakeup in a webhook or event handler asynchronously using the unique id and executor
const childExecution = await executor.wakeupSleepingTaskExecution(
waitForWebhookTask,
'entity_id',
{
status: 'completed',
output: 'webhook_output',
},
)
// Input: undefined
// Output: 'webhook_output'
Use persistent storage in production.
import {
createPgTaskExecutionsTable,
createPgTaskExecutionsStorage
} from 'durable-execution-storage-drizzle'
import { drizzle } from 'drizzle-orm/node-postgres'
const db = drizzle(process.env.DATABASE_URL!)
const taskExecutionsTable = createPgTaskExecutionsTable()
const storage = createPgTaskExecutionsStorage(db, taskExecutionsTable)
const executor = await DurableExecutor.make(storage)
Run multiple executor instances in different processes or even different machines.
// First executor instance
const executor1 = await DurableExecutor.make(storage, {
maxConcurrentTaskExecutions: 100,
})
// Second executor instance on a beefier machine
const executor2 = await DurableExecutor.make(storage, {
maxConcurrentTaskExecutions: 1000,
})
Lightweight stats are exposed by the executor. Track these periodically to watch throughput and latency of executor and storage.
const runningTaskExecutionsCount = executor.getRunningTaskExecutionsCount()
// 100
const runningTaskExecutionIds = executor.getRunningTaskExecutionIds()
// Set(['task_execution_id_1', 'task_execution_id_2', ...])
const storageMetrics = executor.getStorageMetrics()
// [
// {
// processName: 'insertMany',
// count: 250,
// min: 10,
// max: 25,
// quantiles: [
// [0.5, Option.some(15)],
// [0.9, Option.some(18)],
// [0.95, Option.some(24)]
// ]
// },
// ...
// ]
For a complete diagram of the task execution lifecycle, see DESIGN_DIAGRAM.md.
The following diagram shows the internal state transition of the task execution once it is enqueued till it's run function completes.
flowchart TD
A[Enqueue task]-->B[status=ready<br/>isClosed=false]
B-->C[status=running]
C-->|run function failed| D[status=failed]
C-->|run function timed_out| E[status=timed_out]
C-->|run function completed| F(See the diagram below)
D-->|close| Y[close_status=closing]
E-->|close| Y
Y-->|complete closing| Z[close_status=closed]
The following diagram shows the internal state transition of the task execution once it's run function completes.
flowchart TD
A[Run function completed]-->B{Did task return children?}
B-->|Yes| C[status=waiting_for_children]
C-->|All children completed| D{Does task have finalize?}
D-->|Yes| E[status=waiting_for_finalize]
D-->|No| F[status=completed]
E-->|finalize failed| G[status=finalize_failed]
E-->|finalize completed| F
B-->|No| D
F-->|close| Y[close_status=closing]
G-->|close| Y
Y-->|complete closing| Z[close_status=closed]
Active States (task is being processed):
ready
- Waiting for executor to pick uprunning
- Currently executing run functionwaiting_for_children
- Parent task waiting for children to completewaiting_for_finalize
- Waiting for finalize task to completeTerminal States (execution finished):
completed
- Successfully finished ✅failed
- Execution failed (may be retried) ❌timed_out
- Exceeded timeout limit ⏰finalize_failed
- Parent task finalize function failed ❌cancelled
- Manually cancelled or parent failed 🛑Recovery Mechanisms:
running
state beyond expiresAt
are automatically reset to ready
for retryOnce a task is finished, it goes through a closure process. It happens in the background. These are the steps that happen during the closure process:
finalize
task. If the parent task
has a finalize
task, the parent task is marked as waiting_for_finalize
and the finalize
task is enqueuedfinalize
task, the parent task is marked as completedfinalize
task, the parent task is marked as finalize_failed
If a task is in any non-terminal state, it can be cancelled.
When a task execution is cancelled, the task execution status is marked as cancelled and
the needsPromiseCancellation
field is set to true
. A background process will cancel the
task execution if the needsPromiseCancellation
field is set to true
and the executor was the
one running the task run function. This ensures that if there are multiple durable executors with
the same storage, the cancellation will be propagated to all the durable executors and whichever
durable executor is running the task run function will cancel it.
After cancellation, the closure process happens as described above.
When a task execution status is marked as running, the expiresAt
field is set based on the
timeout of the task plus some leeway. When the expiration background process runs, it will check if
the task execution is still in the running state after the expiration time, and if it is it will be
marked as ready to run again.
This ensures that the task execution is resilient to process failures. If a process never fails during the execution, the task execution will end up in a finished state. Only in the case of a process failure, the task execution will be in running state beyond its timeout.
On shutdown, these happen in this order:
For custom storage implementations, the library provides several utility classes:
TaskExecutionsStorageWithMutex
- Wraps storage to make all operations atomic using a mutex.
Use this if your storage implementation is not natively atomic.TaskExecutionsStorageWithBatching
- Implements batching methods for storage that doesn't
support batch operations natively.import {
TaskExecutionsStorageWithMutex,
TaskExecutionsStorageWithBatching
} from 'durable-execution'
// Wrap a non-atomic storage
const atomicStorage = new TaskExecutionsStorageWithMutex(myStorage)
// Wrap a storage without batch support
const batchingStorage = new TaskExecutionsStorageWithBatching(myStorage)
For effect users, the library provides first-class effect support:
makeEffectDurableExecutor
- Creates an effect-based executorEffectDurableExecutor
- Type for the effect durable executorEffectDurableExecutorOptions
- Configuration optionsimport { Effect } from 'effect'
import { makeEffectDurableExecutor } from 'durable-execution'
const program = Effect.gen(function* () {
const executor = yield* makeEffectDurableExecutor({
maxConcurrentTaskExecutions: 100
})
const task = yield* executor.task({
id: 'effectTask',
timeoutMs: 30_000,
run: (ctx, input) => Effect.succeed(`Hello ${input}!`)
})
const handle = yield* executor.enqueueTask(task, 'world')
const result = yield* handle.waitAndGetFinishedExecution()
return result
})
The library exports several error types and status constants for advanced error handling:
import {
// Error types
DurableExecutionError,
DurableExecutionNotFoundError,
DurableExecutionTimedOutError,
DurableExecutionCancelledError,
// Status constants
ALL_TASK_EXECUTION_STATUSES,
ACTIVE_TASK_EXECUTION_STATUSES,
FINISHED_TASK_EXECUTION_STATUSES,
ERRORED_TASK_EXECUTION_STATUSES,
// Storage status types
type TaskExecutionStatus,
type TaskExecutionCloseStatus,
type TaskExecutionOnChildrenFinishedProcessingStatus
} from 'durable-execution'
import {
DurableExecutionError,
DurableExecutionNotFoundError,
DurableExecutionCancelledError
} from 'durable-execution'
const apiTask = executor.task({
id: 'api-call',
run: async (ctx, input: { url: string }) => {
try {
const response = await fetch(input.url)
if (response.status === 404) {
// Resource doesn't exist - don't retry
throw new DurableExecutionNotFoundError(
`Resource not found: ${input.url}`,
)
// OR
throw DurableExecutionError.nonRetryable(
`Resource not found: ${input.url}`,
)
}
if (response.status === 400) {
// Bad request - client error, don't retry
throw DurableExecutionError.nonRetryable(
`Invalid request to ${input.url}`,
)
}
if (response.status >= 500) {
// Server error - might be transient, retry
throw DurableExecutionError.retryable(
`Server error from ${input.url}: ${response.status}`,
)
}
if (response.status === 429) {
// Rate limited - retry with backoff
throw DurableExecutionError.retryable(
`Rate limited by ${input.url}`,
)
}
const data = await response.json()
if (data.error) {
// Custom cancellation - throw this error to mark the task as cancelled
throw new DurableExecutionCancelledError(data.error)
}
return await response.json()
} catch (error) {
if (error instanceof DurableExecutionError) {
throw error // Re-throw our custom errors
}
// Network errors, timeouts, etc. - usually retryable
throw DurableExecutionError.retryable(
`Network error calling ${input.url}`,
{ cause: error }
)
}
}
})
import { DurableExecutionError } from 'durable-execution'
const batchProcessingTask = executor.parentTask({
id: 'batch-processing',
runParent: async (ctx, input: { batchItems: Array<string> }) => {
// Process items one by one
return {
output: undefined,
children: input.batchItems.map((item, index) =>
childTask(processItemTask, { item, index })
),
}
},
finalize: async (ctx, input) => {
const { output, children } = input
// Separate successful and failed children
const successful = children.filter(child => child.status === 'completed')
const cancelled = children.filter(child => child.status === 'cancelled')
const failed = children.filter(child => child.status !== 'completed' && child.status !== 'cancelled')
// Log results for monitoring
console.log(`Batch processing completed: ${successful.length} succeeded, ${cancelled.length} cancelled, ${failed.length} failed`)
// Different error handling strategies:
// 1. Fail if ANY child failed (strict)
if (failed.length > 0) {
throw DurableExecutionError.nonRetryable(
`Batch processing failed: ${failed.length} items failed`,
)
}
// 2. Fail only if more than 50% failed (tolerance-based)
// if (failed.length > children.length / 2) {
// throw DurableExecutionError.nonRetryable(
// `Too many failures: ${failed.length}/${children.length}`
// )
// }
// 3. Always succeed but report partial results (best-effort)
// return {
// successful: successful.map(s => s.output),
// failed: failed.length,
// total: children.length
// }
// Return successful results
return {
results: successful.map(child => child.output),
processedCount: successful.length,
cancelledCount: cancelled.length,
failedCount: failed.length
}
}
})
async function attemptApi(url: string) {
const response = await fetch(url)
if (!response.ok) {
throw new Error(`HTTP ${response.status}: ${response.statusText}`)
}
return response.json()
}
const resilientApiTask = executor.task({
id: 'resilient-api-call',
retryOptions: {
maxAttempts: 5,
baseDelayMs: 1000,
delayMultiplier: 2,
maxDelayMs: 30_000
},
run: async (ctx, input: { url: string, fallbackUrl?: string }) => {
try {
// Try primary URL
return await attemptApi(input.url)
} catch (primaryError) {
// If we have a fallback and this is our last attempt
if (input.fallbackUrl && ctx.attempt >= 3) {
try {
console.log(`Primary URL failed, trying fallback: ${input.fallbackUrl}`)
return await attemptApi(input.fallbackUrl)
} catch (fallbackError) {
// Both failed - provide detailed error
throw DurableExecutionError.nonRetryable(
`Both primary and fallback URLs failed`,
{
cause: {
primary: primaryError,
fallback: fallbackError
}
}
)
}
}
// Retry with primary URL
throw DurableExecutionError.retryable(
`API call failed (attempt ${ctx.attempt}/${ctx.maxAttempts})`,
{ cause: primaryError }
)
}
}
})
For custom serialization needs:
If you are using a custom serializer, you must ensure that the serializer can handle all the types that are used in the task inputs and outputs.
import { createSuperjsonSerializer, type Serializer } from 'durable-execution'
// Use the default serializer
const defaultSerializer = createSuperjsonSerializer()
// Create a custom serializer
const customSerializer: Serializer = {
serialize: <T>(value: T) => JSON.stringify(value),
deserialize: <T>(str: string) => JSON.parse(str) as T
}
This project is licensed under the MIT License. See the LICENSE file for details.