Run Worker processes - TypeScript SDK
How to run Worker Processes
The Worker Process is where Workflow Functions and Activity Functions are executed.
- Each Worker Entity in the Worker Process must register the exact Workflow Types and Activity Types it may execute.
- Each Worker Entity must also associate itself with exactly one Task Queue.
- Each Worker Entity polling the same Task Queue must be registered with the same Workflow Types and Activity Types.
A Worker Entity is the component within a Worker Process that listens to a specific Task Queue.
Although multiple Worker Entities can be in a single Worker Process, a single Worker Entity Worker Process may be perfectly sufficient. For more information, see the Worker tuning guide.
A Worker Entity contains a Workflow Worker and/or an Activity Worker, which makes progress on Workflow Executions and Activity Executions, respectively.
How to run a Worker on Docker in TypeScript
To improve worker startup time, we recommend preparing workflow bundles ahead-of-time. See our productionsample for details.
Workers based on the TypeScript SDK can be deployed and run as Docker containers.
We recommend an LTS Node.js release such as 18, 20, 22, or 24. Both amd64 and arm64 architectures are supported. A
glibc-based image is required; musl-based images are not supported (see below).
The easiest way to deploy a TypeScript SDK Worker on Docker is to start with the node:20-bullseye image. For example:
FROM node:20-bullseye
# For better cache utilization, copy package.json and lock file first and install the dependencies before copying the
# rest of the application and building.
COPY . /app
WORKDIR /app
# Alternatively, run npm ci, which installs only dependencies specified in the lock file and is generally faster.
RUN npm install --only=production \
&& npm run build
CMD ["npm", "start"]
For smaller images and/or more secure deployments, it is also possible to use -slim Docker image variants (like
node:20-bullseye-slim) or distroless/nodejs Docker images (like gcr.io/distroless/nodejs20-debian11) with the
following caveats.
Using node:slim images
node:slim images do not contain some of the common packages found in regular images. This results in significantly
smaller images.
However, TypeScript SDK requires the presence of root TLS certificates (the ca-certificates package), which are not
included in slim images. The ca-certificates package is required even when connecting to a local Temporal Server or
when using a server connection config that doesn't explicitly use TLS.
For this reason, the ca-certificates package must be installed during the construction of the Docker image. For
example:
FROM node:20-bullseye-slim
RUN apt-get update \
&& apt-get install -y ca-certificates \
&& rm -rf /var/lib/apt/lists/*
# ... same as with regular image
Failure to install this dependency results in a [TransportError: transport error] runtime error, because the
certificates cannot be verified.
Using distroless/nodejs images
distroless/nodejs images include only the files that are strictly required to execute node. This results in even
smaller images (approximately half the size of node:slim images). It also significantly reduces the surface of
potential security issues that could be exploited by a hacker in the resulting Docker images.
It is generally possible and safe to execute TypeScript SDK Workers using distroless/nodejs images (unless your code
itself requires dependencies that are not included in distroless/nodejs).
However, some tools required for the build process (notably the npm command) are not included in the
distroless/nodejs image. This might result in various error messages during the Docker build.
The recommended solution is to use a multi-step Dockerfile. For example:
# -- BUILD STEP --
FROM node:20-bullseye AS builder
COPY . /app
WORKDIR /app
RUN npm install --only=production \
&& npm run build
# -- RESULTING IMAGE --
FROM gcr.io/distroless/nodejs20-debian11
COPY /app /app
WORKDIR /app
CMD ["node", "build/worker.js"]
Properly configure Node.js memory in Docker
By default, node configures its maximum old-gen memory to 25% of the physical memory of the machine on which it is
executing, with a maximum of 4 GB. This is likely inappropriate when running Node.js in a Docker environment and can
result in either underusage of available memory (node only uses a fraction of the memory allocated to the container)
or overusage (node tries to use more memory than what is allocated to the container, which will eventually lead to the
process being killed by the operating system).
Therefore we recommended that you always explicitly set the --max-old-space-size node argument to approximately 80%
of the maximum size (in megabytes) that you want to allocate the node process. You might need some experimentation and
adjustment to find the most appropriate value based on your specific application.
In practice, it is generally easier to provide this argument through the
NODE_OPTIONS environment variable.
Do not use Alpine
Alpine replaces glibc with musl, which is incompatible with the Rust core of the TypeScript SDK. If you receive errors like the following, it's probably because you are using Alpine.
Error: Error loading shared library ld-linux-x86-64.so.2: No such file or directory (needed by /opt/app/node_modules/@temporalio/core-bridge/index.node)
Or like this:
Error: Error relocating /opt/app/node_modules/@temporalio/core-bridge/index.node: __register_atfork: symbol not found
How to run a Temporal Cloud Worker
To run a Worker that uses Temporal Cloud, you need to provide additional connection and client options that include the following:
- An address that includes your Cloud Namespace Name and a port number:
<Namespace>.<ID>.tmprl.cloud:<port>. - mTLS CA certificate.
- mTLS private key.
For more information about managing and generating client certificates for Temporal Cloud, see How to manage certificates in Temporal Cloud.
For more information about configuring TLS to secure inter- and intra-network communication for a Temporal Service, see Temporal Customization Samples.
How to register types
All Workers listening to the same Task Queue name must be registered to handle the exact same Workflows Types and Activity Types.
If a Worker polls a Task for a Workflow Type or Activity Type it does not know about, it fails that Task. However, the failure of the Task does not cause the associated Workflow Execution to fail.
In development, use
workflowsPath:
import { Worker } from '@temporalio/worker';
import * as activities from './activities';
async function run() {
const worker = await Worker.create({
workflowsPath: require.resolve('./workflows'),
taskQueue: 'snippets',
activities,
});
await worker.run();
}
In this snippet, the Worker bundles the Workflow code at runtime.
In production, you can improve your Worker's startup time by bundling in advance: as part of your production build, call
bundleWorkflowCode:
production/src/scripts/build-workflow-bundle.ts
import { bundleWorkflowCode } from '@temporalio/worker';
import { writeFile } from 'fs/promises';
import path from 'path';
async function bundle() {
const { code } = await bundleWorkflowCode({
workflowsPath: require.resolve('../workflows'),
});
const codePath = path.join(__dirname, '../../workflow-bundle.js');
await writeFile(codePath, code);
console.log(`Bundle written to ${codePath}`);
}
Then the bundle can be passed to the Worker:
const workflowOption = () =>
process.env.NODE_ENV === 'production'
? {
workflowBundle: {
codePath: require.resolve('../workflow-bundle.js'),
},
}
: { workflowsPath: require.resolve('./workflows') };
async function run() {
const worker = await Worker.create({
...workflowOption(),
activities,
taskQueue: 'production-sample',
});
await worker.run();
}
How to shut down a Worker and track its state
Workers shut down if they receive any of the Signals enumerated in
shutdownSignals: 'SIGINT',
'SIGTERM', 'SIGQUIT', and 'SIGUSR2'.
In development, we shut down Workers with Ctrl+C (SIGINT) or
nodemon
(SIGUSR2). In production, you usually want to give Workers time to finish any in-progress Activities by setting
shutdownGraceTime.
As soon as a Worker receives a shutdown Signal or request, the Worker stops polling for new Tasks and allows in-flight
Tasks to complete until shutdownGraceTime is reached. Any Activities that are still running at that time will stop
running and will be rescheduled by Temporal Server when an Activity timeout occurs.
If you must guarantee that the Worker eventually shuts down, you can set shutdownForceTime.
You might want to programmatically shut down Workers (with Worker.shutdown()) in integration tests or when automating a fleet of Workers.
Worker states
At any time, you can Query Worker state with Worker.getState(). A Worker is always in one of seven states:
INITIALIZED: The initial state of the Worker after calling Worker.create() and successfully connecting to the server.RUNNING: Worker.run() was called and the Worker is polling Task Queues.FAILED: The Worker encountered an unrecoverable error;Worker.run()should reject with the error.- The last four states are related to the Worker shutdown process:
STOPPING: The Worker received a shutdown Signal orWorker.shutdown()was called. The Worker will forcefully shut down aftershutdownGraceTimeexpires.DRAINING: All Workflow Tasks have been drained; waiting for Activities and cached Workflows eviction.DRAINED: All Activities and Workflows have completed; ready to shut down.STOPPED: Shutdown complete;worker.run()resolves.
If you need more visibility into internal Worker state, see the Worker class in the API reference.