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0.22.0-alpha.5 • Public • Published

Zeebe Node.js Client

License CircleCI

This is a Node.js gRPC client for Zeebe. It is written in TypeScript and transpiled to JavaScript in the dist directory.

Comprehensive API documentation is available online.

See to see what has changed with each release.

Docker-compose configurations for Zeebe are available at


To enable that the client libraries can be easily supported to the Zeebe server we map the version numbers, so that Major, Minor match the server application. Patches are independent and indicate client updates.

NPM Package version 0.22.x supports Zeebe 0.22.x

NPM Package version 0.21.x supports Zeebe 0.21.x

NPM Package version 0.20.x supports Zeebe 0.20.x

NPM Package version 0.19.x supports Zeebe 0.19.x

NPM Package version 2.x.x supports Zeebe 0.18.

NPM Package version 1.x.x supports Zeebe 0.15/0.16.

Type difference from other Zeebe clients

Protobuf fields of type int64 are serialised as type string in the Node library. These fields are serialised as numbers (long) in the Go and Java client. See grpc/#7229 for why the Node library serialises them as string. The Workflow instance key, and other fields that are of type long in other client libraries, are type string in this library. Fields of type int32 are serialised as type number in the Node library.

Scaffolding code from a BPM file

You can scaffold your worker code from a BPMN file with the bin/zeebe-node-cli command. Pass in the path to the BPMN file, and it will produce a file to implement it.

Example Use

Add the Library to your Project

npm i zeebe-node

Get Broker Topology

const ZB = require('zeebe-node')
;(async () => {
    const zbc = new ZB.ZBClient('localhost:26500')
    const topology = await zbc.topology()
    console.log(JSON.stringify(topology, null, 2))

Deploy a workflow

const ZB = require('zeebe-node')
const fs = require('fs')
;(async () => {
    const zbc = new ZB.ZBClient() // localhost:26500 || ZEEBE_GATEWAY_ADDRESS
    const res = await zbc.deployWorkflow('./domain-mutation.bpmn')
    // Deploy multiple with an array of filepaths
    await zbc.deployWorkflow(['./wf1.bpmn', './wf2.bpmn'])
    const buffer = fs.readFileSync('./wf3.bpmn')
    // Deploy from an in-memory buffer
    await zbc.deployWorkflow({ definition: buffer, name: 'wf3.bpmn' })

Client-side gRPC retry in ZBClient

If a gRPC command method fails in the ZBClient - such as ZBClient.deployWorkflow or ZBClient.topology(), the underlying gRPC library will throw an exception.

If no workers have been started, this can be fatal to the process if it is not handled by the application logic. This is especially an issue when a worker container starts before the Zeebe gRPC gateway is available to service requests, and can be inconsistent as this is a race condition.

To mitigate against this, the Node client implements some client-side gRPC operation retry logic by default. This can be configured, including disabled, via configuration in the client constructor.

  • Operations retry, but only for gRPC error codes 8 and 14 - indicating resource exhaustion (8) or transient network failure (14). Resource exhaustion occurs when the broker starts backpressure due to latency because of load. Network failure can be caused by passing in an unresolvable gateway address (14: DNS Resolution failed), or by the gateway not being ready yet (14: UNAVAILABLE: failed to connect to all addresses).
  • Operations that fail for other reasons, such as deploying an invalid bpmn file or cancelling a workflow that does not exist, do not retry.
  • Retry is enabled by default, and can be disabled by passing { retry: false } to the client constructor.
  • maxRetries and maxRetryTimeout are also configurable through the constructor options. By default, if not supplied, the values are:
const zbc = new ZB.ZBClient(gatewayAddress, {
    retry: true,
    maxRetries: 50,
    maxRetryTimeout: 5000

Retry is provided by promise-retry, and the back-off strategy is simple ^2.

Additionally, the gRPC Client will continually reconnect when in a failed state, such as when the gateway goes away due to pod rescheduling on Kubernetes.

onReady(), onConnectionError(), and connected

The client has a connected property that can be examined to determine if it has a gRPC connection to the gateway.

The client and the worker can take an optional onReady() and onConnectionError() handler in their options, like this:

const zbc = new ZB.ZBClient({
    onReady: () => console.log(`Connected!`),
    onConnectionError: () => console.log(`Disconnected!`)
const zbWorker = zbc.createWorker(
        onReady: () => console.log(`Worker connected!`),
        onConnectionError: () => console.log(`Worker disconnected!`)

These handlers are called whenever the gRPC channel is established or lost. As the channel will jitter when it is lost, there is a connectionTolerance property that determines how long the connection must be in a connected or failed state before the handler is called. By default this is 3000ms. You can specify another value like this:

const zbc = new ZB.ZBClient({
    onReady: () => console.log(`Connected!`),
    onConnectionError: () => console.log(`Disconnected!`),
    connectionTolerance: 5000
const zbWorker = zbc.createWorker(
        onReady: () => console.log(`Worker connected!`),
        onConnectionError: () => console.log(`Worker disconnected!`),
        connectionTolerance: 35000


The Node client does not use TLS by default.

Enable a secure connection by setting useTLS: true:

const zbc = new ZB.ZBClient(tlsProxiedGatewayAddress, {
    useTLS: true,

Via environment variable:



In case you need to connect to a secured endpoint with OAuth, you can pass in OAuth credentials. This will enable TLS (unless you explicitly disable it with useTLS: false), and handle the OAuth flow to get / renew a JWT:

const zbc = new ZB.ZBClient("", {
    oAuth: {
        url: "https://your-auth-endpoint/oauth/token",
        audience: "",
        clientId: "myClientId",
        cacheOnDisk: true

The cacheOnDisk option will cache the token on disk in $HOME/.camunda, which can be useful in development if you are restarting the service frequently, or are running in a serverless environment, like AWS Lambda.

If the cache directory is not writable, the ZBClient constructor will throw an exception. This is considered fatal, as it can lead to denial of service or hefty bills if you think caching is on when it is not.

Basic Auth

If you put a proxy in front of the broker with basic auth, you can pass in a username and password:

const zbc = new ZB.ZBClient("", {
    basicAuth: {
        username: "user1",
        password: "secret",
    useTLS: true

Basic Auth will also work without TLS.

Camunda Cloud

You can connect to Camunda Cloud by using the camundaCloud configuration option, using the clusterId, clientSecret, and clientId from the Camunda Cloud Console, like this:

const zbc = new ZB.ZBClient({
    camundaCloud: {

That's it! Under the hood, the client lib will construct the OAuth configuration for Camunda Cloud and set the gateway address and port for you.

Zero-Conf constructor

The ZBClient has a 0-parameter constructor that takes the config from the environment. This is useful for injecting secrets into your app via the environment, and switching between development and production environments with no change to code.

To use the zero-conf constructor, you create the client like this:

const zbc = new ZBClient()

With no relevant environment variables set, it will default to localhost on the default port with no TLS.

The following environment variable configurations are possible with the Zero-conf constructor:

Camunda Cloud:


Self-hosted or local broker (no TLS or OAuth):


Self-hosted or local broker with OAuth + TLS:


Basic Auth:


Create a Task Worker

const ZB = require('zeebe-node')
const zbc = new ZB.ZBClient('localhost:26500')
const zbWorker = zbc.createWorker(null, 'demo-service', handler)
function handler(job, complete) {
    console.log('Task variables', job.variables)
    // Task worker business logic goes here
    const updateToBrokerVariables = {
        updatedProperty: 'newValue',

Here is an example job:

{ key: '578',
  type: 'demo-service',
   { workflowInstanceKey: '574',
     bpmnProcessId: 'test-process',
     workflowDefinitionVersion: 1,
     workflowKey: '3',
     elementId: 'ServiceTask_0xdwuw7',
     elementInstanceKey: '577' },
  customHeaders: '{}',
  worker: 'test-worker',
  retries: 3,
  deadline: '1546915422636',
  variables: { testData: 'something' } }

The worker can be configured with options. Shown below are the defaults that apply if you don't supply them:

const workerOptions = {
    maxActiveJobs: 32, // the number of simultaneous tasks this worker can handle
    timeout: 1000, // the maximum amount of time the broker should allow this worker to complete a task
const onConnectionError = err => console.log(err) // Called when the connection to the broker cannot be established, or fails
const zbWorker = zbc.createWorker(

Unhandled Exceptions in Task Handlers

When a task handler throws an unhandled exception, the library will fail the job. Zeebe will then retry the job according to the retry settings of the task. Sometimes you want to halt the entire workflow so you can investigate. To have the library cancel the workflow on an unhandled exception, pass in {failWorkflowOnException: true} to the createWorker call:

zbc.createWorker('test-worker', 'console-log', maybeFaultyHandler, {
    failWorkflowOnException: true,

Completing tasks with success or failure

To complete a task, the task worker handler function receives a complete parameter. The complete object has a success and a failure method.

Call complete.success() passing in a optional plain old JavaScript object (POJO) - a key:value map. These are variable:value pairs that will be used to update the workflow state in the broker. They will be merged with existing values. You can set an existing key to null or undefined, but there is no way to delete a key.

Call complete.failure() to fail the task. You must pass in a string message describing the failure. The client library decrements the retry count, and the broker handles the retry logic. If the failure is a hard failure and should cause an incident to be raised in Operate, then pass in 0 for the optional second parameter, retries:

complete.failure('This is a critical failure and will raise an incident', 0)

Long polling

With Zeebe 0.21 onward, long polling is supported for clients, and is used by default. Rather than polling continuously for work and getting nothing back, a client can poll once and leave the request open until work appears. This reduces network traffic and CPU utilization in the server. Every JobActivation Request is appended to the event log, so continuous polling can significantly impact broker performance, especially when an exporter is loaded (see here).

The default long polling period is 60000ms (60s).

To use a different long polling period, pass in a long poll timeout in milliseconds to the client. All workers created with that client will use it. Alternatively, set a period per-worker.

Long polling for workers is configured in the ZBClient like this:

const zbc = new ZBClient('serverAddress', {
    longPoll: 600000, // Ten minutes in millis - inherited by workers
const longPollingWorker = zbc.createWorker(null, 'task-type', handler, {
    longPoll: 120000, // override client, poll 2m

Start a Workflow Instance

const ZB = require('zeebe-node')
;(async () => {
    const zbc = new ZB.ZBClient('localhost:26500')
    const result = await zbc.createWorkflowInstance('test-process', {
        testData: 'something',

Example output:

{ workflowKey: '3',
  bpmnProcessId: 'test-process',
  version: 1,
  workflowInstanceKey: '569' }

Start a Workflow Instance of a specific version of a Workflow definition

From version 0.22 of the client onward:

const ZB = require('zeebe-node')
;(async () => {
    const zbc = new ZB.ZBClient('localhost:26500')
    const result = await zbc.createWorkflowInstance({
        bpmnProcessId: 'test-process',
        variables: {
            testData: 'something',
        version: 5,

Start a workflow instance and await the workflow outcome

From version 0.22 of the broker and client:

const result = await zbc.createWorkflowInstanceWithResult(processId, {
    sourceValue: 5,

Overriding the gateway's default timeout for a workflow that needs more time to complete:

const result = await zbc.createWorkflowInstanceWithResult({
    bpmnProcessId: processId,
    variables: {
        sourceValue: 5,
        otherValue: 'rome',
    requestTimeout: 25000,

Publish a Message

const zbc = new ZB.ZBClient('localhost:26500')
    correlationKey: 'value-to-correlate-with-workflow-variable',
    messageId: uuid.v4(),
    name: 'message-name',
    variables: { valueToAddToWorkflowVariables: 'here', status: 'PROCESSED' },
    timeToLive: 10000,

You can also publish a message targeting a Message Start Event. In this case, the correlation key is optional, and all Message Start events that match the name property will receive the message.

You can use the publishStartMessage() method to publish a message with no correlation key (it will be set to a random uuid in the background):

const zbc = new ZB.ZBClient('localhost:26500')
    messageId: uuid.v4(),
    name: 'message-name',
    variables: { initialWorkflowVariable: 'here' },
    timeToLive: 10000,

Both normal messages and start messages can be published idempotently by setting both the messageId and the correlationKey. They will only ever be correlated once. See: A message can be published idempotent.

Graceful Shutdown

To drain workers, call the close() method of the ZBClient. This causes all workers using that client to stop polling for jobs, and returns a Promise that resolves when all active jobs have either finished or timed out.

console.log('Closing client...')
zbc.close().then(() => console.log('All workers closed'))

Generating TypeScript constants for BPMN Processes

Message names and Task Types are untyped magic strings. You can generate type information to avoid some classes of errors.

0.22.0-alpha.5 and above

Install the package globally:

npm i -g zeebe-node

Now you have the command zeebe-node <filename> that parses a BPMN file and emits type definitions.

All versions

The BpmnParser class provides a static method generateConstantsForBpmnFiles(). This method takes a filepath and returns TypeScript definitions that you can use to avoid typos in your code, and to reason about the completeness of your task worker coverage.

const ZB = require('zeebe-node')
;(async () => {
    console.log(await ZB.BpmnParser.generateConstantsForBpmnFiles(workflowFile))

This will produce output similar to:

// Autogenerated constants for msg-start.bpmn
export enum TaskType = {
    CONSOLE_LOG = "console-log"
export enum MessageName = {


Control the log output for the client library by setting the ZBClient log level. Valid log levels are NONE (supress all logging), ERROR (log only exceptions), INFO (general logging), or DEBUG (verbose logging). You can set this in the client constructor:

const zbc = new ZBClient('localhost', { loglevel: 'DEBUG' })

And also via the environment:


By default the library uses and console.error for logging. You can also pass in a custom logger, such as pino:

const logger = require('pino')()
const zbc = new ZBClient('', { stdout: logger })


The source is written in TypeScript in src, and compiled to ES6 in the dist directory.

To build:

npm run build

To start a watcher to build the source and API docs while you are developing:

npm run dev


Tests are written in Jest, and live in the src/__tests__ directory. To run the unit tests:

npm t

Integration tests are in the src/__tests__/integration directory.

They require a Zeebe broker to run. You can run them using the Circle CI CLI:

circleci local execute -c .circleci/config.yml --job test

Or you can start a dockerised broker:

cd docker
docker-compose up

And then run them manually:

npm run test:integration

For the failure test, you need to run Operate (docker-compose config) and manually verify that an incident has been raised at http://localhost:8080.

Writing Tests

Zeebe is inherently stateful, so integration tests need to be carefully isolated so that workers from one test do not service tasks in another test. Jest runs tests in a random order, so intermittent failures are the outcome of tests that mutate shared state.

For each feature:

  • Use a unique bpmn process, named the same as the test file. Don't reuse processes between tests, because they are tightly coupled.
  • Name the task types with a namespace that matches the test name. This avoids workers from one test servicing tasks from another test, which causes unpredictable behaviour.
  • Cancel any workflows that do not run to completion in an AfterAll or AfterEach block. This avoids subsequent test runs interacting with workflows from a previous test run.
  • Ensure that there no Active workflows in the engine after running the integration tests have run. This manual check is to verify that there is no left-over state. (Note one exception: the Raise Incident test leaves the workflow open for manual verification in Operate).


Josh Wulf
Colin Raddatz
Jarred Filmer
Timothy Colbert
Olivier Albertini
Patrick Dehn


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