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    Apache Kafka to Google Pub/Sub Gateway, API controlled. Helper for Google Cloud Function Services that are built upon Apache Kafka.


    You can manage topics to be transferred on the fly via /api/topic-config and roach-storm will keep track of anything that goes through your Apache Kafka cluster. Messages are filtered and published on Google Cloud Pub/Sub service. It also ships a few additional tools to make the Google Cloud Functions live easier, e.g. handling metrics or producing back to Apache Kafka.


    As of now (Q1 2019) services like Google Cloud Functions do not have the ability to be triggered or integrated into Apache Kafka directly.


    • Node.js >= 9.x.x (we suggest >= 10.11.x)
    • Apache Kafka >= 0.11.x (we suggest >= 1.x.x)
    • MongoDB >= 3.2 (we suggest >= 4.x)


    As simple as yarn global add roach-storm.

    (NOTE: In case you dont have yarn run npm i -g yarn first.)


    roach-storm "./baseConfig.js"

    You just have to throw in a config (JSON or JS). A base config is always used, so you just have to overwrite your specific requirements.

    Check out roach-storm -h for other options.


    With any HTTP client.

    Checkout the API quick start or the setup infos below.

    API Quick Start

    Getting general info about roach-storm and your Kafka clusters

    You can get an overview of possible API actions by calling GET /api/info.

    Configuring Kafka topics for roach-storm

    By default roach-storm, will connect and fetch some information about your Kafka cluster. But it wont start transferring topics/messages yet. You will have to configure topics so that they will be consumed and processed.

    You can do that by providing a small configuraton in a POST /api/config/topic call. You will have to provide the following information in the body { sourceTopic, parseAsJson, pipes }.

    If you configure a topic, it will be consumed from earliest.

    Please note that any changes on the topic-config resource will take a few seconds to be polled and applied to all roach-storm instances.

    Please note that roach-storm will not create PubSub topics for you, you will have to create the topics beforehand.


    • sourceTopic (string) (is required) is the name of the Kafka topic (you can fetch available topics via GET /api/info/topics/available)
    • parseAsJson (boolean) (default is true) if this is false the message (key and value) fields are passed as Buffers
    • pipes (Array[Pipe]) (is required) defines where the kafka messages should be published too, of course you can add multiple pipes for the same topic to filter and publish specific messages to different pubsub topics


    • targetTopic (string) (is required) is the name for the Google PubSub topic where the message should be published to
    • chunkSize (number) (default is 1) the amount of kafka messages (based on topic and partition) to batch into a single pub sub message
    • publishTombstones (boolean) (default is false) if null value kafka messages should be published
    • filter (object) (default is undefined) using this object a filter can be build for a pipe, this way you can publish specific messages to a specific pubsub topic (this can save a lot of costs) as you do not waste function triggers for example:
    Filter Example

    Assume the following messages on your topic: { value: { payload: { eventType: "my-cool-type", version: 5 }}} You can add a filter to a pipe to publish only these certain messages:

    const topicConfig = {
      sourceTopic: "my-topic",
      parseAsJson: true, // please always do this, if you want to use filters on values
      pipes: [
          targetTopic: "pubsub-all-with-version-five",
          chunkSize: 5,
          publishTombstones: false,
          filter: {
            "value.payload.version": 5,
          targetTopic: "pubsub-cool-with-version-six",
          chunkSize: 5,
          publishTombstones: false,
          filter: {
            "value.payload.eventType": "my-cool-type",
            "value.payload.version": 6,

    In this scenario roachstorm will consume the topic my-topic filter out all tombstone messages and publish all kafka messages with payload.version equal to 5 to pubsub topic pubsub-all-with-version-five and at the same time all kafka messages with payload.eventType my-cool-type and payload.version equal to 6 to pubsub topic pubsub-cool-with-version-six.

    Testing filters or producing some test messages to pubsub topics

    You can use the /api/produce/kafka-batch endpoint to easily mimic some kafka messages that are flushed through your configured roach-storm topics and filters and should be published to your configured pubsub topics.

    curl -X POST \
      http://localhost:1919/api/produce/kafka-batch \
      -H 'Authorization: your-roach-storm-token-here' \
      -H 'Content-Type: application/json' \
      -H 'cache-control: no-cache' \
      -d '{
        "batch": {
            "some-kafka-topic": {
                "0": [
                        "topic": "some-kafka-topic",
                        "partition": 0,
                        "key": "cbedcd96-3de5-4649-ba5b-5788cabdb894",
                        "value": {}

    Defining a Bridge from PubSub to Apache Kafka

    roach-storm is also able to move publish events from pubsub topics to Apache Kafka. You can configure a mirror pubsub topic that roach-storm will subscribe to (during start) by setting the config field: pubSubToKafkaTopicName (if you leave it empty or set it to null there will be no mirroring from pubsub to kafka, only from kafka to pubsub).

    The pubsub topic should contain events with data like so: = Buffer.from(JSON.stringify([
        topic: "a-target-kafka-topic", // required
        value: "some value", // if set to null and key is present a tombstone messages will be produced
        key: null, // optional
        partition: null, // optional
      }, // you can pass multiple messages for different topics and partitions in the same pubsub message

    If a produce error occures, roachstorm will not send pubsub acks and the subscription will halt. Errors, writes and acks are exposed via metrics.

    Handling metrics from GCF

    By simply passing the gcf object in the configuration you can easily enable the subcription of a pubsub topic to render prometheus metrics along with a different set of prefixes and labels.

    gcf: {
          metrics: {
              pubSubMetricTopic: null,
              counterLabels: [],
              gaugeLabels: [],
              prefix: "gcf_roach",

    The pubsub topic should contain events with data like so: = Buffer.from(JSON.stringify([
        metric: "my_calls", // the name of the metric
        type: "counter", // counter or gauge
        value: 1, // couter increment by or gauge value set
        labels: { "special": "bla" }, // make sure that these labels (keys) are already set in the config (counterLabels, gaugeLabels)
      }, // you can of course sent multiple metrics per pubsub message

    If an error occures it will be logged and internal metrics will show them, however they will be ignored afterwards and acks will be sent to pubsub.

    Setup Info

    Deployment & Scaling

    roach-storm as process is limited to a single CPU core and does not require too much memory (depending on Kafka consumer configuration) as well. About 0.1 CPU and 150 MB RAM with default configuration can be sufficient.

    But roach-storm is build to scale horizontally, just spin up a few containers (see Dockerfile example) and scale up. In production environments we suggest to have as many instances are the largest amount of partitions configured for a Kafka topic in your cluster.


    You can monitor roach-storm via Prometheus at http://localhost:1919/metrics.

    Access Management

    roach-storm allows fine grained access management with a similiar span of what Kafka ACLs allow you to do on a per topic basis. You define tokens as keys in the configs http access object and set the topic names or special rights as string members of the key's array value. A wildcard * grants all rights.


    const config = {
      http: {
        access: {
          "my-crazy-secure-token-string": [ "__topic", "on-some-topic" ],
          "token-for-some-topics": [ "customers", "baskets", "orders" ],
          "token-for-admin": [ "*" ]

    When making calls to roach-storm's HTTP API the token is provided in the authorization header.

    • * Allows every operation
    • __topic Is allowed to configure topics (only for provided topics)

    Be aware that the default configuration is a wildcard for everything. (Meaning no token is required). Never expose roach-storm's HTTP interface publicly.

    Config via Environment Variables

    It is possible to set a few config parameters (most in role of secrets) via environment variables. They will always overwrite the passed configuration file.

    • MONGODB_URL="mongodb://localhost:27017" -> turns into: config.mongo.url = "mongodb://localhost:27017";
    • MONGODB_USERNAME=admin -> turns into: config.mongo.options.user = "admin";
    • MONGODB_PASSWORD=admin -> turns into: config.mongo.options.pass = "admin";
    • MONGODB_DBNAME=roach_prod -> turns into: config.mongo.options.dbName = "roach_prod";
    • KAFKA_BROKER_LIST=kafka-1:9093,kafka-2:9093 -> turns into: config.kafka.consumer.noptions[""] = "kafka-1:9093";
    • KAFKA_SSL_PASSPHRASE="123456" -> turns into: config.kafka.consumer.noptions["ssl.key.password"] = "123456";
    • KAFKA_SASL_USERNAME="123456" -> turns into: config.kafka.consumer.noptions["sasl.username"] = "123456";
    • KAFKA_SASL_PASSWORD="123456" -> turns into: config.kafka.consumer.noptions["sasl.password"] = "123456";
    • ACL_DEFINITIONS="mytoken=topic1,topic2;othertoken=topic3" roach-storm -l "./config.json" -> turns into: config.http.access.mytoken = [ "topic1", "topic2" ];
    • PUBSUB_PROJECT_ID=my-project-id -> turns into options.pubSubConfig.projectId = "123";

    The kafka env values will set consumer and producer at the same time.


    Christian Fröhlingsdorf @chrisfroeh

    Build with ❤️ 🍕 and ☕️ by nodefluent


    This software is not associated with Google.


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