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README.adoc

MQTT Kafka tracker

Built based on Simon Aubury’s excellent example, all credit and thanks to Simon for this.

mqtt kafka 01

For demo script see here

kibana01

  • Install Owntracks on your phone

  • Owntracks sends data to MQTT server

  • Kafka Connect ingests MQTT into Kafka topic

  • ksqlDB parses and transforms the data for analysis

  • Kafka Connect streams the data to Elasticsearch

  • Kibana does nice visualisation of the data

1. Pre-requisites

1.1. MQTT

  1. You’ll need an MQTT server; https://www.cloudmqtt.com is very easy to setup and no credit card required for entry-level tier. From your MQTT server you need:

    • Hostname

    • Port

    • Username

    • Password

Tip: MQTT Explorer is a useful tool.

1.2. OwnTracks

  1. Download Owntracks to your phone. Click the ℹ️ icon in the top left and configure the MQTT settings.

  2. On your MQTT server (e.g. CloudMQTT’s WebSocket UI view) you should see messages arriving

1.3. Option 1 : Cloud

In this approach you use Confluent Cloud and Elastic Cloud as fully managed services. The only thing you have to run is a Kafka Connect worker, which is shown here done under Docker, but there are also link::ec2_notes.adoc[notes here on deploying it on EC2].

Create a local .env file and enter into it your details from Confluent Cloud along with your details of your MQTT server and Elasticsearch instance.

CCLOUD_BROKER_HOST=
CCLOUD_API_KEY=
CCLOUD_API_SECRET=
CCLOUD_SCHEMA_REGISTRY_URL=
CCLOUD_SCHEMA_REGISTRY_API_KEY=
CCLOUD_SCHEMA_REGISTRY_API_SECRET=

ELASTIC_URL=
ELASTIC_USERNAME=
ELASTIC_PASSWORD=

CONFLUENTPLATFORM_VERSION=5.4.0-beta1

MQTT_USERNAME=
MQTT_PASSWORD=
MQTT_URL=

Make sure you’ve got Docker/Docker Compose and then run:

docker-compose -f docker-compose_ccloud.yml up -d

1.4. Option 2 : Local

In this approach you run the full Confluent Platform and Elastic stack locally, through Docker.

Create a local .env file and enter into it your details of your MQTT server. You can leave the Elasticsearch details as they are.

CONFLUENTPLATFORM_VERSION=5.4.0-beta1

ELASTIC_URL=http://elasticsearch:9200
ELASTIC_USERNAME=dummy
ELASTIC_PASSWORD=dummy

MQTT_USERNAME=
MQTT_PASSWORD=
MQTT_URL=

Make sure you’ve got Docker/Docker Compose and then run:

docker-compose -f up -d

2. Configuration

2.1. Kafka Connect MQTT Source

Depending on whether you are sending data up to Confluent Cloud or to a local Kafka broker run :

  • Confluent Cloud

    ./create_mqtt_source_ccloud.sh
  • Local

    ./create_mqtt_source_local.sh

2.2. ksqlDB

With data flowing in, now it’s time to build your stream processing apps! The ksqlDB applications apply a schema to the data, set the data types, and extract fields such as the device/sender ID.

  • Confluent Cloud - launch the ksqlDB page, and paste in the contents of the mqtt.ksql file.

  • Local

    • Run ksqlDB CLI

      docker exec -it ksqldb-cli bash -c 'echo -e "\n\n⏳ Waiting for ksqlDB to be available before launching CLI\n"; while : ; do curl_status=$(curl -s -o /dev/null -w %{http_code} http://ksqldb-server:8088/info) ; echo -e $(date) " ksqlDB server listener HTTP state: " $curl_status " (waiting for 200)" ; if [ $curl_status -eq 200 ] ; then  break ; fi ; sleep 5 ; done ; ksql http://ksqlDB-server:8088'
    • Run script

      RUN SCRIPT '/data/mqtt.ksql';

2.3. Kafka Connect Elasticsearch sink

Depending on whether you are sending data up to Confluent Cloud or to a local Kafka broker run :

  • Confluent Cloud

    ./create_mqtt_source_ccloud.sh
  • Local

    ./create_mqtt_source_local.sh

2.4. Kafka Connect Elasticsearch sink

  1. You need to create an Elasticsearch dynamic mapping template so that geopoint fields and dates are correctly picked up.

    If running using Docker Compose this has already been done for you. If using a hosted Elasticsearch then run :

    ./create_es_dynamic_mapping.sh
  2. Create the sink connectors. There are two because the key.ignore value is different between them (otherwise they could be combined into one and use a topics list or topics.regex):

    ./create_es_sink.sh

    Check connector status:

    curl -s "http://localhost:8083/connectors?expand=info&expand=status" | \
               jq '. | to_entries[] | [ .value.info.type, .key, .value.status.connector.state,.value.status.tasks[].state,.value.info.config."connector.class"]|join(":|:")' | \
               column -s : -t| sed 's/\"//g'| sort
    sink    |  sink-elastic-runner_location-00  |  RUNNING  |  RUNNING  |  io.confluent.connect.elasticsearch.ElasticsearchSinkConnector
    sink    |  sink-elastic-runner_status-00    |  RUNNING  |  RUNNING  |  io.confluent.connect.elasticsearch.ElasticsearchSinkConnector
    source  |  source-mqtt-01                   |  RUNNING  |  RUNNING  |  io.confluent.connect.mqtt.MqttSourceConnector
  3. Check data is arriving in Elasticsearch:

    $ curl "http://localhost:9200/_cat/indices/runn*?h=idx,docsCount"
    runner_status     0
    runner_location 237

    (For Elastic Cloud just add -u user:password to the curl call before the URL)

3. Footnote - Sync data from Confluent Cloud to local Kafka brokers

You can use Confluent Replicator to stream the contents of a topic (or topics) between Kafka clusters, including between on-premises Kafka and Confluent Cloud. This could be useful if you wanted a copy of the data on a local environment to use whilst not connected to Confluent Cloud (e.g. whilst on ✈️)

In the docker-compose.yml is a container for replicator. Make sure that this is running, and then run

./create_replicator_source.sh

This runs on the local stack and pulls down messages from the Confluent Cloud topic(s) specified. Note that three brokers are run as part of the docker-compose.yml because Replicator creates topics with the same config as on the source (and Confluent Cloud has replication factor=3)

Check the status:

curl -s "http://localhost:58083/connectors?expand=info&expand=status" | \
         jq '. | to_entries[] | [ .value.info.type, .key, .value.status.connector.state,.value.status.tasks[].state,.value.info.config."connector.class"]|join(":|:")' | \
         column -s : -t| sed 's/\"//g'| sort
source  |  replicator-source   |  RUNNING  |  RUNNING  |  io.confluent.connect.replicator.ReplicatorSourceConnector
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