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Installing ThingsBoard PE using Docker (Linux or Mac OS)

This guide will help you to install and start ThingsBoard Professional Edition (PE) using Docker and Docker Compose on Linux or Mac OS. This guide covers standalone ThingsBoard PE installation. If you are looking for a cluster installation instruction, please visit cluster setup page.

Prerequisites

Install Docker:

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Don’t forget to add your linux user to the docker group. See Manage Docker as a non-root user.

Step 1. Pull ThingsBoard PE Image

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docker pull thingsboard/tb-pe:4.0.0PE

Step 2. Obtain the license key

We assume you have already chosen your subscription plan or decided to purchase a perpetual license. If not, please navigate to pricing page to select the best license option for your case and get your license. See How-to get pay-as-you-go subscription or How-to get perpetual license for more details.

Note: We will reference the license key you have obtained during this step as PUT_YOUR_LICENSE_SECRET_HERE later in this guide.

Step 3. Choose ThingsBoard queue service

ThingsBoard platform currently supports two type of messaging brokers for storing the messages and communication between ThingsBoard services: In-memory and Kafka-based brokers.

  • In Memory queue implementation is built-in and default. It is useful for development(PoC) environments and is not suitable for production deployments or any sort of cluster deployments.

  • Kafka is recommended for production deployments. This queue is used on the most of ThingsBoard production environments now. It is useful for both on-prem and private cloud deployments. It is also useful if you like to stay independent from your cloud provider. However, some providers also have managed services for Kafka. See AWS MSK for example.

  • Confluent Cloud is a fully managed streaming platform based on Kafka. Useful for a cloud agnostic deployments.

See corresponding architecture page and rule engine page for more details.

In Memory (built-in and default)
Kafka (recommended for on-prem, production installations)
Confluent Cloud (Event Streaming Platform based on Kafka)

ThingsBoard includes In Memory Queue service and use it by default without extra settings.

Create docker compose file for ThingsBoard queue service:

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nano docker-compose.yml

Add the following line to the yml file. Don’t forget to replace “PUT_YOUR_LICENSE_SECRET_HERE” with your license secret obtained on the first step:

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version: '3.0'
services:
  mytbpe:
    restart: always
    image: "thingsboard/tb-pe:4.0.0PE"
    ports:
      - "8080:8080"
      - "1883:1883"
      - "7070:7070"
      - "5683-5688:5683-5688/udp"
    environment:
      TB_QUEUE_TYPE: in-memory
      SPRING_DATASOURCE_URL: jdbc:postgresql://postgres:5432/thingsboard
      TB_LICENSE_SECRET: PUT_YOUR_LICENSE_SECRET_HERE
      TB_LICENSE_INSTANCE_DATA_FILE: /data/license.data
    volumes:
      - ~/.mytbpe-data:/data
      - ~/.mytbpe-logs:/var/log/thingsboard
  postgres:
    restart: always
    image: "postgres:15"
    ports:
    - "5432"
    environment:
      POSTGRES_DB: thingsboard
      POSTGRES_PASSWORD: postgres
    volumes:
      - ~/.mytbpe-data/db:/var/lib/postgresql/data

Apache Kafka is an open-source stream-processing software platform.

Create docker compose file for ThingsBoard queue service:

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nano docker-compose.yml

Add the following line to the yml file. Don’t forget to replace “PUT_YOUR_LICENSE_SECRET_HERE” with your license secret obtained on the first step:

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version: '3.2'
services:
  kafka:
    restart: always
    image: bitnami/kafka:3.8.1
    ports:
      - 9092:9092 #to localhost:9092 from host machine
      - 9093 #for Kraft
      - 9094 #to kafka:9094 from within Docker network
    environment:
      ALLOW_PLAINTEXT_LISTENER: "yes"
      KAFKA_CFG_LISTENERS: "OUTSIDE://:9092,CONTROLLER://:9093,INSIDE://:9094"
      KAFKA_CFG_ADVERTISED_LISTENERS: "OUTSIDE://localhost:9092,INSIDE://kafka:9094"
      KAFKA_CFG_LISTENER_SECURITY_PROTOCOL_MAP: "INSIDE:PLAINTEXT,OUTSIDE:PLAINTEXT,CONTROLLER:PLAINTEXT"
      KAFKA_CFG_INTER_BROKER_LISTENER_NAME: "INSIDE"
      KAFKA_CFG_AUTO_CREATE_TOPICS_ENABLE: "false"
      KAFKA_OFFSETS_TOPIC_REPLICATION_FACTOR: "1"
      KAFKA_TRANSACTION_STATE_LOG_MIN_ISR: "1"
      KAFKA_TRANSACTION_STATE_LOG_REPLICATION_FACTOR: "1"
      KAFKA_CFG_PROCESS_ROLES: "controller,broker" #KRaft
      KAFKA_CFG_NODE_ID: "0" #KRaft
      KAFKA_CFG_CONTROLLER_LISTENER_NAMES: "CONTROLLER" #KRaft
      KAFKA_CFG_CONTROLLER_QUORUM_VOTERS: "0@kafka:9093" #KRaft
    volumes:
      - kafka-data:/bitnami
  mytbpe:
    restart: always
    image: "thingsboard/tb-pe:4.0.0PE"
    depends_on:
      - kafka
    ports:
      - "8080:8080"
      - "1883:1883"
      - "7070:7070"
      - "5683-5688:5683-5688/udp"
    environment:
      TB_QUEUE_TYPE: kafka
      SPRING_DATASOURCE_URL: jdbc:postgresql://postgres:5432/thingsboard
      TB_KAFKA_SERVERS: kafka:9094
      TB_LICENSE_SECRET: PUT_YOUR_LICENSE_SECRET_HERE
      TB_LICENSE_INSTANCE_DATA_FILE: /data/license.data
    volumes:
      - ~/.mytbpe-data:/data
      - ~/.mytbpe-logs:/var/log/thingsboard
  postgres:
    restart: always
    image: "postgres:15"
    ports:
    - "5432"
    environment:
      POSTGRES_DB: thingsboard
      POSTGRES_PASSWORD: postgres
    volumes:
      - ~/.mytbpe-data/db:/var/lib/postgresql/data
volumes:
    kafka-data:
      driver: local

Confluent Cloud Configuration

To access Confluent Cloud you should first create an account, then create a Kafka cluster and get your API Key.

Create docker compose file for ThingsBoard queue service:

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nano docker-compose.yml

Add the following line to the yml file. Don’t forget to replace “CLUSTER_API_KEY”, “CLUSTER_API_SECRET” and “confluent.cloud:9092” with your real Confluent Cloud bootstrap servers:

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version: '3.0'
services:
  mytbpe:
    restart: always
    image: "thingsboard/tb-pe:4.0.0PE"
    ports:
      - "8080:8080"
      - "1883:1883"
      - "7070:7070"
      - "5683-5688:5683-5688/udp"
    environment:
      TB_QUEUE_TYPE=kafka
      SPRING_DATASOURCE_URL: jdbc:postgresql://postgres:5432/thingsboard
    
      TB_KAFKA_SERVERS:confluent.cloud:9092
      TB_QUEUE_KAFKA_REPLICATION_FACTOR:3
    
      TB_QUEUE_KAFKA_USE_CONFLUENT_CLOUD:true
      TB_QUEUE_KAFKA_CONFLUENT_SSL_ALGORITHM:https
      TB_QUEUE_KAFKA_CONFLUENT_SASL_MECHANISM:PLAIN
      TB_QUEUE_KAFKA_CONFLUENT_SASL_JAAS_CONFIG:org.apache.kafka.common.security.plain.PlainLoginModule required username="CLUSTER_API_KEY" password="CLUSTER_API_SECRET";
      TB_QUEUE_KAFKA_CONFLUENT_SECURITY_PROTOCOL:SASL_SSL
      TB_QUEUE_KAFKA_CONFLUENT_USERNAME:CLUSTER_API_KEY
      TB_QUEUE_KAFKA_CONFLUENT_PASSWORD:CLUSTER_API_SECRET
    
      TB_QUEUE_KAFKA_RE_TOPIC_PROPERTIES:retention.ms:604800000;segment.bytes:52428800;retention.bytes:1048576000
      TB_QUEUE_KAFKA_CORE_TOPIC_PROPERTIES:retention.ms:604800000;segment.bytes:52428800;retention.bytes:1048576000
      TB_QUEUE_KAFKA_TA_TOPIC_PROPERTIES:retention.ms:604800000;segment.bytes:52428800;retention.bytes:1048576000
      TB_QUEUE_KAFKA_NOTIFICATIONS_TOPIC_PROPERTIES:retention.ms:604800000;segment.bytes:52428800;retention.bytes:1048576000
      TB_QUEUE_KAFKA_JE_TOPIC_PROPERTIES:retention.ms:604800000;segment.bytes:52428800;retention.bytes:104857600

      # These params affect the number of requests per second from each partitions per each queue.
      # Number of requests to particular Message Queue is calculated based on the formula:
      # ((Number of Rule Engine and Core Queues) * (Number of partitions per Queue) + (Number of transport queues)
      #  + (Number of microservices) + (Number of JS executors)) * 1000 / POLL_INTERVAL_MS
      # For example, number of requests based on default parameters is:
      # Rule Engine queues:
      # Main 10 partitions + HighPriority 10 partitions + SequentialByOriginator 10 partitions = 30
      # Core queue 10 partitions
      # Transport request Queue + response Queue = 2
      # Rule Engine Transport notifications Queue + Core Transport notifications Queue = 2
      # Total = 44
      # Number of requests per second = 44 * 1000 / 25 = 1760 requests
      # 
      # Based on the use case, you can compromise latency and decrease number of partitions/requests to the queue, if the message load is low.
      # By UI set the parameters - interval (1000) and partitions (1) for Rule Engine queues.
      # Sample parameters to fit into 10 requests per second on a "monolith" deployment: 
      TB_QUEUE_CORE_POLL_INTERVAL_MS: 1000
      TB_QUEUE_CORE_PARTITIONS: 2
      TB_QUEUE_RULE_ENGINE_POLL_INTERVAL_MS: 1000
      TB_QUEUE_TRANSPORT_REQUEST_POLL_INTERVAL_MS: 1000
      TB_QUEUE_TRANSPORT_RESPONSE_POLL_INTERVAL_MS: 1000
      TB_QUEUE_TRANSPORT_NOTIFICATIONS_POLL_INTERVAL_MS: 1000
      TB_QUEUE_VC_INTERVAL_MS: 1000
      TB_QUEUE_VC_PARTITIONS: 1
    volumes:
      - ~/.mytbpe-data:/data
      - ~/.mytbpe-logs:/var/log/thingsboard
  postgres:
    restart: always
    image: "postgres:15"
    ports:
    - "5432"
    environment:
      POSTGRES_DB: thingsboard
      POSTGRES_PASSWORD: postgres
    volumes:
      - ~/.mytbpe-data/db:/var/lib/postgresql/data

You can update default Rule Engine queues configuration using UI. More about ThingsBoard Rule Engine queues see in documentation.

Where:

  • PUT_YOUR_LICENSE_SECRET_HERE - placeholder for your license secret obtained on the third step;
  • 8080:8080 - connect local port 8080 to exposed internal HTTP port 8080;
  • 1883:1883 - connect local port 1883 to exposed internal MQTT port 1883;
  • 7070:7070 - connect local port 7070 to exposed internal Edge RPC port 7070;
  • 5683-5688:5683-5688/udp - connect local UDP ports 5683-5688 to exposed internal COAP and LwM2M ports;
  • ~/.mytbpe-data:/data - mounts the host’s dir ~/.mytbpe-data to ThingsBoard data directory;
  • ~/.mytbpe-data/db:/var/lib/postgresql/data - mounts the host’s dir ~/.mytbpe-data/db to Postgres data directory;
  • ~/.mytbpe-logs:/var/log/thingsboard - mounts the host’s dir ~/.mytbpe-logs to ThingsBoard logs directory;
  • mytbpe - friendly local name of this machine;
  • restart: always - automatically start ThingsBoard in case of system reboot and restart in case of failure.;
  • thingsboard/tb-pe:4.0.0PE - docker image.

Step 4. Running

Before starting your Docker containers, execute the following commands to create directories for data storage and logs. These commands will also change the ownership of the newly created directories to the Docker container user.

The chown command is used to change the owner of the directories, and it requires sudo permissions. You may be prompted to enter a password to grant sudo access:

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For Docker Desktop users on MacOS, that utilize Synchronized file shares feature (enabled by default for /Users subdirectories):

Please note that you need to omit changing host volume ownership, since it is resolved automatically by virtualization engine.

mkdir -p ~/.mytbpe-data

mkdir -p ~/.mytbpe-logs

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mkdir -p ~/.mytbpe-data && sudo chown -R 799:799 ~/.mytbpe-data
mkdir -p ~/.mytbpe-logs && sudo chown -R 799:799 ~/.mytbpe-logs

NOTE: replace directory ~/.mytbpe-data and ~/.mytbpe-logs with directories you’re planning to used in docker-compose.yml.

Set the terminal in the directory which contains the docker-compose.yml file and execute the following commands to up this docker compose directly:

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docker compose up -d && docker compose logs -f mytbpe

After executing this command you can open http://{your-host-ip}:8080 in your browser (for ex. http://localhost:8080). You should see ThingsBoard login page. Use the following default credentials:

  • System Administrator: sysadmin@thingsboard.org / sysadmin
  • Tenant Administrator: tenant@thingsboard.org / tenant
  • Customer User: customer@thingsboard.org / customer

You can always change passwords for each account in account profile page.

Detaching, stop and start commands

You can detach from session terminal using Ctrl-p Ctrl-q key sequence - the container will keep running in the background.

In case of any issues you can examine service logs for errors. For example to see ThingsBoard PE container logs execute the following command:

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docker compose logs -f mytbpe

To stop the container:

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docker compose stop mytbpe

To start the container:

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docker compose start mytbpe
Doc info icon

Docker Compose as docker-compose (with a hyphen) is deprecated. It is recommended to use Docker Compose V2 instead.
If you still rely on docker compose as standalone here is the list of the above commands:
docker-compose logs -f mytbpe
docker-compose stop mytbpe
docker-compose start mytbpe

Upgrading

In case when database upgrade is needed:

  • Stop mytbpe container
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docker compose stop mytbpe
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If you still rely on Docker Compose as docker-compose (with a hyphen) execute next command:
docker-compose stop mytbpe

  • Update docker-compose.yml - TB image should be the latest version (see Step 3)

  • In case you are upgrading to:
    • 3.9.1 or newer - no additional actions required
    • 3.9.0 or previous releases - change upgradeversion variable to your current ThingsBoard version. For ex., if upgrading from 3.6.4: 
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      echo '3.6.4' | sudo tee ~/.mytbpe-data/.upgradeversion
  • Execute the following commands:
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docker compose run mytbpe upgrade-tb.sh
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If you still rely on Docker Compose as docker-compose (with a hyphen) execute next command:
docker-compose run mytbpe upgrade-tb.sh

  • Start ThingsBoard:
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docker compose up -d
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If you still rely on Docker Compose as docker-compose (with a hyphen) execute next command:
docker-compose up -d

Troubleshooting

DNS issues

NOTE If you observe errors related to DNS issues, for example

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127.0.1.1:53: cannot unmarshal DNS message

You may configure your system to use Google public DNS servers. See corresponding Linux and Mac OS instructions.

Next steps