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Installing ThingsBoard CE on Ubuntu Server

Prerequisites

This guide describes how to install ThingsBoard on Ubuntu 20.04 LTS / 22.04 LTS / 24.04 LTS. Hardware requirements depend on chosen database and amount of devices connected to the system. To run ThingsBoard and PostgreSQL on a single machine you will need at least 4Gb of RAM. To run ThingsBoard and Cassandra on a single machine you will need at least 8Gb of RAM.

Step 1. Install Java 17 (OpenJDK)

ThingsBoard service is running on Java 17. Follow this instructions to install OpenJDK 17:

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sudo apt update
sudo apt install openjdk-17-jdk

Please don’t forget to configure your operating system to use OpenJDK 17 by default. You can configure which version is the default using the following command:

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sudo update-alternatives --config java

You can check the installation using the following command:

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java -version

Expected command output is:

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openjdk version "17.x.xx" 
OpenJDK Runtime Environment (...)
OpenJDK 64-Bit Server VM (...)

Step 2. ThingsBoard service installation

Download installation package.

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wget https://github.com/thingsboard/thingsboard/releases/download/v3.8.1/thingsboard-3.8.1.deb

Install ThingsBoard as a service

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sudo dpkg -i thingsboard-3.8.1.deb

Step 3. Configure ThingsBoard database

ThingsBoard is able to use SQL or hybrid database approach. See corresponding architecture page for more details.

PostgreSQL (recommended for < 5K msg/sec)
Hybrid
PostgreSQL+Cassandra
(recommended for > 5K msg/sec)
Doc info icon

ThingsBoard team recommends to use PostgreSQL for development and production environments with reasonable load (< 5000 msg/sec). Many cloud vendors support managed PostgreSQL servers which is a cost-effective solution for most of ThingsBoard instances.

PostgreSQL Installation

Instructions listed below will help you to install PostgreSQL.

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# Automated repository configuration:
sudo apt install -y postgresql-common
sudo /usr/share/postgresql-common/pgdg/apt.postgresql.org.sh

# install and launch the postgresql service:
sudo apt update
sudo apt -y install postgresql-16
sudo service postgresql start

Once PostgreSQL is installed you may want to create a new user or set the password for the main user. The instructions below will help to set the password for main PostgreSQL user.

To switch your current user context to the postgres user, execute the following script:

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sudo su - postgres

To be able to interact with the PostgreSQL database, enter:

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psql

You will connect to the database as the main PostgreSQL user. To set the password, enter the following command after postgres=# :

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\password

Enter and confirm the password. Then, press “Ctrl+D” to return to main user console.

Then, connect to the “postgres” database as the “postgres” user:

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psql -U postgres -d postgres -h 127.0.0.1 -W

Create the ThingsBoard database named “thingsboard” :

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CREATE DATABASE thingsboard;

Press “Ctrl+D” twice to exit PostgreSQL.

ThingsBoard Configuration

Edit ThingsBoard configuration file

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sudo nano /etc/thingsboard/conf/thingsboard.conf

Add the following lines to the configuration file. Don’t forget to replace “PUT_YOUR_POSTGRESQL_PASSWORD_HERE” with your real postgres user password:

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# DB Configuration 
export DATABASE_TS_TYPE=sql
export SPRING_DATASOURCE_URL=jdbc:postgresql://localhost:5432/thingsboard
export SPRING_DATASOURCE_USERNAME=postgres
export SPRING_DATASOURCE_PASSWORD=PUT_YOUR_POSTGRESQL_PASSWORD_HERE
# Specify partitioning size for timestamp key-value storage. Allowed values: DAYS, MONTHS, YEARS, INDEFINITE.
export SQL_POSTGRES_TS_KV_PARTITIONING=MONTHS
Doc info icon

ThingsBoard team recommends to use Hybrid database approach if you do plan to have 1M+ devices in production or high data ingestion rate (> 5000 msg/sec). In this case, ThingsBoard will be storing timeseries data in Cassandra while continue to use PostgreSQL for main entities (devices/assets/dashboards/customers).

PostgreSQL Installation

Instructions listed below will help you to install PostgreSQL.

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# Automated repository configuration:
sudo apt install -y postgresql-common
sudo /usr/share/postgresql-common/pgdg/apt.postgresql.org.sh

# install and launch the postgresql service:
sudo apt update
sudo apt -y install postgresql-16
sudo service postgresql start

Once PostgreSQL is installed you may want to create a new user or set the password for the main user. The instructions below will help to set the password for main PostgreSQL user.

To switch your current user context to the postgres user, execute the following script:

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sudo su - postgres

To be able to interact with the PostgreSQL database, enter:

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psql

You will connect to the database as the main PostgreSQL user. To set the password, enter the following command after postgres=# :

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\password

Enter and confirm the password. Then, press “Ctrl+D” to return to main user console.

Then, connect to the “postgres” database as the “postgres” user:

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psql -U postgres -d postgres -h 127.0.0.1 -W

Create the ThingsBoard database named “thingsboard” :

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CREATE DATABASE thingsboard;

Press “Ctrl+D” twice to exit PostgreSQL.

Cassandra Installation

Instructions listed below will help you to install Cassandra.

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# Add cassandra repository
echo "deb https://debian.cassandra.apache.org 41x main" | sudo tee /etc/apt/sources.list.d/cassandra.sources.list
curl https://downloads.apache.org/cassandra/KEYS | sudo apt-key add -
sudo apt-get update
## Cassandra installation
sudo apt-get install cassandra
## Tools installation
sudo apt-get install cassandra-tools

In order to run Cassandra, you will need to install Java 11.

Install the package.

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sudo apt install openjdk-11-jdk

Set Java 17 as the default version (required for ThingsBoard).

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sudo update-alternatives --config java

Edit Cassandra config.

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sudo nano /usr/share/cassandra/cassandra.in.sh

Find the following line.

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# JAVA_HOME can optionally be set here
#JAVA_HOME=/usr/local/jdk6

And replace it as follows:

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# JAVA_HOME can optionally be set here
JAVA_HOME=/usr/lib/jvm/java-11-openjdk-amd64

Then, restart Cassandra.

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sudo service cassandra stop

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sudo service cassandra start

You can use Astra DB cloud instead installing your own Cassandra. See how to connect ThingsBoard to Astra DB

ThingsBoard Configuration

Edit ThingsBoard configuration file

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sudo nano /etc/thingsboard/conf/thingsboard.conf

Add the following lines to the configuration file. Don’t forget to replace “PUT_YOUR_POSTGRESQL_PASSWORD_HERE” with your real postgres user password:

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# DB Configuration 
export DATABASE_TS_TYPE=cassandra
export SPRING_DATASOURCE_URL=jdbc:postgresql://localhost:5432/thingsboard
export SPRING_DATASOURCE_USERNAME=postgres
export SPRING_DATASOURCE_PASSWORD=PUT_YOUR_POSTGRESQL_PASSWORD_HERE

You can optionally add the following parameters to reconfigure your ThingsBoard instance to connect to external Cassandra nodes:

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export CASSANDRA_CLUSTER_NAME=Thingsboard Cluster
export CASSANDRA_KEYSPACE_NAME=thingsboard
export CASSANDRA_URL=127.0.0.1:9042
export CASSANDRA_USE_CREDENTIALS=false
export CASSANDRA_USERNAME=
export CASSANDRA_PASSWORD=

Step 4. Choose ThingsBoard queue service

ThingsBoard is able to use various messaging systems/brokers for storing the messages and communication between ThingsBoard services. How to choose the right queue implementation?

  • 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.

  • RabbitMQ is recommended if you don’t have much load and you already have experience with this messaging system.

  • AWS SQS is a fully managed message queuing service from AWS. Useful if you plan to deploy ThingsBoard on AWS.

  • Google Pub/Sub is a fully managed message queuing service from Google. Useful if you plan to deploy ThingsBoard on Google Cloud.

  • Azure Service Bus is a fully managed message queuing service from Azure. Useful if you plan to deploy ThingsBoard on Azure.

  • 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)
Kafka in docker container (recommended for on-prem, production installations)
AWS SQS (managed service from AWS)
Google Pub/Sub (managed service from Google)
Azure Service Bus (managed service from Azure)
RabbitMQ (for small on-prem installations)
Confluent Cloud (Event Streaming Platform based on Kafka)

In Memory queue is built-in and enabled by default. No additional configuration steps required.

Kafka Installation

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

Install ZooKeeper

Kafka uses ZooKeeper so you need to first install ZooKeeper server:

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sudo apt-get install zookeeper
Setup ZooKeeper Systemd Unit file

Create systemd unit file for Zookeeper:

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sudo nano /etc/systemd/system/zookeeper.service

Add below content:

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[Unit]
Description=Apache Zookeeper server
Documentation=http://zookeeper.apache.org
Requires=network.target remote-fs.target
After=network.target remote-fs.target

[Service]
Type=simple
ExecStart=/usr/local/kafka/bin/zookeeper-server-start.sh /usr/local/kafka/config/zookeeper.properties
ExecStop=/usr/local/kafka/bin/zookeeper-server-stop.sh
Restart=on-abnormal

[Install]
WantedBy=multi-user.target
Enable and start ZooKeeper:
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sudo systemctl enable --now zookeeper
Install Kafka
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wget https://downloads.apache.org/kafka/3.8.1/kafka_2.13-3.8.1.tgz

tar -xzf kafka_2.13-3.8.1.tgz

sudo mv kafka_2.13-3.8.1 /usr/local/kafka
Setup Kafka Systemd Unit file

Create systemd unit file for Kafka:

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sudo nano /etc/systemd/system/kafka.service

Add the below content. Make sure to replace “PUT_YOUR_JAVA_PATH” with your real JAVA_HOME path as per the Java installed on your system, by default like “/usr/lib/jvm/java-11-openjdk-xxx”:

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[Unit]
Description=Apache Kafka Server
Documentation=http://kafka.apache.org/documentation.html
Requires=zookeeper.service

[Service]
Type=simple
Environment="JAVA_HOME=PUT_YOUR_JAVA_PATH"
ExecStart=/usr/local/kafka/bin/kafka-server-start.sh /usr/local/kafka/config/server.properties
ExecStop=/usr/local/kafka/bin/kafka-server-stop.sh

[Install]
WantedBy=multi-user.target
Enable and start Kafka:
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sudo systemctl enable --now kafka
ThingsBoard Configuration

Edit ThingsBoard configuration file

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sudo nano /etc/thingsboard/conf/thingsboard.conf

Add the following line to the configuration file. Don’t forget to replace “localhost:9092” with your real Kafka bootstrap servers:

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export TB_QUEUE_TYPE=kafka
export TB_KAFKA_SERVERS=localhost:9092

Kafka Installation

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

Install Kafka

Use the instructions below for installing Kafka in a Docker container.

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nano docker-compose-kafka.yml

Add the following lines to the docker-compose-kafka.yml file:

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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
volumes:
  kafka-data:
    driver: local

Start the container:

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docker compose -f docker-compose-kafka.yml up -d
ThingsBoard Configuration

Edit ThingsBoard configuration file

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sudo nano /etc/thingsboard/conf/thingsboard.conf

Add the following line to the configuration file. Don’t forget to replace “localhost:9092” with your real Kafka bootstrap servers:

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export TB_QUEUE_TYPE=kafka
export TB_KAFKA_SERVERS=localhost:9092

AWS SQS Configuration

To access AWS SQS service, you first need to create an AWS account.

To work with AWS SQS service you will need to create your next credentials using this instruction:

  • Access key ID
  • Secret access key
ThingsBoard Configuration

Edit ThingsBoard configuration file

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sudo nano /etc/thingsboard/conf/thingsboard.conf

Add the following lines to the configuration file. Don’t forget to replace “YOUR_KEY”, “YOUR_SECRET” with your real AWS SQS IAM user credentials and “YOUR_REGION” with your real AWS SQS account region:

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export TB_QUEUE_TYPE=aws-sqs
export TB_QUEUE_AWS_SQS_ACCESS_KEY_ID=YOUR_KEY
export TB_QUEUE_AWS_SQS_SECRET_ACCESS_KEY=YOUR_SECRET
export TB_QUEUE_AWS_SQS_REGION=YOUR_REGION

# 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: 

export TB_QUEUE_CORE_POLL_INTERVAL_MS=1000
export TB_QUEUE_CORE_PARTITIONS=2
export TB_QUEUE_RULE_ENGINE_POLL_INTERVAL_MS=1000
export TB_QUEUE_TRANSPORT_REQUEST_POLL_INTERVAL_MS=1000
export TB_QUEUE_TRANSPORT_RESPONSE_POLL_INTERVAL_MS=1000
export TB_QUEUE_TRANSPORT_NOTIFICATIONS_POLL_INTERVAL_MS=1000
export TB_QUEUE_VC_INTERVAL_MS=1000
export TB_QUEUE_VC_PARTITIONS=1

You can update default Rule Engine queues configuration (poll interval and partitions) using UI. More about ThingsBoard Rule Engine queues see in documentation.

Google Pub/Sub Configuration

To access Pub/Sub service, you first need to create an Google cloud account.

To work with Pub/Sub service you will need to create a project using this instruction.

Create service account credentials with the role “Editor” or “Admin” using this instruction, and save json file with your service account credentials step 9 here.

ThingsBoard Configuration

Edit ThingsBoard configuration file

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sudo nano /etc/thingsboard/conf/thingsboard.conf

Add the following lines to the configuration file. Don’t forget to replace “YOUR_PROJECT_ID”, “YOUR_SERVICE_ACCOUNT” with your real Pub/Sub project id, and service account (it is whole data from json file):

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export TB_QUEUE_TYPE=pubsub
export TB_QUEUE_PUBSUB_PROJECT_ID=YOUR_PROJECT_ID
export TB_QUEUE_PUBSUB_SERVICE_ACCOUNT=YOUR_SERVICE_ACCOUNT

# 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: 

export TB_QUEUE_CORE_POLL_INTERVAL_MS=1000
export TB_QUEUE_CORE_PARTITIONS=2
export TB_QUEUE_RULE_ENGINE_POLL_INTERVAL_MS=1000
export TB_QUEUE_TRANSPORT_REQUEST_POLL_INTERVAL_MS=1000
export TB_QUEUE_TRANSPORT_RESPONSE_POLL_INTERVAL_MS=1000
export TB_QUEUE_TRANSPORT_NOTIFICATIONS_POLL_INTERVAL_MS=1000
export TB_QUEUE_VC_INTERVAL_MS=1000
export TB_QUEUE_VC_PARTITIONS=1

You can update default Rule Engine queues configuration (poll interval and partitions) using UI. More about ThingsBoard Rule Engine queues see in documentation.

Azure Service Bus Configuration

To access Azure Service Bus, you first need to create an Azure account.

To work with Service Bus service you will need to create a Service Bus Namespace using this instruction.

Create Shared Access Signature using this instruction.

ThingsBoard Configuration

Edit ThingsBoard configuration file

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sudo nano /etc/thingsboard/conf/thingsboard.conf

Add the following lines to the configuration file. Don’t forget to replace “YOUR_NAMESPACE_NAME” with your real Service Bus namespace name, and “YOUR_SAS_KEY_NAME”, “YOUR_SAS_KEY” with your real Service Bus credentials. Note: “YOUR_SAS_KEY_NAME” it is “SAS Policy”, “YOUR_SAS_KEY” it is “SAS Policy Primary Key”:

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export TB_QUEUE_TYPE=service-bus
export TB_QUEUE_SERVICE_BUS_NAMESPACE_NAME=YOUR_NAMESPACE_NAME
export TB_QUEUE_SERVICE_BUS_SAS_KEY_NAME=YOUR_SAS_KEY_NAME
export TB_QUEUE_SERVICE_BUS_SAS_KEY=YOUR_SAS_KEY

# 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: 

export TB_QUEUE_CORE_POLL_INTERVAL_MS=1000
export TB_QUEUE_CORE_PARTITIONS=2
export TB_QUEUE_RULE_ENGINE_POLL_INTERVAL_MS=1000
export TB_QUEUE_TRANSPORT_REQUEST_POLL_INTERVAL_MS=1000
export TB_QUEUE_TRANSPORT_RESPONSE_POLL_INTERVAL_MS=1000
export TB_QUEUE_TRANSPORT_NOTIFICATIONS_POLL_INTERVAL_MS=1000
export TB_QUEUE_VC_INTERVAL_MS=1000
export TB_QUEUE_VC_PARTITIONS=1

You can update default Rule Engine queues configuration (poll interval and partitions) using UI. More about ThingsBoard Rule Engine queues see in documentation.

RabbitMQ Installation

For installation RabbitMQ you can use official docs, or our instruction bellow:

Since RabbitMQ is written in Erlang, you need to install Erlang before you can use RabbitMQ:

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sudo apt-get install erlang

Install the rabbitmq-server package:

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sudo apt-get install rabbitmq-server

Start the Server:

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sudo systemctl start rabbitmq-server.service
sudo systemctl enable rabbitmq-server.service

By default, RabbitMQ creates a user named “guest” with a password “guest”. You can also create your own administrator account on RabbitMQ server using following commands. Don’t forget to replace “PUT_YOUR_USER_NAME” like: “admin” and “PUT_YOUR_PASSWORD” with your own user name and password:

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sudo rabbitmqctl add_user PUT_YOUR_USER_NAME PUT_YOUR_PASSWORD 
sudo rabbitmqctl set_user_tags PUT_YOUR_USER_NAME administrator
sudo rabbitmqctl set_permissions -p / PUT_YOUR_USER_NAME ".*" ".*" ".*"
ThingsBoard Configuration

Edit ThingsBoard configuration file

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sudo nano /etc/thingsboard/conf/thingsboard.conf

Add the following lines to the configuration file. Don’t forget to replace “YOUR_USERNAME” and “YOUR_PASSWORD” with your real user credentials, “localhost” and “5672” with your real RabbitMQ host and port:

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export TB_QUEUE_TYPE=rabbitmq
export TB_QUEUE_RABBIT_MQ_USERNAME=YOUR_USERNAME
export TB_QUEUE_RABBIT_MQ_PASSWORD=YOUR_PASSWORD
export TB_QUEUE_RABBIT_MQ_HOST=localhost
export TB_QUEUE_RABBIT_MQ_PORT=5672

Confluent Cloud Configuration

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

ThingsBoard Configuration

Edit ThingsBoard configuration file

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sudo nano /etc/thingsboard/conf/thingsboard.conf

Add the following lines to the configuration file. Don’t forget to replace “CLUSTER_API_KEY”, “CLUSTER_API_SECRET” and “localhost:9092” with your real Confluent Cloud bootstrap servers:**

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export TB_QUEUE_TYPE=kafka
export TB_QUEUE_KAFKA_USE_CONFLUENT_CLOUD=true
export TB_KAFKA_SERVERS=localhost:9092
export TB_QUEUE_KAFKA_REPLICATION_FACTOR=3
export TB_QUEUE_KAFKA_CONFLUENT_SASL_JAAS_CONFIG='org.apache.kafka.common.security.plain.PlainLoginModule required username="CLUSTER_API_KEY" password="CLUSTER_API_SECRET";'

# 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: 

export TB_QUEUE_CORE_POLL_INTERVAL_MS=1000
export TB_QUEUE_CORE_PARTITIONS=2
export TB_QUEUE_RULE_ENGINE_POLL_INTERVAL_MS=1000
export TB_QUEUE_TRANSPORT_REQUEST_POLL_INTERVAL_MS=1000
export TB_QUEUE_TRANSPORT_RESPONSE_POLL_INTERVAL_MS=1000
export TB_QUEUE_TRANSPORT_NOTIFICATIONS_POLL_INTERVAL_MS=1000
export TB_QUEUE_VC_INTERVAL_MS=1000
export TB_QUEUE_VC_PARTITIONS=1

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

Step 5. [Optional] Memory update for slow machines (4GB of RAM)

Edit ThingsBoard configuration file

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sudo nano /etc/thingsboard/conf/thingsboard.conf

Add the following lines to the configuration file.

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# Update ThingsBoard memory usage and restrict it to 2G in /etc/thingsboard/conf/thingsboard.conf
export JAVA_OPTS="$JAVA_OPTS -Xms2G -Xmx2G"

We recommend adjusting these parameters depending on your server resources. It should be set to at least 2G (gigabytes), and increased accordingly if there is additional RAM space available. Usually, you need to set it to 1/2 of your total RAM if you do not run any other memory-intensive processes (e.g. Cassandra), or to 1/3 otherwise.

Step 6. Run installation script

Once ThingsBoard service is installed and DB configuration is updated, you can execute the following script:

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# --loadDemo option will load demo data: users, devices, assets, rules, widgets.
sudo /usr/share/thingsboard/bin/install/install.sh --loadDemo

Step 7. Start ThingsBoard service

Execute the following command to start ThingsBoard:

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sudo service thingsboard start

Once started, you will be able to open Web UI using the following link:

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http://localhost:8080/

The following default credentials are available if you have specified –loadDemo during execution of the installation script:

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

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Please allow up to 90 seconds for the Web UI to start.

Post-installation steps

Configure HAProxy to enable HTTPS

You may want to configure HTTPS access using HAProxy. This is possible in case you are hosting ThingsBoard in the cloud and have a valid DNS name assigned to your instance. Please follow this guide to install HAProxy and generate valid SSL certificate using Let’s Encrypt.

Troubleshooting

ThingsBoard logs are stored in the following directory:

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/var/log/thingsboard

You can issue the following command in order to check if there are any errors on the backend side:

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cat /var/log/thingsboard/thingsboard.log | grep ERROR

Next steps