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Installing ThingsBoard on Raspberry Pi

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ThingsBoard Cloud

We recommend to use ThingsBoard Cloud - fully managed, scalable and fault-tolerant platform for your IoT applications
ThingsBoard Cloud is for everyone who would like to use ThingsBoard but don’t want to host their own instance of the platform.

This guide describes how to install ThingsBoard on a Raspberry Pi running Raspbian Buster.

Third-party components installation

Step 1. Install Java 11 (OpenJDK)

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# Add repository.
echo "deb http://deb.debian.org/debian unstable main non-free contrib" | sudo tee /etc/apt/sources.list

# Run system update.
sudo apt update

# Install JAVA
sudo apt install openjdk-11-jdk

#Check installation
java -version

Step 2. ThingsBoard service installation

Download installation package.

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wget https://github.com/thingsboard/thingsboard/releases/download/v3.6.4/thingsboard-3.6.4.deb

Install ThingsBoard as a service

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sudo dpkg -i thingsboard-3.6.4.deb

Step 3. Configure ThingsBoard database

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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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# install **wget** if not already installed:
sudo apt install -y wget

# import the repository signing key:
wget --quiet -O - https://www.postgresql.org/media/keys/ACCC4CF8.asc | sudo apt-key add -

# add repository contents to your system:
echo "deb https://apt.postgresql.org/pub/repos/apt/ $(lsb_release -cs)-pgdg main" | sudo tee  /etc/apt/sources.list.d/pgdg.list

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

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

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sudo su - postgres
psql
\password
\q

Then, press “Ctrl+D” to return to main user console and connect to the database to create thingsboard DB:

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psql -U postgres -d postgres -h 127.0.0.1 -W
CREATE DATABASE thingsboard;
\q
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

Step 4. Choose ThingsBoard queue service

ThingsBoard uses queue services for API calls between micro-services and able to use next queue services: In Memory (default), AWS SQS, Google Pub/Sub or Azure Service Bus.

In Memory (built-in and default)
AWS SQS (managed service from AWS)
Google Pub/Sub (managed service from Google)
Azure Service Bus (managed service from Azure)
Confluent Cloud (Event Streaming Platform based on Kafka)

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

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.

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. Memory update for slow machines (1GB 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 256MB in /etc/thingsboard/conf/thingsboard.conf
export JAVA_OPTS="$JAVA_OPTS -Xms256M -Xmx256M"

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 240 seconds for the Web UI to start. This is applicable only for slow machines with 1-2 CPUs or 1-2 GB RAM.

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