Installing ThingsBoard PE on Ubuntu

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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

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sudo su - postgres

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psql

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\password

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

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CREATE DATABASE thingsboard;

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

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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

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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

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sudo su - postgres

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psql

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\password

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

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CREATE DATABASE thingsboard;

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sudo apt install openjdk-11-jdk

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sudo update-alternatives --config java

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

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sudo service cassandra stop

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sudo service cassandra start

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

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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

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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=

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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

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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

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export TB_QUEUE_TYPE=kafka
export TB_KAFKA_SERVERS=localhost:9092

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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

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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

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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

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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

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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

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cat <<EOT >> tb-web-report.yml
version: '3.0'
services:
  tb-web-report:
    container_name: tb-web-report
    restart: always
    image: "thingsboard/tb-pe-web-report:3.8.1PE"
    ports:
      - "8383:8383"
    env_file:
      - ./tb-web-report.env
EOT

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cat <<EOT >> tb-web-report.env
HTTP_BIND_ADDRESS=0.0.0.0
HTTP_BIND_PORT=8383
LOGGER_LEVEL=info
LOG_FOLDER=logs
LOGGER_FILENAME=tb-web-report-%DATE%.log
DOCKER_MODE=true

DEFAULT_PAGE_NAVIGATION_TIMEOUT=120000
DASHBOARD_LOAD_WAIT_TIME=3000
USE_NEW_PAGE_FOR_REPORT=true
EOT

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docker compose -f tb-web-report.yml up -d

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docker logs -f tb-web-report

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wget https://dist.thingsboard.io/tb-web-report-3.8.1pe.deb

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sudo apt install -yq  libatk1.0-0 libc6 libcairo2 libcups2 libdbus-1-3 \
     libexpat1 libfontconfig1 libgcc1  libgdk-pixbuf2.0-0 libglib2.0-0 libgtk-3-0 libnspr4 \
     libpango-1.0-0 libpangocairo-1.0-0 libstdc++6 libx11-6 libx11-xcb1 libxcb1 libxcomposite1 \
     libxcursor1 libxdamage1 libxext6 libxfixes3 libxi6 libxrandr2 libxrender1 libxss1 libxtst6 \
     ca-certificates fonts-liberation libnss3 lsb-release xdg-utils unzip wget libgbm-dev

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sudo apt install fonts-roboto

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sudo dpkg -i tb-web-report-3.8.1pe.deb
sudo service tb-web-report start