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安装 > 本地环境 > Docker (Windows)
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Docker(Windows)安装

ThingsBoard云服务

建议你的物联网应用程序使用ThingsBoard云服务完全托管，可扩展和容错的平台。
ThingsBoard云服务适用于想要使用ThingsBoard但又不想自己托管平台实例的每个人。

本指南将帮助你在Windows上使用Docker安装和启动ThingsBoard。

先决条件

运行

根据所使用的数据库有三种类型的ThingsBoard单实例docker映像：

  • thingsboard/tb-postgres - ThingsBoard与PostgreSQL数据库的单实例

    对于具有至少1GB内存的小型服务器的推荐选项建议使用2-4GB。

  • thingsboard/tb-cassandra - 具有Cassandra数据库的ThingsBoard的单个实例。

    最高性能和推荐的选项但至少需要4GB的RAM建议使用8GB。

  • thingsboard/tb - 具有嵌入式HSQLDB数据库的ThingsBoard的单个实例。

    注意： 不建议用于任何评估或生产用途仅用于开发目的和自动测试。

在此说明中将使用thingsboard/tb-postgres镜像你可以选择其他具有不同数据库的镜像（请参见上文）。

Windows用户应将Docker托管卷用于ThingsBoard数据库。
在执行docker run命令之前创建docker卷(例如mytb-data):
打开”Docker Quickstart Terminal”。执行以下命令以创建Docker卷：

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docker volume create mytb-data
docker volume create mytb-logs

选择消息队列服务

ThingsBoard使用消息系统存储服务之间的通信，请正确选择队列？

  • 内存 适用于开发环境（开发）

  • Kafka 适用于生产环境（集群）

  • RabbitMQ 适用生产环境（单体）

  • AWS SQS 适用生产环境（AWS公有云）

  • Google发布/订阅 适用生产环境（Google公有云）

  • Azure服务总线 适用生产环境（Azure公有云）

  • Confluent云 适用于生产环境（托管）

参见相应的架构页面和规则引擎页面以获取更多详细信息。

内存(默认内置)
Kafka(本地安装)
AWS(AWS托管)
Google发布/订阅(Google托管)
Azure服务总线(Azure托管)
RabbitMQ(本地最小安装)
Confluent云(基于Kafka事件流)

ThingsBoard默认使用内存队列服务无需额外设置。

创建docker compose文件：

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docker-compose.yml

将以下行添加到yml文件

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version: '3.0'
services:
  mytb:
    restart: always
    image: "thingsboard/tb-postgres"
    ports:
      - "8080:9090"
      - "1883:1883"
      - "7070:7070"
      - "5683-5688:5683-5688/udp"
    environment:
      TB_QUEUE_TYPE: in-memory
    volumes:
      - mytb-data:/data
      - mytb-logs:/var/log/thingsboard
volumes:
  mytb-data:
    external: true
  mytb-logs:
    external: true

Kafka安装

Apache Kafka是一个开源的流式数据处理平台。

创建docker compose文件：

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docker-compose.yml

Add the following line to the yml file.

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version: '3.0'
services:
  zookeeper:
    restart: always
    image: "zookeeper:3.5"
    ports:
      - "2181:2181"
    environment:
      ZOO_MY_ID: 1
      ZOO_SERVERS: server.1=zookeeper:2888:3888;zookeeper:2181
  kafka:
    restart: always
    image: wurstmeister/kafka
    depends_on:
      - zookeeper
    ports:
      - "9092:9092"
    environment:
      KAFKA_ZOOKEEPER_CONNECT: zookeeper:2181
      KAFKA_LISTENERS: INSIDE://:9093,OUTSIDE://:9092
      KAFKA_ADVERTISED_LISTENERS: INSIDE://:9093,OUTSIDE://kafka:9092
      KAFKA_LISTENER_SECURITY_PROTOCOL_MAP: INSIDE:PLAINTEXT,OUTSIDE:PLAINTEXT
      KAFKA_INTER_BROKER_LISTENER_NAME: INSIDE
    volumes:
      - /var/run/docker.sock:/var/run/docker.sock
  mytb:
    restart: always
    image: "thingsboard/tb-postgres"
    depends_on:
      - kafka
    ports:
      - "8080:9090"
      - "1883:1883"
      - "7070:7070"
      - "5683-5688:5683-5688/udp"
    environment:
      TB_QUEUE_TYPE: kafka
      TB_KAFKA_SERVERS: kafka:9092
    volumes:
      - mytb-data:/data
      - mytb-logs:/var/log/thingsboard
volumes:
  mytb-data:
    external: true
  mytb-logs:
    external: true

AWS SQS配置

首先需要创建AWS账户然后访问AWS SQS服务。

使用此说明创建AWS SQS服务凭证。

  • Access key ID
  • Secret access key

创建docker compose文件：

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docker-compose.yml

添加配置将”YOUR_KEY”和”YOUR_SECRET”替换为真实的AWS用户凭证并将”YOUR_REGION”替换成AWS SQS帐户区域：

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version: '3.0'
services:
  mytb:
    restart: always
    image: "thingsboard/tb-postgres"
    ports:
      - "9090:9090"
      - "1883:1883"
      - "7070:7070"
      - "5683-5688:5683-5688/udp"
    environment:
      TB_QUEUE_TYPE: aws-sqs
      TB_QUEUE_AWS_SQS_ACCESS_KEY_ID: YOUR_KEY
      TB_QUEUE_AWS_SQS_SECRET_ACCESS_KEY: YOUR_SECRET
      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: 
      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:
      - ~/.mytb-data:/data
      - ~/.mytb-logs:/var/log/thingsboard
volumes:
  mytb-data:
    external: true
  mytb-logs:
    external: true

可以使用UI更新默认规则引擎队列配置（轮询间隔和分区）有关ThingsBoard规则引擎队列的更多信息请参阅文档。

Google发布/订阅配置

创建一个Google帐户并访问发布/订阅服务。

使用此说明创建一个项目并使用发布/订阅服务。

使用此说明创建服务帐户凭据并编辑角色或管理员后保存json凭据步骤9的文件此处。

创建docker compose文件：

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docker-compose.yml

添加下面配置内容使用真正用户密码替换“YOUR_PROJECT_ID”, “YOUR_SERVICE_ACCOUNT”：

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version: '3.0'
services:
  mytb:
    restart: always
    image: "thingsboard/tb-postgres"
    ports:
      - "8080:9090"
      - "1883:1883"
      - "7070:7070"
      - "5683-5688:5683-5688/udp"
    environment:
      TB_QUEUE_TYPE: pubsub
      TB_QUEUE_PUBSUB_PROJECT_ID: YOUR_PROJECT_ID
      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: 
      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:
      - mytb-data:/data
      - mytb-logs:/var/log/thingsboard
volumes:
  mytb-data:
    external: true
  mytb-logs:
    external: true

可以使用UI更新默认规则引擎队列配置（轮询间隔和分区）有关ThingsBoard规则引擎队列的更多信息请参阅文档。

Azure服务总线配置

创建Azure帐户并访问Azure服务总线。

通过使用说明了解并使用总线服务。

使用说明创建共享访问签名。

创建docker compose文件：

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docker-compose.yml

添加下面配置内容使用真正的服务总线名称空间替换”YOUR_NAMESPACE_NAME”和”YOUR_SAS_KEY_NAME”及”YOUR_SAS_KEY”：

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version: '3.0'
services:
  mytb:
    restart: always
    image: "thingsboard/tb-postgres"
    ports:
      - "8080:9090"
      - "1883:1883"
      - "7070:7070"
      - "5683-5688:5683-5688/udp"
    environment:
      TB_QUEUE_TYPE: service-bus
      TB_QUEUE_SERVICE_BUS_NAMESPACE_NAME: YOUR_NAMESPACE_NAME
      TB_QUEUE_SERVICE_BUS_SAS_KEY_NAME: YOUR_SAS_KEY_NAME
      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: 
      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:
      - mytb-data:/data
      - mytb-logs:/var/log/thingsboard
volumes:
  mytb-data:
    external: true
  mytb-logs:
    external: true

可以使用UI更新默认规则引擎队列配置（轮询间隔和分区）有关ThingsBoard规则引擎队列的更多信息请参阅文档。

RabbitMQ安装

你可以使用官方文档安装RabbitMQ或按照以下说明：

创建docker compose文件：

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docker-compose.yml

将以下行添加到配置文件将“YOUR_USERNAME”和“YOUR_PASSWORD”替换为真实的信息将“localhost”和“5672”替换为真实的RabbitMQ主机和端口：

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version: '3.0'
services:
  mytb:
    restart: always
    image: "thingsboard/tb-postgres"
    ports:
      - "8080:9090"
      - "1883:1883"
      - "7070:7070"
      - "5683-5688:5683-5688/udp"
    environment:
      TB_QUEUE_TYPE: rabbitmq
      TB_QUEUE_RABBIT_MQ_USERNAME: YOUR_USERNAME
      TB_QUEUE_RABBIT_MQ_PASSWORD: YOUR_PASSWORD
      TB_QUEUE_RABBIT_MQ_HOST: localhost
      TB_QUEUE_RABBIT_MQ_PORT: 5672
    volumes:
      - mytb-data:/data
      - mytb-logs:/var/log/thingsboard
volumes:
  mytb-data:
    external: true
  mytb-logs:
    external: true

Confluent配置

你应该创建一个帐户后访问Confluent云然后创建一个Kafka集群和 API Key。

创建docker compose文件：

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docker-compose.yml

添加下面配置内容使用真正的Confluent云服务器地址替换”CLUSTER_API_KEY”, “CLUSTER_API_SECRET”和”localhost:9092”：

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version: '3.0'
services:
  mytb:
    restart: always
    image: "thingsboard/tb-postgres"
    ports:
      - "8080:9090"
      - "1883:1883"
      - "7070:7070"
      - "5683-5688:5683-5688/udp"
    environment:
      TB_QUEUE_TYPE: kafka
      TB_KAFKA_SERVERS: localhost:9092
      TB_QUEUE_KAFKA_REPLICATION_FACTOR: 3
      TB_QUEUE_KAFKA_USE_CONFLUENT_CLOUD: true
      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: 
      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:
      - mytb-data:/data
      - mytb-logs:/var/log/thingsboard
volumes:
  mytb-data:
    external: true
  mytb-logs:
    external: true

{: .copy-code}\

可以使用UI更新默认规则引擎队列配置（轮询间隔和分区）有关ThingsBoard规则引擎队列的更多信息请参阅文档。

说明:

  • docker run - 运行容器
  • -it - 将终端会话与当前ThingsBoard进程输出连接
  • 8080:9090 - 将本地端口8080转发至HTTP端口9090
  • 1883:1883 - 将本地端口1883转发至MQTT端口1883
  • 5683:5683 - 将本地端口5683转发至MQTT端口5683
  • ~/.mytb-data:/data - 将主机的目录~/.mytb-data挂载到ThingsBoard数据目录
  • ~/.mytb-logs:/var/log/thingsboard - 将主机的目录~/.mytb-logs挂载到ThingsBoard日志目录
  • mytb - 计算机本地名称
  • restart: always - 在系统重新启动的情况下自动启动ThingsBoard在出现故障的情况下自动重新启动ThingsBoard。
  • image: thingsboard/tb-postgres - docker镜像也可以是thingsboard/tb-cassandra或thingsboard/tb

在包含该文件的目录终端中执行以下命令启动此docker compos：docker-compose.yml

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docker compose pull
docker compose up -d
docker compose logs -f mytb

ThingsBoard3.4.2版本开始支持Docker Compose V2（Docker Desktop或Compose插件）因为Docker不再支持docker-compose作为独立设置。

我们强烈建议更新到Docker Compose V2 使用它。

更新最新镜像docker-compose命令：
docker-compose pull
docker-compose up -d
docker-compose logs -f mytb

为了从Windows计算机上的外部IP/主机访问必需的资源请执行以下命令：

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set PATH=%PATH%;"C:\Program Files\Oracle\VirtualBox"
VBoxManage controlvm "default" natpf1 "tcp-port8080,tcp,,8080,,9090"  
VBoxManage controlvm "default" natpf1 "tcp-port1883,tcp,,1883,,1883"
VBoxManage controlvm "default" natpf1 "tcp-port7070,tcp,,7070,,7070"
VBoxManage controlvm "default" natpf1 "udp-port5683,udp,,5683,,5683"
VBoxManage controlvm "default" natpf1 "udp-port5684,udp,,5684,,5684"
VBoxManage controlvm "default" natpf1 "udp-port5685,udp,,5685,,5685"
VBoxManage controlvm "default" natpf1 "udp-port5686,udp,,5686,,5686"
VBoxManage controlvm "default" natpf1 "udp-port5687,udp,,5687,,5687"
VBoxManage controlvm "default" natpf1 "udp-port5688,udp,,5688,,5688"

说明:

  • C:\Program Files\Oracle\VirtualBox - VirtualBox安装目录的路径

执行完命令后你可以http://{your-host-ip}:8080在浏览器中打开(例如http://localhost:8080)。 使用以下默认凭据：

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

可以在帐户详情页面中更改每个帐户的密码。

分离、停止和启动

你可以使用Ctrl-p Ctrl-q与会话终端分离容器将继续在后台运行。

如果出现任何问题可以检查服务日志中的错误例如：要查看ThingsBoard容器日志。
请执行以下命令：

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docker compose logs -f mytb

停止容器：

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docker compose stop mytb

启动容器：

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docker compose start mytb

Docker Compose已被弃用建议使用Docker Compose V2
更新最新镜像docker-compose命令：
docker-compose logs -f mytb
docker-compose stop mytb
docker-compose start mytb

升级

更新最新镜像命令：

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$ docker pull thingsboard/tb-postgres
$ docker compose stop
$ docker run -it -v mytb-data:/data --rm thingsboard/tb-postgres upgrade-tb.sh
$ docker compose rm mytb
$ docker compose up

更新最新镜像docker-compose命令：
$ docker pull thingsboard/tb-postgres
$ docker-compose stop
$ docker run -it -v mytb-data:/data –rm thingsboard/tb-postgres upgrade-tb.sh
$ docker-compose rm mytb
$ docker-compose up

注意: 如果你使用不同的数据库则在所有命令中将映像名称从更改为thingsboard/tb-postgres至thingsboard/tb-cassandra或thingsboard/tb 。

注意: 将主机的目录替换为~/.mytb-data容器创建期间使用的目录。

故障排查

DNS问题

注意：如果你发现与DNS问题相关的错误，例如

1

127.0.1.1:53: cannot unmarshal DNS message

你可以配置系统以使用Google公用DNS服务

下一步

  • 入门指南 - 快速学习ThingsBoard相关功能。

  • 连接设备 - 学习如何根据你的连接方式或解决方案连接设备。

  • 可 视 化 - 学习如何配置复杂的ThingsBoard仪表板说明。

  • 数据处理 - 学习如何使用ThingsBoard规则引擎。

  • 数据分析 - 学习如何使用规则引擎执行基本的分析任务。

  • 硬件样品 - 学习如何将各种硬件平台连接到ThingsBoard。

  • 高级功能 - 学习高级ThingsBoard功能。

  • 开发指南 - 学习ThingsBoard中的贡献和开发。