- Install Kafka Docker Linux
- Install Kafka Docker Windows
- Install Kafka Docker Centos
- Setup Kafka Docker Compose
Docker Java Example
We shall learn following items in this Docker Java Example :
Apr 15, 2020 To install packages in a docker container, the packages should be defined in the Dockerfile. If you want to install packages in the Container, use the RUN statement followed by exact download command. $ RUN pip install //IN Windows $ RUN apt-get install //in Ubuntu $ RUN yum install //CentOS/RHEL. Nov 27, 2019 Install Docker on all the Master and Worker Nodes participating in your cluster. That means you need to repeat this process on each node in turn. Note: Hardware devices have unique addresses, although some virtual machines may have identical values.
Build Docker Image with Java Application
1. Create a directory
A separate directory is useful to organise docker applications. For this Java Example, create a directory somewhere with name of your choice. We shall use the name java-application
2. Create Java Application
Create a simple Java File, in the directory java-application, with name HelloWorld.java containing the following content.
3. Dockerfile
Create a file with name Dockerfile. Dockerfile contains instructions to prepare Docker image with our Java Application.
Following is the content of Dockerfile.
4. Verify contents of java-application directory
5. Build docker image
Login as root user. Navigate into java-application directory and run the following command. Instructions in the Dockerfile are executed.
Please observe that there is dot (.) at the end of the command. Docker image is successfully built.
6. Check the docker image
To display available docker images, run the following command.
Run Docker Java Example
Run the following command to run the java-application Docker image in a container.
The Java Application has run, and the print statement could be seen in the console.
Save Docker Image to a tar file
Save the Docker Image file to a tar file, so that the image file could be copied to other machines through disk storage devices like pen-drive, etc.
Run the following command to save Docker image as a tar file.
Saving might take few seconds. Wait for the command to complete.
Copy and Run the Docker Image file in another machine
You may copy the Docker image tar file to another computer.
Run the following command to load the Docker image into the Docker.
Replace /home/arjun/workspace/java-application.tar with your file location.
You may run the image using the same command we used to run the image file after building.
Conclusion
In this Docker Tutorial – Docker Java Example, we have learnt to build a Docker Image with Java Application and also how to save the image to a file and transfer it to other computers or servers.
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. |
- Troubleshooting
This guide will help you to install and start ThingsBoard using Docker on Linux or Mac OS.
Prerequisites
Running
Depending on the database used there are three type of ThingsBoard single instance docker images:
thingsboard/tb-postgres - single instance of ThingsBoard with PostgreSQL database.
Recommended option for small servers with at least 1GB of RAM and minimum load (few messages per second). 2-4GB is recommended.
thingsboard/tb-cassandra - single instance of ThingsBoard with Cassandra database.
The most performant and recommended option but requires at least 4GB of RAM. 8GB is recommended.
thingsboard/tb - single instance of ThingsBoard with embedded HSQLDB database.
Note: Not recommended for any evaluation or production usage and is used only for development purposes and automatic tests.
In this instruction thingsboard/tb-postgres
image will be used. You can choose any other images with different databases (see above).
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.
ThingsBoard includes In Memory Queue service and use it by default without extra settings. Create docker compose file for ThingsBoard queue service: Add the following lines to the yml file: |
Apache Kafka is an open-source stream-processing software platform. Create docker compose file for ThingsBoard queue service: Add the following lines to the yml file. |
AWS SQS ConfigurationTo 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:
Create docker compose file for ThingsBoard queue service: Add the following lines to the yml 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: |
Google Pub/Sub ConfigurationTo 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. Create docker compose file for ThingsBoard queue service: Add the following lines to the yml 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): |
Azure Service Bus ConfigurationTo 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. Create docker compose file for ThingsBoard queue service: Add the following lines to the yml 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”: |
For installing RabbitMQ use this instruction. Create docker compose file for ThingsBoard queue service: Add the following lines to the yml 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: |
Confluent Cloud ConfigurationTo 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: Add the following line to the yml file. Don’t forget to replace “CLUSTER_API_KEY”, “CLUSTER_API_SECRET” and “localhost:9092” with your real Confluent Cloud bootstrap servers: |
Where:
8080:9090
- connect local port 8080 to exposed internal HTTP port 90901883:1883
- connect local port 1883 to exposed internal MQTT port 18835683:5683
- connect local port 5683 to exposed internal COAP port 5683~/.mytb-data:/data
- mounts the host’s dir~/.mytb-data
to ThingsBoard DataBase data directory~/.mytb-logs:/var/log/thingsboard
- mounts the host’s dir~/.mytb-logs
to ThingsBoard logs directorymytb
- friendly local name of this machinerestart: always
- automatically start ThingsBoard in case of system reboot and restart in case of failure.image: thingsboard/tb-postgres
- docker image, can be alsothingsboard/tb-cassandra
orthingsboard/tb
Before starting Docker container run following commands to create a directory for storing data and logs and then change its owner to docker container user,to be able to change user, chown command is used, which requires sudo permissions (command will request password for a sudo access):
NOTE: Replace directory ~/.mytb-data
and ~/.mytb-logs
with directories you’re planning to use in docker-compose.yml
.
Set the terminal in the directory which contains the docker-compose.yml
file and execute the following command to up this docker compose directly:
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: [email protected] / sysadmin
- Tenant Administrator: [email protected] / tenant
- Customer User: [email protected] / customer
You can always change passwords for each account in account profile page.
Detaching, stop and start commands
Install Kafka Docker Linux
You can detach from session terminal with Ctrl-p
Ctrl-q
- 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 node logs execute the following command:
To stop the container:
To start the container:
Install Kafka Docker Windows
Upgrading
In order to update to the latest image, execute the following commands:
NOTE: if you use different database change image name in all commands from thingsboard/tb-postgres
to thingsboard/tb-cassandra
or thingsboard/tb
correspondingly.
NOTE: replace host’s directory ~/.mytb-data
with directory used during container creation.
NOTE: if you have used one database and want to try another one, then remove the current docker container using docker-compose rm
command and use different directory for ~/.mytb-data
in docker-compose.yml
.
Troubleshooting
DNS issues
Note If you observe errors related to DNS issues, for example
Install Kafka Docker Centos
You may configure your system to use Google public DNS servers. See corresponding Linux and Mac OS instructions.
Next steps
Getting started guides - These guides provide quick overview of main ThingsBoard features. Designed to be completed in 15-30 minutes.
Connect your device - Learn how to connect devices based on your connectivity technology or solution.
Data visualization - These guides contain instructions how to configure complex ThingsBoard dashboards.
Data processing & actions - Learn how to use ThingsBoard Rule Engine.
IoT Data analytics - Learn how to use rule engine to perform basic analytics tasks.
Hardware samples - Learn how to connect various hardware platforms to ThingsBoard.
Advanced features - Learn about advanced ThingsBoard features.
Contribution and Development - Learn about contribution and development in ThingsBoard.