Docker compose is a tool for defining and running multi-container (Skedler Reports, Elasticsearch and Kibana) Docker applications.  With Compose, you use a YAML file to configure your application’s services. Then with a single command, you create and start all the services from your configuration.

In this section, I will describe how to create a containerized installation for Skedler Reports, Elasticsearch and Kibana.

Benefits:

• You describe the multi-container set up in a clear way and bring up the containers in a single command.
• You can define the priority and dependency of the container on other containers.

Step-by-Step Instruction:

Step 1: Define services in a Compose file:

Create a file called docker-compose.yml in your project directory and paste the following

docker-compose.yml:

—

version: “2.4”

services:

#  Skedler Reports container

  reports:

    image: skedler/reports:latest

    container_name: reports

    privileged: true

    cap_add:

      – SYS_ADMIN

    volumes:

      – /sys/fs/cgroup:/sys/fs/cgroup:ro

      – reportdata:/var/lib/skedler

      – ./reporting.yml:/opt/skedler/config/reporting.yml

    command: /opt/skedler/bin/skedler

    depends_on:

      elasticsearch: { condition: service_healthy }

    ports:

      – 3000:3000

    healthcheck:

      test: [“CMD”, “curl”, “-s”, “-f”, “http://localhost:3000”]

    networks: [‘stack’]

#  Elasticsearch container

  elasticsearch:

    container_name: elasticsearch

    hostname: elasticsearch

    image: “docker.elastic.co/elasticsearch/elasticsearch:7.1.1”

    logging:

      options:

        max-file: “3”

        max-size: “50m”

    environment:

      – http.host=0.0.0.0

      – transport.host=127.0.0.1

      – bootstrap.memory_lock=true

      – “ES_JAVA_OPTS=-Xms${ES_JVM_HEAP} -Xmx${ES_JVM_HEAP}”

    mem_limit: ${ES_MEM_LIMIT}

    ulimits:

      memlock:

        soft: -1

        hard: -1

    volumes:

      – ./config/elasticsearch/elasticsearch.yml:/usr/share/elasticsearch/config/elasticsearch.yml

      – esdata:/usr/share/elasticsearch/data

    ports: [‘9200:9200’]

    healthcheck:

      test: [“CMD”, “curl”,”-s” ,”-f”, “http://localhost:9200/_cat/health”]

    networks: [‘stack’]

 #Kibana container

  kibana:

    container_name: kibana

    hostname: kibana

    image: “docker.elastic.co/kibana/kibana:7.1.1”

    logging:

      options:

        max-file: “3”

        max-size: “50m”

    volumes:

      – ./config/kibana/kibana.yml:/usr/share/kibana/config/kibana.yml

    ports: [‘5601:5601’]

    networks: [‘stack’]

    depends_on:

      elasticsearch: { condition: service_healthy }

    restart: on-failure

    healthcheck:

      test: [“CMD”, “curl”, “-s”, “-f”, “http://localhost:5601/”]

      retries: 6

volumes:

  esdata:

    driver: local

  reportdata:

    driver: local

networks: {stack: {}}

This Compose file defines three services, Skedler Reports, Elasticsearch and Kibana.

Step 2: Basic configurations using reporting.yml and kibana.yml

Create a files called reporting.yml in your project directory.

Getting the reporting.yml file found here

Note: For more configuration options kindly refer the article reporting.yml and ReportEngineOptions Configuration

Create a files called kibana.yml in your project directory.

Note: For more configuration options kindly refer the article kibana.yml

Step 3: Build and run your app with docker-compose

From your project directory, start up your application by running

sudo docker-compose up -d

Compose pulls a Skedler Reports, Elasticsearch and Kibana images, builds an image for your code, and starts the services you defined

Skedler Reports is available at http://<hostIP>:3000,  Elasticsearch is available at http://<hostIP>:9200 and Kibana is available at http://<hostIP>:5601 .

Summary

Docker compose is a useful tool to manage container stacks for your client. And manage all related containers with one single command.