Elastic search container VS no container - unix1998/technical_notes GitHub Wiki

Whether to use Elasticsearch with containers or to install it directly on the OS depends on various factors, including your infrastructure, operational practices, and specific requirements. Here are the pros and cons of each approach:

Using Containers

Pros:

  1. Isolation: Containers provide a level of isolation that helps prevent conflicts with other applications on the same host.
  2. Portability: Containers can be easily moved between different environments (development, staging, production) without changes.
  3. Scalability: Containers can be easily scaled up or down using container orchestration platforms like Kubernetes.
  4. Consistency: Ensures that the application runs in the same environment across different stages, reducing the "it works on my machine" issue.
  5. Resource Management: Container orchestrators provide advanced resource management and scheduling capabilities.

Cons:

  1. Complexity: Running Elasticsearch in containers, especially in a production environment, can add complexity to your setup.
  2. Performance Overhead: Containers may introduce some performance overhead compared to running directly on the host OS.
  3. Storage Management: Managing persistent storage for Elasticsearch data can be more challenging in a containerized environment.

Installing Directly on OS

Pros:

  1. Performance: Running Elasticsearch directly on the host OS can provide better performance with less overhead.
  2. Simplicity: Easier to set up and manage without the additional layer of containerization.
  3. Resource Utilization: Direct access to host resources without the abstraction layer of containers.

Cons:

  1. Lack of Isolation: Less isolation compared to containers, which can lead to conflicts with other applications.
  2. Portability: More difficult to move across different environments, as dependencies and configurations may vary.
  3. Scalability: Scaling can be more challenging and typically requires more manual intervention compared to container orchestrators.

Best Practices for Containerized Elasticsearch

If you choose to go with containers, consider the following best practices:

  1. Use Official Docker Images: Use the official Elasticsearch Docker images provided by Elastic. 
    docker pull docker.elastic.co/elasticsearch/elasticsearch:7.17.0
  2. Stateful Workloads: Use Kubernetes StatefulSets for managing Elasticsearch nodes, as they handle stateful workloads well.
  3. Persistent Storage: Use persistent volumes (PVs) and persistent volume claims (PVCs) to manage storage for Elasticsearch data.
  4. Resource Requests and Limits: Define resource requests and limits for Elasticsearch containers to ensure they have enough resources to function properly.
  5. Cluster Configuration: Use Kubernetes ConfigMaps or Secrets to manage Elasticsearch configuration.
  6. Networking: Ensure proper network configuration and DNS resolution for the Elasticsearch cluster nodes.

Example Docker Compose for Elasticsearch

If you're not using Kubernetes, you can use Docker Compose to set up a multi-node Elasticsearch cluster:

version: '3.7'
services:
  es01:
    image: docker.elastic.co/elasticsearch/elasticsearch:7.17.0
    container_name: es01
    environment:
      - node.name=es01
      - cluster.name=es-docker-cluster
      - discovery.seed_hosts=es02,es03
      - cluster.initial_master_nodes=es01,es02,es03
      - bootstrap.memory_lock=true
      - "ES_JAVA_OPTS=-Xms1g -Xmx1g"
    ulimits:
      memlock:
        soft: -1
        hard: -1
    volumes:
      - esdata01:/usr/share/elasticsearch/data
    ports:
      - 9200:9200
    networks:
      - esnet

  es02:
    image: docker.elastic.co/elasticsearch/elasticsearch:7.17.0
    container_name: es02
    environment:
      - node.name=es02
      - cluster.name=es-docker-cluster
      - discovery.seed_hosts=es01,es03
      - cluster.initial_master_nodes=es01,es02,es03
      - bootstrap.memory_lock=true
      - "ES_JAVA_OPTS=-Xms1g -Xmx1g"
    ulimits:
      memlock:
        soft: -1
        hard: -1
    volumes:
      - esdata02:/usr/share/elasticsearch/data
    networks:
      - esnet

  es03:
    image: docker.elastic.co/elasticsearch/elasticsearch:7.17.0
    container_name: es03
    environment:
      - node.name=es03
      - cluster.name=es-docker-cluster
      - discovery.seed_hosts=es01,es02
      - cluster.initial_master_nodes=es01,es02,es03
      - bootstrap.memory_lock=true
      - "ES_JAVA_OPTS=-Xms1g -Xmx1g"
    ulimits:
      memlock:
        soft: -1
        hard: -1
    volumes:
      - esdata03:/usr/share/elasticsearch/data
    networks:
      - esnet

volumes:
  esdata01:
    driver: local
  esdata02:
    driver: local
  esdata03:
    driver: local

networks:
  esnet:

In conclusion, both approaches have their merits. Containers provide flexibility, scalability, and portability, while installing directly on the OS offers simplicity and performance. The best choice depends on your specific needs and existing infrastructure.