ELK

Prerequisites

docker.elastic.co/elasticsearch/elasticsearch   8.5.0     65719a2cfaea   2 years ago     1.29GB
docker.elastic.co/logstash/logstash             8.5.0     df0e328413e1   2 years ago     753MB
docker.elastic.co/kibana/kibana                 8.5.0     4737b8e943ba   2 years ago     715MB

To deploy an ELK Stack using the Docker images have provided for Elasticsearch, Logstash, and Kibana, you can follow these steps. I'll guide you through the process of deploying and connecting the three components (Elasticsearch, Logstash, and Kibana) using Docker.

1. Prerequisites

Ensure you have Docker installed and running on your machine.
You should have the Docker images for elasticsearch, logstash, and kibana available (the versions you've mentioned).
Make sure to allocate sufficient resources (RAM, CPU) for Elasticsearch (it can be resource-intensive).

2. Create a Docker Network

First, create a custom Docker network so that the three containers can communicate with each other:

docker network create elk

3. Deploy Elasticsearch Container

Elasticsearch is the central component of the ELK stack and needs to be set up first. Here's how to deploy it:

docker run -d --name elasticsearch \
  --network elk \
  -e "discovery.type=single-node" \
  -e "ES_JAVA_OPTS=-Xms2g -Xmx2g" \
  -p 9200:9200 \
  docker.elastic.co/elasticsearch/elasticsearch:8.5.0

Explanation of the flags:

--name elasticsearch: The name of the container.
--network elk: Connects the container to the elk network.
-e "discovery.type=single-node": This option makes Elasticsearch run as a single node (important for local setups).
-e "ES_JAVA_OPTS=-Xms2g -Xmx2g": Allocates memory (2 GB for both min and max).
-p 9200:9200: Exposes port 9200 for Elasticsearch's REST API.
docker.elastic.co/elasticsearch/elasticsearch:8.5.0: Specifies the Elasticsearch Docker image.

4. Deploy Logstash Container

Logstash is used to process logs and send them to Elasticsearch. Here’s how to deploy it:

docker run -d --name logstash \
  --network elk \
  -p 5044:5044 \
  -e "LOGSTASH_JAVA_OPTS=-Xms1g -Xmx1g" \
  docker.elastic.co/logstash/logstash:8.5.0

Explanation of the flags:

--name logstash: The name of the container.
--network elk: Connects the container to the elk network.
-p 5044:5044: Exposes port 5044 for Logstash’s Beats input (e.g., Filebeat).
-e "LOGSTASH_JAVA_OPTS=-Xms1g -Xmx1g": Allocates memory (1 GB for both min and max).
docker.elastic.co/logstash/logstash:8.5.0: Specifies the Logstash Docker image.

You can also mount your Logstash configuration file (logstash.conf) if needed, for example:

docker run -d --name logstash \
  --network elk \
  -v /path/to/logstash.conf:/usr/share/logstash/pipeline/logstash.conf \
  -p 5044:5044 \
  docker.elastic.co/logstash/logstash:8.5.0

Make sure to configure logstash.conf for your input (e.g., Filebeat), filter, and output (Elasticsearch).

5. Deploy Kibana Container

Kibana is used for data visualization in the ELK stack. Here's how to deploy it:

docker run -d --name kibana \
  --network elk \
  -p 5601:5601 \
  docker.elastic.co/kibana/kibana:8.5.0

Explanation of the flags:

--name kibana: The name of the container.
--network elk: Connects the container to the elk network.
-p 5601:5601: Exposes port 5601 for Kibana's web interface.
docker.elastic.co/kibana/kibana:8.5.0: Specifies the Kibana Docker image.

6. Verify the Deployment

Once all containers are running, check their status:
```
docker ps
```
You should see the Elasticsearch, Logstash, and Kibana containers running.
Elasticsearch should be accessible at http://localhost:9200. You can verify it by making a request:
```
curl http://localhost:9200
```
It should return JSON data about your Elasticsearch node.
Kibana should be accessible at http://localhost:5601. Open this in your browser, and you should see the Kibana web interface.

7. Configure Logstash Input and Output

If you're planning to use Filebeat or any other log shipper, you will need to configure Logstash with the appropriate input and output settings. For example, you can configure Logstash to receive logs from Filebeat and forward them to Elasticsearch.

Here’s an example logstash.conf:

input {
  beats {
    port => 5044
  }
}

filter {
  # Custom filtering (if necessary)
}

output {
  elasticsearch {
    hosts => ["http://elasticsearch:9200"]
    index => "logstash-%{+YYYY.MM.dd}"
  }
}

You can mount this configuration file into the Logstash container using the -v flag.

8. Access Kibana and Explore Data

Once Kibana is up and running, you can access it via the browser at http://localhost:5601. Here, you can set up index patterns, explore your logs, and create visualizations and dashboards based on the data sent from Logstash.

To simplify the deployment of the ELK Stack using Docker, you can create a docker-compose.yml file. This YAML file will allow you to define and configure all the required services (Elasticsearch, Logstash, and Kibana) in a single file, and then spin them up using the docker-compose command.

Here’s a step-by-step guide to create the docker-compose.yml file for your ELK stack and deploy it:

1. Create a `docker-compose.yml` File

First, create a new directory for your ELK Stack project:

mkdir elk-stack
cd elk-stack

Now, create a file called docker-compose.yml inside this directory:

touch docker-compose.yml

Edit the docker-compose.yml file with the following content:

yamlCopyversion: '3'
services:
  elasticsearch:
    image: docker.elastic.co/elasticsearch/elasticsearch:8.5.0
    container_name: elasticsearch
    environment:
      - discovery.type=single-node
      - ES_JAVA_OPTS=-Xms2g -Xmx2g
    networks:
      - elk
    ports:
      - "9200:9200"
    volumes:
      - elasticsearch-data:/usr/share/elasticsearch/data
    ulimits:
      memlock:
        soft: -1
        hard: -1

  logstash:
    image: docker.elastic.co/logstash/logstash:8.5.0
    container_name: logstash
    environment:
      - LOGSTASH_JAVA_OPTS=-Xms1g -Xmx1g
    networks:
      - elk
    ports:
      - "5044:5044"
    volumes:
      - ./logstash/config/logstash.conf:/usr/share/logstash/pipeline/logstash.conf
    depends_on:
      - elasticsearch

  kibana:
    image: docker.elastic.co/kibana/kibana:8.5.0
    container_name: kibana
    networks:
      - elk
    ports:
      - "5601:5601"
    depends_on:
      - elasticsearch

networks:
  elk:
    driver: bridge

volumes:
  elasticsearch-data:
    driver: local

Explanation of the Configuration:

version: '3': The version of the Docker Compose file format (version 3 is commonly used).
services: Defines the services (Elasticsearch, Logstash, and Kibana) that will be spun up.
- Elasticsearch:
  - The discovery.type=single-node is for single-node Elasticsearch deployments (for local environments).
  - The ES_JAVA_OPTS=-Xms2g -Xmx2g configures Java heap memory.
  - It exposes port 9200 for communication.
  - Data is stored in a Docker volume called elasticsearch-data.
- Logstash:
  - The logstash.conf configuration file is mounted into the container for custom processing rules (you’ll need to create this configuration).
  - Exposes port 5044 for receiving log data from filebeat (or any other log shipper).
  - depends_on ensures Logstash starts after Elasticsearch is ready.
- Kibana:
  - Exposes port 5601 for the Kibana web interface.
  - depends_on ensures Kibana starts after Elasticsearch is ready.
networks: All services are connected to a custom Docker bridge network called elk so that they can communicate with each other.
volumes: Elasticsearch data is stored in a named volume (elasticsearch-data), so it persists even if the container is stopped or removed.

2. Create the Logstash Configuration File

Now, create the Logstash pipeline configuration file in the logstash/config directory. You can use the following command to create the directory and configuration file:

mkdir -p logstash/config
touch logstash/config/logstash.conf

Edit the logstash.conf file and add the following basic configuration (or customize it based on your needs):

plaintextCopyinput {
  beats {
    port => 5044
  }
}

filter {
  # Your filter configuration (optional)
}

output {
  elasticsearch {
    hosts => ["http://elasticsearch:9200"]
    index => "logstash-%{+YYYY.MM.dd}"
  }
}

This configuration tells Logstash to listen for log data from Beats (e.g., Filebeat) on port 5044 and send the data to Elasticsearch. The logs will be indexed with the logstash-* pattern in Elasticsearch.

3. Spin Up the Containers with Docker Compose

Now that your docker-compose.yml and Logstash configuration are ready, use Docker Compose to spin up the containers.

From the directory containing the docker-compose.yml file, run:

docker-compose up -d

This will:

Pull the Docker images for Elasticsearch, Logstash, and Kibana.
Create and start the containers.
Attach the containers to the custom Docker network (elk).

4. Verify the Deployment

You can check if everything is running correctly using:

docker ps

You should see all three containers running (Elasticsearch, Logstash, and Kibana).

5. Access Kibana

Once the containers are up and running, open your web browser and go to:

http://localhost:5601

This will open the Kibana web interface where you can interact with the data stored in Elasticsearch, configure dashboards, create visualizations, and explore logs.

6. Shutting Down the Stack

To stop and remove the containers, run:

docker-compose down

This will stop the containers and remove them. If you want to remove the volumes as well (which deletes your Elasticsearch data), run:

docker-compose down -v

Additional Customization

You can customize the Logstash pipeline configuration further based on your needs (e.g., different input/output plugins or filters).
You can also tweak the memory settings for Elasticsearch and Logstash if needed.

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Last updated 8 months ago

1. Prerequisites

2. Create a Docker Network

3. Deploy Elasticsearch Container

4. Deploy Logstash Container

5. Deploy Kibana Container

6. Verify the Deployment

7. Configure Logstash Input and Output

8. Access Kibana and Explore Data

1. Create a docker-compose.yml File

Explanation of the Configuration:

2. Create the Logstash Configuration File

3. Spin Up the Containers with Docker Compose

4. Verify the Deployment

5. Access Kibana

6. Shutting Down the Stack

Additional Customization

1. Create a `docker-compose.yml` File