elasticompose

Objective:

Efficiently deploy and manage the ELK (Elasticsearch, Logstash, Kibana) stack using Docker Compose, enabling streamlined logging and monitoring solutions for various applications and environments.

Components:

1. Elasticsearch

Serves as the search and analytics engine, storing and indexing log data for quick and efficient retrieval.

2. Logstash

Collects, processes, and transforms log data before sending it to Elasticsearch.

3. Kibana

Visualizes data stored in Elasticsearch through customizable dashboards and graphs.

4. Filebeat

Lightweight shipper for forwarding and centralizing log data to Logstash and Elasticsearch.

5. Docker

Containerizes the entire ELK stack, making it easy to deploy, manage, and scale.

Pre-requisites:

Ensure Docker is installed on your system.
Docker Compose is required to manage multi-container Docker applications. Install Docker Compose to orchestrate the ELK stack services.
At least 4GB of RAM is recommended to run the ELK stack smoothly.
Ensure you have the necessary permissions to install software and manage Docker containers on your system.

.env Configuration

Since there are some secret credentials that need to stay hidden they have been added inside the .env file. This is an example of the contents inside the file:

ELASTIC_VERSION=[string]
ELASTIC_PASSWORD=[string]
KIBANA_SYSTEM_PASSWORD=[string]
LOGSTASH_INTERNAL_PASSWORD=[string]
FILEBEAT_INTERNAL_PASSWORD=[string]

Steps:

1. Set Up the Environment

Install Docker and Docker Compose on your system and ensure your system meets the memory, CPU, and storage requirements.

2. Prepare Configuration Files:

Create or obtain configuration files for Elasticsearch, Logstash, Kibana, and Filebeat and ensure these files are tailored to your specific needs, such as log paths and indices.

3. Create a Docker Compose File:

Define a docker-compose.yml file to orchestrate the ELK stack services. Include configurations for Elasticsearch, Logstash, Kibana, and Filebeat in the file.

4. Start the ELK Stack:

Navigate to the directory containing your docker-compose.yml file and run the docker-compose up -d command to start the ELK Stack services in detached mode.

5. Verify Service Availability:

Check the status of the ELK stack services using the docker-compose ps command. Use curl or a web browser to verify that Elasticsearch and Kibana are accessible.

6. Set Up User Authentication:

Access the Elasticsearch container using the docker exec -it elasticsearch /bin/bash command.

7. Configure Kibana:

Log in to Kibana using the elastic user credentials and set up index patterns and visualizations to monitor and analyze your data.

8. Test the Setup:

Send sample log data to ensure the entire pipeline (Filebeat -> Logstash -> Elasticsearch -> Kibana) is working correctly and verify that logs are being indexed in Elasticsearch and visualized in Kibana.