Skip to main content

Command Palette

Search for a command to run...

Day 11:Deploying ELK Stack on Docker Swarm Cluster

Published
โ€ข2 min read
Day 11:Deploying ELK Stack on Docker Swarm Cluster
K

"Hello, I'm Kiran Pawar, a passionate Cloud and Devops Engineer with a strong background in cloud automation, configuration, and deployment. My journey in the world of technology has been a thrilling adventure, where I've had the privilege to work with cutting-edge tools and practices.

๐Ÿš€ As a DevOps Engineer:

I specialize in automating, configuring, and deploying instances in cloud environments and data centers. My expertise extends to DevOps, GitOps, CI/CD pipeline management, HashiCorp Terraform, and containerization. I'm proficient in AWS and Linux/Unix administration, ensuring robust infrastructure and application performance.

๐Ÿ”ง My Tech Stack:

Front-end skills: HTML, CSS, SCSS, Tailwind CSS, Bootstrap, React, Material-UI, JavaScript DevOps toolbox: GIT, OWASP,Nexus,Trivy, Github, Gitlab, Terraform, Ansible, Docker, Kubernetes, Helm, Jenkins, Prometheus, Grafana, Argo CD, AWS EKS.

๐ŸŒ My Cloud Expertise:

I have hands-on experience managing AWS services, including EC2, S3, EBS, VPC, ELB, RDS, IAM, Route53, and more.

๐Ÿ”’ Networking and Security:

My skills include managing networking concepts such as TCP/IP protocols, security policies, and subnet interfacing. I have a strong understanding of infrastructure and networking, covering topics like firewalls, IP addressing, DNS, and more.

๐Ÿ’ก What Sets Me Apart:

I bring a positive attitude, a strong work ethic, and a collaborative spirit to every project. I'm a self-starter, a fast learner, and an effective team player with strong interpersonal skills. In addition to my DevOps skills, I've developed shell scripts (Bash) for automating tasks and have proficiency in Python scripting. My ability to communicate and manage projects, along with a track record of resolving client issues, adds value to every team I work with. If you're looking for a DevOps engineer who is also well-versed in front-end technologies, feel free to connect with me. Let's explore new possibilities and create exceptional technical solutions together!"

Introduction

In modern DevOps workflows, monitoring and logging play a crucial role in diagnosing issues and analyzing system performance. ELK Stack (Elasticsearch, Logstash, and Kibana) is a popular choice for log management. In this guide, we will deploy an ELK stack in a Docker Swarm Cluster to achieve scalable and fault-tolerant centralized logging.

Prerequisites

Before starting, ensure you have:

  • A Docker Swarm cluster (at least 1 manager and 2 worker nodes)

  • Docker & Docker Compose installed

  • At least 4GB RAM per node for optimal performance

  • Port 9200 (Elasticsearch) & 5601 (Kibana) open in firewall settings

Step 1: Create an Overlay Network

To allow communication between ELK services, create an overlay network:

$ docker network create --driver=overlay elk-network

Step 2: Deploy Elasticsearch

Create a file named elasticsearch.yml:

version: '3.8'
services:
  elasticsearch:
    image: docker.elastic.co/elasticsearch/elasticsearch:8.5.0
    environment:
      - discovery.type=single-node
      - bootstrap.memory_lock=true
      - xpack.security.enabled=false
    volumes:
      - elasticsearch-data:/usr/share/elasticsearch/data
    networks:
      - elk-network
    deploy:
      replicas: 1
      placement:
        constraints:
          - node.role == manager
volumes:
  elasticsearch-data:
networks:
  elk-network:
    external: true

Deploy Elasticsearch:

$ docker stack deploy -c elasticsearch.yml elk

Step 3: Deploy Logstash

Create a logstash.yml file:

version: '3.8'
services:
  logstash:
    image: docker.elastic.co/logstash/logstash:8.5.0
    volumes:
      - ./logstash.conf:/usr/share/logstash/pipeline/logstash.conf
    networks:
      - elk-network
    deploy:
      replicas: 1
volumes:
  logstash-data:
networks:
  elk-network:
    external: true

Create a logstash.conf pipeline configuration:

input {
  beats {
    port => 5044
  }
}

filter {
  mutate {
    remove_field => [ "@version" ]
  }
}

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

Deploy Logstash:

$ docker stack deploy -c logstash.yml elk

Step 4: Deploy Kibana

Create kibana.yml:

version: '3.8'
services:
  kibana:
    image: docker.elastic.co/kibana/kibana:8.5.0
    environment:
      - ELASTICSEARCH_HOSTS=http://elasticsearch:9200
    ports:
      - "5601:5601"
    networks:
      - elk-network
    deploy:
      replicas: 1
networks:
  elk-network:
    external: true

Deploy Kibana:

$ docker stack deploy -c kibana.yml elk

Step 5: Verify the Deployment

  1. Check running services:

     $ docker service ls
    
  2. Access Kibana at: http://<manager-node-ip>:5601

  3. Navigate to Index Management in Kibana and verify indices.

Step 6: Sending Logs to ELK

To send logs from a Docker container to Logstash, install Filebeat:

docker run --rm --network=elk-network \
  -v /var/lib/docker/containers:/var/lib/docker/containers:ro \
  -v /var/run/docker.sock:/var/run/docker.sock \
  docker.elastic.co/beats/filebeat:8.5.0 \
  -E output.logstash.hosts=["logstash:5044"]

Conclusion

You have successfully deployed the ELK stack in a Docker Swarm cluster for centralized logging. This setup helps in aggregating logs from multiple containers and visualizing them in Kibana. For production, consider enabling security settings, persistent storage, and load balancing.


Next Steps

  • Integrate with Traefik for Ingress control

  • Set up Loki and Promtail for advanced log management

  • Automate deployment using Terraform

Stay tuned for more DevOps tutorials! ๐Ÿš€

More from this blog

Kiran Pawar's Blog

122 posts