DevOps from Scratch: CI/CD, Docker, Monitoring in 30 Days — Step-by-Step Plan

DevOps from Scratch: CI/CD, Docker, Monitoring in 30 Days — Step-by-Step Plan

In the modern IT industry, DevOps has become not just a buzzword but a necessity for fast and stable software delivery. Whether you are a developer, system administrator, or simply want to master a sought-after specialty, this plan will help you move from theory to practice in 30 days. We will break down key components: containerization with Docker, build and deployment automation via CI/CD, as well as setting up monitoring and logging. Get ready for an intensive but exciting journey.

Week 1: DevOps Basics and Docker

The first week is dedicated to the foundation. Start by understanding the DevOps philosophy: it's not just tools, but a culture of collaboration between development and operations. Learn the principles of continuous integration (CI) and continuous delivery (CD), and get acquainted with the concept of infrastructure as code.

Day 1-2: Theory and Environment Setup

• Install Git, Docker Desktop (or Docker Engine for Linux).
• Learn basic Docker commands: docker run, docker ps, docker build.
• Create a simple Dockerfile for a web application (e.g., Python Flask).

Day 3-5: Diving into Docker

• Master working with Docker Compose to run multi-container applications (e.g., web server + database).
• Experiment with networks and volumes for data storage.
• Example: write a docker-compose.yml that spins up Nginx and PostgreSQL.

Day 6-7: Practice and Refactoring

• Optimize the Dockerfile (multi-stage builds, minimizing layers).
• Run the application locally and ensure everything works.

Week 2: CI/CD Pipelines

In the second week, you will automate build, testing, and deployment using CI/CD. This is the heart of DevOps, allowing you to deliver changes quickly and without errors.

Day 8-10: Tool Selection and First Pipeline

• Sign up for GitHub and create a repository.
• Set up GitHub Actions: write a simple workflow to build a Docker image and run tests.
• Alternative: GitLab CI/CD — learn the basic .gitlab-ci.yml.

Day 11-13: Integration with Docker

• Add a stage to the pipeline for publishing the image to Docker Hub.
• Implement automatic deployment to a test server (e.g., via SSH or using Docker Compose).
• Example: after a push to the main branch, the pipeline builds the image, pushes it to the registry, and deploys it to the server.

Day 14: Analysis and Improvement

• Check pipeline logs, fix errors. Add notifications to Slack or Telegram.

Week 3: Monitoring and Logging

The third week is about seeing what is happening with your application. Monitoring and logging are key to stability in production.

Day 15-17: Setting Up Monitoring

• Install Prometheus and Node Exporter for collecting metrics (CPU, memory, disk).
• Set up dashboards in Grafana: create a simple CPU load graph.
• Example: docker-compose with Prometheus, Grafana, and Node Exporter.

Day 18-20: Logging with the ELK Stack

• Deploy Elasticsearch, Logstash, Kibana (or use a lighter setup Loki + Promtail).
• Configure the application to send logs to Logstash via the Docker driver.
• In Kibana, create a visualization of errors over time.

Day 21: Integration with Alerting System

• Set up Alertmanager in Prometheus to send alerts (e.g., if CPU > 90%).
• Verify that alerts arrive via email.

Week 4: Infrastructure as Code and Final Project

The last week — combine everything into a single pipeline using IaC (Infrastructure as Code).

Day 22-24: Terraform for Infrastructure Management

• Install Terraform and a provider for a cloud service (AWS, Yandex Cloud, or DigitalOcean).
• Write a configuration to create a virtual machine and install Docker.
• Example: main.tf with an aws_instance resource and a provisioner for Docker installation.

Day 25-27: Final Project

• Create a simple application (e.g., a TODO list).
• Set up the full cycle: Docker