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

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

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