Welcome to the DevOps Essentials repository! This guide is designed to help you expand your knowledge and skills in DevOps. Whether you're a network or a system engineer looking to enhance your expertise or a beginner exploring the world of DevOps, this repository provides step-by-step guidance, practical exercises, and best practices to empower you in the DevOps domain.
- Continuous Integration (CI)
- Continuous Delivery/Deployment (CD)
- Infrastructure as Code (IaC)
- Containerization
- Monitoring
- Contributions
- License
Continuous Integration involves the frequent integration of code changes into a shared repository. The main goal is to catch integration issues early by running automated tests against the codebase. This practice ensures that the codebase remains stable and minimizes conflicts when multiple developers are working on the same project.
To set up a CI pipeline, we can use Jenkins, an open-source automation server. Jenkins allows you to automate the build, test, and integration processes by defining pipelines as code. It supports a wide range of plugins for integrating with different version control systems, build tools, and testing frameworks.
Follow this exercise to learn how to set up a CI pipeline with Jenkins. By the end of this exercise, you'll have a working CI pipeline that automates the build and test processes for your project.
Continuous Delivery expands on CI by automating the process of deploying applications to various environments, such as development, staging, and production. The goal is to ensure that the software is always in a releasable state and can be deployed with minimal effort.
There are various tools available for implementing CD, and one popular option is GitLab CI/CD. It provides a comprehensive platform for managing source code repositories, running CI pipelines, and deploying applications. GitLab CI/CD integrates tightly with GitLab and offers a range of features like automatic environment creation, deployment strategies, and manual approval gates.
Follow this exercise to learn how to implement continuous delivery with GitLab CI/CD. By the end of this exercise, you'll have a CI/CD pipeline set up for your project, enabling automated deployments to different environments.
Infrastructure as Code (IaC) is a practice that involves managing infrastructure resources, such as servers, networks, and storage, using code. By treating infrastructure as code, you can version control your infrastructure configurations, automate the provisioning process, and ensure consistency across environments.
Ansible, a powerful IaC tool, uses YAML-based configuration files called playbooks to describe the desired state of the infrastructure. Ansible playbooks allow you to automate the deployment and configuration of servers, install software packages, manage users and permissions, and perform other infrastructure-related tasks.
Follow this exercise to learn advanced Ansible concepts such as role-based development and leveraging Ansible Galaxy for reusable roles. By the end of this exercise, you'll have a deeper understanding of Ansible's capabilities and be able to create more modular and efficient infrastructure automation workflows.
Terraform is another popular IaC tool that allows you to define and provision infrastructure resources using a declarative language. With Terraform, you can automate the provisioning of virtual machines, networks, storage, and more across various cloud providers. Terraform provides a consistent and reproducible way to manage infrastructure and simplifies the process of creating and modifying infrastructure resources.
Follow this exercise to learn how to provision infrastructure resources using Terraform. By the end of this exercise, you'll have hands-on experience with defining infrastructure configurations, creating and managing infrastructure resources in your preferred cloud environment.
Docker is a popular platform for developing, shipping, and running applications in containers. It allows you to package your application and its dependencies into a container image, ensuring consistency across different environments.
Follow this exercise to learn the basics of Docker, including how to create, run, and manage containers. By the end of this exercise, you'll be familiar with Docker and its core concepts.
Kubernetes is an open-source container orchestration platform that automates the deployment, scaling, and management of containerized applications. It provides a robust and flexible infrastructure for running distributed systems and microservices.
Follow this exercise to learn the fundamentals of Kubernetes, including how to deploy applications, manage pods, and scale resources. By the end of this exercise, you'll have a working knowledge of Kubernetes and be able to deploy and manage applications in a Kubernetes cluster.
Monitoring is a critical aspect of DevOps as it ensures the health and performance of applications and infrastructure. Prometheus, a popular choice in the DevOps ecosystem, specializes in time-series data collection, querying, and alerting.
Prometheus collects metrics from various systems and services through exporters, which expose the relevant metrics in a format that Prometheus understands. It stores the collected metrics in a time-series database and provides a query language (PromQL) for retrieving and aggregating the metrics. Prometheus can also trigger alerts based on defined alerting rules.
Follow this exercise to learn how to implement monitoring with Prometheus. By the end of this exercise, you'll have Prometheus set up to collect and visualize metrics from your applications and infrastructure.
To visualize the collected metrics and create dashboards, we can integrate Prometheus with Grafana, a powerful open-source data visualization and monitoring tool. Grafana provides a user-friendly interface for creating customizable dashboards, exploring data, and setting up alerting. It allows you to create visualizations, such as graphs, charts, and tables, to gain insights into the performance and health of your systems.
Follow this exercise to learn how to create dashboards with Grafana. By the end of this exercise, you'll be able to build customized dashboards to monitor and visualize metrics from Prometheus.
We welcome contributions from the open-source community to enhance and improve this guide. If you find any issues, have suggestions for improvements, or would like to add new topics, please feel free to open an issue or submit a pull request.
This repository is licensed under the MIT License.