Practical DevOps Bootcamp for All

Packt via Coursera Specialization

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This specialization features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the specialization. This specialization offers hands-on experience with the full DevOps lifecycle, from version control to cloud infrastructure and containerization. You’ll work with industry tools like Git, Docker, Kubernetes, AWS, Prometheus, and ArgoCD, gaining the skills to automate and manage software development workflows. By the end, you’ll be ready to apply DevOps practices in real-world environments. The journey starts with CI/CD concepts and progresses through cloud infrastructure with AWS and containerization with Docker. You’ll also learn Kubernetes orchestration and application deployment at scale, along with monitoring tools like Prometheus and Grafana to manage performance. The specialization is ideal for software engineers, system administrators, and anyone looking to automate software deployment. Basic programming and cloud knowledge is helpful, but not required. By the end of the specialization, you will be able to automate CI/CD pipelines using GitHub Actions, deploy applications with Kubernetes, manage AWS infrastructure, and monitor performance with Prometheus and Grafana.

Syllabus

Course 1: DevOps Foundations & Development Workflow
Course 2: Containerization and Kubernetes for DevOps
Course 3: DevOps Automation, Monitoring & GitOps

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This course features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. This comprehensive course delves into containerization with Docker and orchestration using Kubernetes, providing the essential tools for DevOps success. You'll learn the fundamentals of Docker, from container creation to managing Docker images and containers using CLI. After covering Docker, you'll transition into Kubernetes, exploring how to manage containers at scale, set up clusters, and configure services like ClusterIP, NodePort, and LoadBalancer for efficient communication between pods. Throughout the course, you’ll gain hands-on experience with Docker and Kubernetes, including demonstrations on containerizing Python Flask apps and deploying them on Kubernetes. You'll also learn essential troubleshooting techniques, Kubernetes object management, and YAML configuration. The course is designed to help you master container orchestration and manage scalable applications in a DevOps environment. Ideal for DevOps engineers, system administrators, and developers, this course requires basic knowledge of programming and Docker. You'll explore both cloud and on-premise Kubernetes configurations, preparing you for real-world applications. By the end of the course, you will be able to build Docker containers, manage Kubernetes clusters, deploy scalable applications, and troubleshoot containerized environments efficiently.
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This course features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. This course offers a deep dive into DevOps automation, monitoring, and GitOps. Starting with Prometheus, you'll explore how to collect and store monitoring data, then use Grafana for visualizing metrics and building dashboards. Moving to GitOps, you'll learn how ArgoCD simplifies Kubernetes application deployment by automating continuous delivery. You'll also get hands-on experience automating CI/CD pipelines using GitHub Actions. You'll start by mastering monitoring and visualization with Prometheus and Grafana, then proceed to set up GitOps workflows using ArgoCD for Kubernetes deployments. The course wraps up with CI/CD automation via GitHub Actions, covering testing, building, and deploying software with ease. Practical demonstrations at each step ensure you gain the skills needed to apply these techniques in real-world DevOps environments. The course is designed for DevOps engineers, system administrators, and developers who want to automate and streamline their workflows. A basic understanding of Kubernetes, Docker, and Git is recommended for maximum benefit. By the end of the course, you will be able to set up Prometheus and Grafana for monitoring, automate continuous delivery with GitOps and ArgoCD, and create end-to-end CI/CD pipelines using GitHub Actions.
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This course features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. Embark on a comprehensive journey through DevOps principles and workflows. This course will introduce you to essential concepts such as CI/CD, version control, cloud infrastructure, and Linux systems. The course begins with an introduction to DevOps and CI/CD, where you’ll learn the importance of automation and continuous delivery. You’ll explore the stages of the DevOps lifecycle and set up your development environment to begin practical workflows. The course then covers planning with GitHub Projects and Issues, integrating agile practices and real-time project management tools to keep your work organized. You'll dive into Python application fundamentals, learning the basics of Python programming, scripting, and web app development with Flask. You’ll also gain valuable skills in version control with Git, including best practices for branching, merging, and managing teams. As you progress, you'll work with cloud computing on AWS, learning to deploy virtual servers, launch EC2 instances, and manage infrastructure. Targeted at anyone interested in getting started DevOps, this course is ideal for aspiring developers, system administrators, and DevOps engineers. No prior experience with DevOps is necessary, but familiarity with basic programming concepts and Git will be helpful. By the end of the course, you will be able to automate DevOps workflows, manage cloud infrastructure with AWS, deploy applications with Python and Flask, and implement CI/CD pipelines using GitHub and Git.