Containerization and Orchestration

This course will take you on a journey from the fundamentals of containerization to advanced techniques in orchestration and monitoring, helping you build real-world expertise step by step. You will start with the basics of Docker, gradually progressing to orchestrating containers at scale with Kubernetes, and finally mastering container monitoring and visualization using Prometheus and Grafana. With a hands-on approach, this course covers everything from the fundamentals of containerization to deploying complex, multi-container applications, managing Kubernetes clusters, and implementing observability. You will gain the skills necessary to automate, monitor, and manage large-scale containerized environments. By the end of this course, you will be able to: • Understand the fundamentals of Docker and containerization • Create and manage Docker containers and images • Utilize Docker Compose for multi-container applications • Analyze the architecture of Kubernetes and deploy applications using Kubernetes. • Evaluate and scale Kubernetes clusters to meet application needs. • Design and implement observability solutions using Prometheus and Grafana to monitor containers and clusters. This course is designed for DevOps practitioners, system administrators, cloud engineers, and developers who want to deepen their expertise in containerization, orchestration, and monitoring. It’s perfect for those looking to enhance their ability to deploy, scale, and manage containerized applications in modern cloud-native environments while gaining proficiency in observability practices using tools like Prometheus and Grafana

• Create and manage containers and images with Docker to containerize applications effectively
• Deploy, scale, and manage containerized applications using Kubernetes in a cluster environment
• Orchestrate and manage multi-container applications with Docker Compose and Kubernetes for scalability and efficiency
• Set up Prometheus and Grafana to monitor and visualize container and cluster performance, ensuring system reliability

• Basic familiarity with the topic and its common terminology
• Readiness to practice through applied exercises or case-based work