Kubernetes Workloads

Course Description

This course is designed to take you beyond the basics of Kubernetes and into the world of effectively managing application workloads. Through a series of hands-on labs, you will master the creation and management of Pods, the foundational unit of Kubernetes. You'll then learn to ensure high availability with ReplicaSets and orchestrate seamless application rollouts and rollbacks using Deployments. A key focus of the course is on building resilient, scalable systems, covering everything from self-healing mechanisms to configuring the Horizontal Pod Autoscaler (HPA). By the end, you'll be equipped with advanced skills, including multi-container pod patterns, and the confidence to manage complex, production-grade applications on Kubernetes.

Who is this course for

This is an intermediate-level course for individuals who understand the fundamental architecture of Kubernetes and are ready to learn how to deploy and manage applications on the platform. It is ideal for:

• DevOps Engineers & SREs: Who are responsible for building and maintaining CI/CD pipelines and production Kubernetes clusters.

• Cloud Engineers & System Administrators: Who manage infrastructure and deploy applications on Kubernetes.

• Software Developers: Who need to understand how to package and run their applications effectively in a Kubernetes environment.

Course Objectives

Upon successful completion of this course, you will be able to:

• Manage Pods: Create, manage, and debug Kubernetes Pods using YAML manifests.

• Organize Resources: Use labels, selectors, and annotations to effectively manage and organize Kubernetes resources.

• Implement Deployments: Create and manage Deployments to ensure application availability and orchestrate rolling updates.

• Perform Seamless Rollbacks: Confidently roll back a Deployment to a previous stable version to minimize downtime.

• Auto-scale Applications: Configure a Horizontal Pod Autoscaler (HPA) to automatically scale your applications based on resource utilization.

• Design Advanced Pods: Implement multi-container pod patterns, such as the init container pattern, for more complex application needs.

Prerequisites

To succeed in this course, you must have:

1. A Solid Foundation in Kubernetes: You should understand the core architecture of Kubernetes (control plane, nodes) and be proficient with basic kubectl commands.

2. Command-Line Proficiency: You must be comfortable working in a terminal or command prompt.

3. A Working Kubernetes Cluster: You need access to a Kubernetes environment (like Minikube, kind, or a cloud-based cluster) to perform the hands-on labs.

Course outline

Section 1: Pods Creation and Management

1. Introduction to Pods

2. The Pod Specification YAML File

3. Hands-on Lab: Creating an Nginx Pod in Kubernetes

4. Debugging Pods: Common Errors and Their Causes

5. Hands-on Lab: Debugging Kubernetes Scenarios

Section 2: Managing Kubernetes Resource Configurations

1. Kubernetes Labels and Selectors

2. Code Example: Using Kubernetes Annotations

Section 3: ReplicaSets

1. Role of the ReplicaSet

Section 4: Deployments in Kubernetes

1. Introduction to Kubernetes Deployments

2. Code Example: YAML Configuration for Deployments

3. Hands-on Lab: Creating an Nginx Deployment in Kubernetes

4. Desired State vs. Current State in Kubernetes

5. Self-healing vs. Auto-scaling in Kubernetes

Section 5: Deployments Rollback in Kubernetes

1. Understanding Rollbacks in Deployments

2. Different Aspects of Rollbacks

3. Hands-on Lab: Performing Rollbacks in Deployments

Section 6: Autoscaling in Kubernetes Using Deployments

1. Scaling Deployments in Kubernetes

2. Maintaining High Availability using maxUnavailable and maxSurge

3. Hands-on Lab: Horizontal Pod Autoscaler (HPA) in Kubernetes using Minikube

4. The Impact of Autoscaling on Performance

Section 7: Advanced Pod and Deployment Concepts

1. Multi-container Pods

2. Multi-container Pod Design Patterns

3. Hands-on Lab: Multi-Container Pod with an Init Container

4. Understanding Static Pods

Testimonials