Set up Kubernetes clusters and deploy applications to ensure high availability.
Configure horizontal pod autoscaling to manage traffic spikes and optimise resource utilisation.
Implement and test failure recovery strategies to maintain service uptime and reliability.

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授课语言：英语（English）

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关于此指导项目

In this 1-hour long project-based course, you will learn how to set up Kubernetes clusters and deploy applications to ensure high availability, configure horizontal pod autoscaling to manage traffic spikes and optimise resource utilisation and finally implement and test failure recovery strategies to maintain service uptime and reliability. We will do this by deploying an e-commerce application.

By the end of this project, you’ll know how to deploy and manage scalable, high-availability web services with Kubernetes. This project is ideal for developers, DevOps engineers, and anyone looking to master container orchestration for resilient infrastructure. Some experience with containers, command-line operations, networking, and YAML files is recommended. Learners should understand basic containerization concepts, be comfortable using the command line, have a foundational knowledge of networking, and be able to read and write YAML files. Access to a computer with Minikube or a similar Kubernetes tool and a stable internet connection is required.

分步进行学习

在与您的工作区一起在分屏中播放的视频中，您的授课教师将指导您完成每个步骤：

Learners will set up Minikube and kubectl to create a functional Kubernetes environment. They will verify the installation, start a cluster, and ensure connectivity.
Learners will deploy a simple Nginx application on Kubernetes using a Deployment YAML file. They will expose the application externally and verify accessibility through a NodePort service.
Learners will enable horizontal pod autoscaling (HPA) to dynamically adjust the number of pods based on CPU usage. They will observe how Kubernetes scales resources in response to workload changes.
Learners will modify and test different autoscaling thresholds to understand their impact on resource allocation. They will adjust CPU utilisation targets and analyse how Kubernetes reacts to this.
Learners will implement resource requests, limits, and affinity rules to optimize workload distribution. They will configure pod scheduling preferences to improve performance and resource efficiency.
Learners will simulate node failures and analyze Kubernetes’ self-healing capabilities. They will observe how pods are rescheduled to healthy nodes, ensuring application availability.
Learners will deploy and scale a web application with horizontal pod autoscaling and resource limits. They will test the application’s resilience under simulated high traffic conditions.