In this module, we will explore what K8sGPT is and how it revolutionizes Kubernetes management. You'll gain insights into why K8sGPT was created and the benefits it offers, followed by a detailed overview of its workflow. A practical demonstration will show you how K8sGPT enhances documentation, ensuring you grasp both theoretical and practical aspects of the tool.

In this module, we will guide you through the necessary steps to set up your environment for using K8sGPT. You'll learn about the prerequisites for setting up K8sGPT, followed by detailed demonstrations of installing Kubernetes and K8sGPT on macOS and via an in-cluster operator. Additionally, we will walk you through how to use the K8sGPT CLI, enabling you to start working with K8sGPT effectively.

In this module, we will explore the core components that make up K8sGPT. You will gain an understanding of key terminologies like analyzers, filters, and AI-powered insights that form the backbone of K8sGPT's functionality. Additionally, we will walk you through the operating and process flow of K8sGPT, highlighting how these components work together to improve Kubernetes operations.

In this module, we will dive into the practical usage of K8sGPT commands through its CLI. You will learn how to utilize the "Analyze" and "Filter" commands to manage Kubernetes data effectively. We will also demonstrate how to integrate K8sGPT with powerful backends like Google Gemini and Amazon Bedrock. Additionally, you will explore advanced features like JSON output, data anonymization, and debugging techniques, empowering you to use K8sGPT with full control and efficiency.

In this module, we will introduce you to the integration capabilities of K8sGPT, starting with how to get started with integrations. You'll see a live demonstration of integrating K8sGPT with Prometheus, a popular monitoring tool. This module will highlight how such integrations can enhance the functionality of K8sGPT in your Kubernetes environment, providing deeper insights and better management of your infrastructure.

In this module, we will focus on real-time issue analysis using K8sGPT. You will explore a case study that showcases how K8sGPT can provide recommendations for improving Kubernetes dashboards. Additionally, we will demonstrate KubeBuddy, an AI-powered dashboard integrated with K8sGPT, showing how it can help you troubleshoot and resolve Kubernetes issues effectively in real-time.

In this module, we will dive into the use of the in-cluster operator to manage K8sGPT within Kubernetes clusters. You will learn how to configure K8sGPT by adding a cluster resource through a manifest file, and we will walk through a demonstration of integrating Prometheus and Grafana for real-time monitoring. This module will give you hands-on experience in using K8sGPT within Kubernetes clusters, optimizing your management and observability processes.

In this module, we will showcase how to integrate K8sGPT with Claude Desktop, enhancing your ability to manage and interact with Kubernetes clusters through a seamless desktop interface. This demonstration will provide you with the tools to effectively use K8sGPT alongside Claude Desktop for improved Kubernetes management.

In this final module, we will recap the key takeaways from the course, highlighting the essential skills and concepts you've learned. You’ll also reflect on how to apply these tools and techniques to real-world Kubernetes environments. Finally, we’ll provide guidance on next steps for further learning and mastering K8sGPT in your Kubernetes workflows.