Kubernetes AI and Machine Learning in Production
Published by Pearson
Build workflows to deploy AI and ML in any Kubernetes environment
- Learn how to work with data sets, models, AI, and machine learning for Kubernetes environment in production
- Dive into AI and ML - 2 of the hottest skills you can learn
- Understand the “why” behind ML and AI on Kubernetes
- Learn the skills to help future-proof yourself
While AI and Machine Learning have been around for 20+ years, Generative AI, which is a text and response-based approach, has quickly made using these technologies a reality for engineers. Kubernetes AI and Machine Learning in Production takes a practical approach to exploring how you can use AI and ML in a production environment.
This 4-hour live training will detail how Machine Learning can be used to collect and build data and how to use AI to improve deployments, efficiency, and analyzation. Learning overall concepts of ML and AI will also help engineers to further future-proof their work as these two topics are increasing in popularity for production environments.
What you’ll learn and how you can apply it
By the end of the live online course, you’ll understand:
- The basics and intermediate concepts of ML and AI
- How to build data sets and models and then troubleshoot Kubernetes with AI
- The latest and greatest tools including ChatGPT, k8sgpt, and Kubeflow
And you’ll be able to:
- Start working with AI and ML on your own or at work
- Build workflows to deploy and use AI and ML in any Kubernetes environment
- Learn how to successfully use one of the latest production trends
This live event is for you because...
- You want to learn how to keep your apps at peak performance
- You want to understand how ML and AI can impact containerized apps
- You want to keep yourself up to date with what management and leadership teams want
Prerequisites
- Kubernetes knowledge (1.5+ years)
- Knowledge of developer tools like IDEs, code editors like VS Code, GitHub, etc.
- Hands-on experience with Kubernetes in production
Course Set-up
- A GitHub account. You can access the code for this course here: https://github.com/AdminTurnedDevOps/PearsonCourses/tree/main/kubernetes-ai-and-ml
- Access to a decently powerful machine (for example, an I7 with 16 GB of RAM)
- VS Code: https://code.visualstudio.com/download
- A Kubernetes cluster running either on-prem bootstrapped with Kubeadm or in the cloud.
- Access to Azure for a small portion of the live training. If you don’t have it, that’s ok.
Recommended Preparation
- Attend: Kubernetes in 4 Hours by Sander van Vugt:
- Watch: Getting Started with Kubernetes, 2nd Edition, by Sander van Vugt
- Attend: Build a CI/CD Pipeline by Byron Sommardahl
- Watch: Creating a Lab Environment by Sander van Vugt
Recommended Follow-up
- Attend: Responsible AI by Omar Santos and Dr. Petar Radanliev
Schedule
The time frames are only estimates and may vary according to how the class is progressing.
Segment 1: Why AI and Machine Learning (30 minutes)
- What is AI?
- What is Machine Learning?
- Large Language Models (LLM)
- AI-related databases and ML
- How AI and ML work together
Segment 2: Kubernetes Machine Learning (60 minutes)
- Why Machine Learning on Kubernetes?
- Creating Datasets and Data models in the cloud
- Properly configuring a Kubernetes cluster for ML workloads
- Installing and configuring Kubeflow
- Navigating the Kubeflow dashboard
- Kubefow pipelines and notebooks
- Implementing KServe
- Lab: Installing and configuring Kubeflow
- Q&A
Break (10 min)
Segment 3: Kubernetes AI (40 minutes)
- Why AI for Kubernetes?
- OpenAI
- How OpenAI uses Kubernetes to run models
- Statefulsets and how they’re crucial for ML workloads
- Make developing easier with Copilot
- The rise of ChatGPT and using it to troubleshoot Kubernetes
- Cost and resource optimization with AI
- Lab: Using CastAI for AI-generated cost optimization
- Q&A
Segment 4: k8sgpt (30 minutes)
- What is k8sgpt?
- Installing and configuring k8sgpt
- Using k8sgpt for troubleshooting
- Integrating k8sgpt with other tools
- Lab: Installing and using k8sgpt
- Q&A
Break (10 minutes)
Segment 5: Tools That use AI For Kubernetes (25)
- Why vendors are putting AI into their tools
- Kubescape
- KoPylot
- Kube Control AI
- Lab: Using Kubescape and KoPylot
- Q&A
Segment 6: ChatGPT and Kubernetes (25 minutes)
- What is ChatGPT?
- Using ChatGPT for troubleshooting
- ChatGPT for Kubernetes Manifests
- ChatGPT for obtaining Kubernetes knowledge
- Lab: Using ChatGPT For Kubernetes Manifests
- Q&A
Q&A (5 minutes)
Your Instructor
Michael Levan
Michael Levan translates technical complexity into practical value. He is a seasoned engineer, consultant, trainer, and content creator in the Kubernetes and Platform Engineering space who spends his time working with startups and enterprises around the globe. Michael is also a Microsoft MVP, 4x published author, podcast host, international public speaker, CNCF Ambassador, and was part of the Kubernetes v1.28 Release Team.