Introduction to Running Kubernetes Clusters

In this section, the speaker introduces different options for running Kubernetes clusters and provides an overview of the three main categories: self-hosted, managed clusters from cloud providers, and higher-level abstractions.

Self-Hosted Kubernetes Clusters

• Self-hosted clusters require setting up and managing all components of Kubernetes.

• This includes provisioning machines for the control plane and data plane, setting up networking and DNS, installing various controllers, container runtime, etc.

• Kelsey Hightower's GitHub repository "Kubernetes The Hard Way" provides a comprehensive guide on manually deploying Kubernetes.

• However, manual deployment is not recommended unless you have extensive knowledge and a dedicated team for debugging potential issues.

Managed Clusters from Cloud Providers

• Major cloud providers offer managed Kubernetes offerings such as GKE (Google), EKS (Amazon), AKS (Azure), as well as other providers like DigitalOcean or Linode.

• With managed clusters, the cloud provider handles the operation of the control plane while allowing users to configure and run applications using the Kubernetes API.

• Managed clusters provide a balance between power/flexibility and operational burden.

Higher-Level Abstractions

• If you don't need all the features of Kubernetes but just want to run containers, there are higher-level abstractions available.

• Examples include EKS Fargate and GKE Autopilot which allow running workloads without managing nodes.

• These abstractions are suitable when you don't require full flexibility but still want to leverage some benefits of Kubernetes.

Challenges of Self-Managing Control Plane

The speaker discusses challenges associated with self-managing the control plane in production environments.

• While Kubernetes has become more stable over time, there are still numerous ways things can go wrong.

• Running and maintaining your own control plane requires deep understanding and expertise.

• The YouTube series "Clustered" by the Raw Code Academy demonstrates deliberate cluster breakage and troubleshooting, highlighting the complexities involved.

• Unless you work in a large, mature engineering organization with specific reasons to self-manage, it is not recommended.

Managed Clusters

The speaker explains managed clusters offered by major cloud providers.

• Nearly all major cloud providers offer managed Kubernetes offerings (GKE, EKS, AKS).

• Other providers like DigitalOcean, Linode, or Sivo also provide similar offerings.

• Managed clusters allow users to provision a cluster while the cloud provider handles the operation of the control plane.

• Users can still install extensions and add-ons onto the cluster for additional functionality.

Higher-Level Abstractions

The speaker discusses higher-level abstractions for running containers without requiring full Kubernetes features.

• EKS Fargate and GKE Autopilot are examples of higher-level abstractions that allow running workloads without managing nodes.

• These abstractions are suitable when you don't need all the features provided by Kubernetes but still want to leverage containerization benefits.

New Section

In this section, the speaker discusses the trade-offs between managing your own Kubernetes cluster and using a managed service from a cloud provider.

Managing Your Own Kubernetes Cluster vs Using a Managed Service

• The speaker mentions that there are limitations around certain advanced features, such as mutating admission web hooks.

• For most teams using Kubernetes, especially in the early stages, it is recommended to use a managed cluster.

• There are many considerations when choosing a managed offering, but that topic will be covered in another video.

That's it for today. Remember to subscribe for future content and check out other videos by the speaker.

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