This repository chronicles the journey of constructing a Kubernetes cluster from the ground up. A unique aspect of this project is the utilization of Docker containers 🐳 for all nodes, including the control plane, eschewing the conventional use of virtual machines. This approach promises a lightweight, adaptable, and scalable cluster environment.
- Manual Configuration: The cluster will be configured without relying on tools like kubeadm for a deep understanding of Kubernetes internals.
- Docker-Based Nodes: All cluster components will run within Docker containers for efficiency and scalability.
- High Availability: The cluster will employ multiple control plane and etcd nodes for redundancy and fault tolerance.
- Total Nodes:
- Control Plane Nodes: 2 🧠
- etcd Nodes: 2 🗄️
- Worker Nodes: 2 👷♂️
Note: The count of each Kubernetes component (Control Plane Nodes, etcd Nodes, Worker Nodes) can be adjusted as needed. These values should be specified in the node_counts.json file.
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etcd Cluster Establishment (🚧 In Progress)
- Configure a highly available etcd cluster across three nodes for reliable data storage.
- Implement necessary security measures and backups.
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Control Plane Deployment (🚧 In Progress)
- Set up Kubernetes API server, controller manager, and scheduler on three dedicated nodes.
- Implement load balancing for high availability and fault tolerance.
- Configure secure communication channels between components.
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Worker Node Configuration (🚧 In Progress)
- Install kubelet and kube-proxy on two worker nodes.
- Join worker nodes to the Kubernetes cluster.
- Configure network policies and resource quotas.
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Cluster Validation and Testing (🚧 In Progress)
- Conduct comprehensive tests to verify cluster functionality and performance.
- Implement monitoring and logging solutions.
- Optimize cluster configuration based on test results.
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Application Deployment (🚧 In Progress)
- Deploy sample applications to demonstrate cluster capabilities.
- Explore deployment strategies and scaling options.
- Efficiency: Reduces overhead compared to virtual machines.
- Scalability: Enables easy management and scaling of nodes.
- Simplified Management: Leverages Docker's streamlined configuration process.
- Explore advanced Kubernetes features like network policies, storage orchestration, and service meshes.
- Implement automated deployment and scaling mechanisms.
- Integrate with cloud platforms for hybrid or multi-cloud environments.
Contributions to this project are welcome! Feel free to submit bug reports, feature requests, or code improvements.
This project is licensed under the Apache-2.0 license
Note: This project is currently under development. More detailed information and documentation will be added as the project progresses.
Some portions of the code were inspired by and adapted from Kubernetes the Hard Way by Kelsey Hightower.