k8_resource_allocation

This repository contains an extended implementation of the solution proposed by James Bremmer for solving the dual-resource bin packing problem. The problem was initially posed by me on Stack Overflow, and the solution uses the first-fit algorithm for Kubernetes resource allocation challenges.

Overview

• The dual-resource bin packing problem involves assigning tasks that consume two types of resources (e.g., CPU and memory) to bins with finite capacities.
• The goal is to optimize resource allocation while minimizing wasted capacity.
• This implementation focuses on Kubernetes, where efficient use of CPU and memory is critical for containerized applications.

Features

First-Fit Algorithm: Based on James Bremner's proposal, this implementation uses the first-fit heuristic for resource allocation.
Extended Functionality: Enhancements and optimizations added to improve performance and handle edge cases in Kubernetes environments.
Dual Resource Handling: Manages two resource constraints simultaneously, ensuring efficient bin packing of both CPU and memory.

Credits

Original first-fit algorithm proposal by James Bremmer.
Problem and extension developed by quartermaine.