2 repositorios
Systems that analyze actual resource usage to automatically adjust requested CPU and memory limits.
Distinct from Request Size Limits: Existing candidates focus on network request size limits or routing, not the right-sizing of pod compute requests.
Explore 2 awesome GitHub repositories matching devops & infrastructure · Resource Request Optimization. Refine with filters or upvote what's useful.
The Kubernetes Cluster Autoscaler is a mechanism that automatically adjusts the number of nodes in a cluster to match the resource demands of pending pods. It functions as a cloud infrastructure scaler that manages the desired capacity of scaling groups to ensure sufficient compute resources for workloads. The system manages cloud infrastructure automation by adjusting node counts when resources are insufficient or nodes are underutilized. It includes a manager for scaling groups using mixed instance policies to balance on-demand and spot instances for cost and availability. The project also
Analyzes pod usage patterns to automatically update CPU and memory requests for better hardware utilization.
Goldilocks is a suite of tools for analyzing resource usage and managing autoscaling policies in Kubernetes. It functions as a resource optimizer and capacity planner, providing a dashboard and command line interface to analyze workload utilization patterns and suggest efficient CPU and memory requests and limits for containers. The project distinguishes itself by visualizing recommendations from the Vertical Pod Autoscaler via a web interface and providing a lifecycle manager to create and configure these autoscaler objects. It includes capabilities to aggregate resource recommendations acro
Analyzes actual CPU and memory usage to determine the most efficient resource requests and limits for containers.