Kubernetes Cluster Autoscaler
Custom autoscaling solution for Kubernetes workloads based on custom metrics and predictive algorithms.
Problem
Manual scaling caused downtime during traffic spikes and wasted resources during low-traffic periods.
Solution
Developed predictive autoscaling using Prometheus metrics and machine learning to anticipate load changes.
Results
Reduced infrastructure costs by 35%, improved response times by 50%, achieved 99.99% uptime.