Learn how Sedai autonomously optimizes Kubernetes (K8s) workloads to achieve your performance, cost, and availability goals.
Sedai uses the following features to intelligently optimize your K8s clusters at both pod and container levels.

Cost Optimization and Resource Efficiency

Sedai autonomously optimizes K8s clusters and workloads to improve both cost and resource efficiency. This is achieved by:
  1. 1.
    Right sizing K8s deployments: Sedai determines the optimal CPU and memory for a particular workload and then allocates these resources accordingly to prevent excessive cost.
  2. 2.
    Optimizing K8s cluster configurations and node groups: Sedai optimizes cluster CPU & memory configurations and determines the optimal number of node groups for peak efficiency.
  3. 3.
    Using optimized purchasing options from cloud providers: Sedai uses cloud provider purchasing options to optimize K8s clusters for performance and cost.

Performance Optimization

In addition to optimizing cost, Sedai autonomously improves application performance. Sedai’s intelligent and continuous horizontal and vertical right sizing increases performance efficiency, allows for greater scalability, and ultimately improves overall reliability.

Availability Improvements

Sedai proactively detects potential availability issues and generates recommendations, restarts, and autonomous configuration updates so your resources remain reliable.