Kubernetes
Learn how to manage settings for your Kubernetes clusters.
Sedai optimizes Kubernetes (K8s) clusters for CPU and memory at both pod and container levels to improve performance and/or reduce costs.
While resource usage and latency may improve simultaneously, they can also inversely impact each other. You can choose whether K8s optimization actions prioritize resource usage, latency, or both resource usage and latency:
- Resource Usage Priority: Sedai will generate optimum CPU and memory allocations to minimize resource usage.
- Latency Priority: Sedai will generate optimum CPU and memory allocations to minimize latency.
- Cost and Latency Priority: Sedai will generate optimum CPU and memory allocations to minimize both resource usage and latency.
In addition to selecting a priority, choose from the following settings to control Sedai’s optimization permissions for your K8s clusters:
- Auto-Execute: Sedai will take safe and confident autonomous actions to optimize your K8s clusters by continuously selecting the optimal CPU and memory configurations.
- Recommend: Sedai will make CPU and memory recommendations but will not act autonomously.
- Off: Sedai will not recommend or autonomously configure memory and CPU.
Sedai can autonomously increase or decrease the number of replicas of a given pod within a deployment to manage traffic. Toggle horizontal sizing on to allow Sedai to autonomously execute horizontal pod sizing.
Sedai can autonomously increase or decrease the amount of CPU or memory allocated to a given pod to manage traffic. Turn vertical sizing on to allow Sedai to autonomously execute vertical pod sizing.
Last modified 7mo ago