Autonomous K8s Optimization Involves Both Compute and Storage Resources – Are You Doing Both?
[Live Webinar] May 14 @ 11:00am EST
One of the most powerful capabilities in K8s is the ability to autoscale resources to meet demands, scaling resources up during peak periods to ensure performance, and down again during lower periods to save money.
This is true of compute resources, where effective pod sizing and node autoscaling are key, as well as storage, where persistent volumes must always have resources to meet the demands of applications. But in practice this is very tricky to do – compute resources are notoriously mis-configured, node scaling can be sub-par because of this (and many other reasons), and storage has no autoscaler at all!
In this joint session, Lucidity and Kubex walk through what end-to-end K8s optimization looks like when you address both layers together. We’ll cover:
- How to identify and eliminate compute waste across your clusters,
- How storage provisioning patterns create hidden costs and I/O constraints, and
- How to build a continuous optimization practice rather than a one-time cleanup.
Expect real examples, not slides full of theory. You’ll leave with a clear picture of where waste is hiding in your environment and a prioritized approach to addressing it.
Can’t join us live? A recording of the session will be sent to registrants.
