Declarative performance for Kubernetes
Valence is a cost and performance management solution for Kubernetes. It’s an operator that figures out replicas, limits, requests, and quality of service for the most cost-efficient and performant way of running your applications in Kubernetes.
4 months ago
Earlier, we explained a little bit about what Valence is: ML-Powered, declarative performance for resources and scaling in Kubernetes. Now we are going to explain how to get started. First, we will go over a quick start to see how Valence works - and then we will go into setting your first Deployment up with Valence.
Hiya 👋, As Kubernetes operators, we love Kubernetes autoscaling, resource control, and scheduling capabilities, but ran into issues with how to autoscale, how to set resources, and how to ensure performance in the most cost effective way. So, we built Valence as a tool to help with that.
Would you recommend this product?
Hey there! I am one of the folks working on
. We built Valence because we thought performance (and as a by product resource utilization aka cost) could be managed Declaratively, in the same way that you could declare Kubernetes resources and have a controller keep that resource up to date. We thought why couldn't you declare some higher level objective such as a Service Level Objective and have some mechanism to go and figure out how your application should be configured? We learned that to do this we'd need to use control theory to learn the dynamics of applications and forecasting to ensure we were able to meet performance objectives ahead of time, not just react to performance violations. Once we saw how Valence was able to meet Declared Service Level Objectives through this feed-forward control mechanism, we wanted to have folks use it and so we built it as a controller/operator for Kubernetes scaling and resources. We'd love for you to try it out and you can do so for free always (up to a limited amount of concurrent applications). I am happy to answer any questions or take any feedback folks have :)
4 months ago