The ScaleOps Blog – Yodar Shafrir

Today, we are excited to announce a significant achievement for ScaleOps – we have successfully raised $21.5 million in total funding. We’re thrilled to be working with LightSpeed Venture Capital, who led this round, and participating investors NFX and Glilot. 

As the usage of Kubernetes as a cloud-native platform increases, the efficient management of computing resources for pods has become increasingly challenging. The efficient use of resources can significantly impact the performance and costs of a workload.

In the world of cloud computing, cost optimization is a critical concern for organizations running applications on Kubernetes. To address this challenge, many organizations have turned to solutions like Cluster Autoscaler to automatically adjust the number of nodes in a cluster to match workload requirements. However, there is another solution worth considering – Karpenter. In this blog, we will take a deep dive into Karpenter and explore how it differs from Cluster Autoscaler, and the benefits it offers for cost optimization in Kubernetes.

Kubernetes Cluster Autoscaler is an indispensable tool for managing resources effectively and maintaining cost-effective, high-performing clusters. However, it is important to note that Cluster Autoscaler is only aware of the pod resource requests, not their actual usage.

When it comes to cloud-native services and applications, Kubernetes is de facto the most common container orchestrator. Kubernetes comes with the benefits of built-in deployment, customization, scaling, resiliency capabilities, use-case agnostic and a faster time to market for applications, big data, AI, HPC, and more. However, managing and orchestrating Kubernetes resources efficiently at scale has […]