Google Cloud Platform (GCP) recently announced the beta launch of Google Cloud Recommenders, and the features and functionality are pretty exciting. The short of it is that with Recommenders in GCP, you can now:

Automatically get analysis of usage patterns to help you determine if resources and policies within Google Cloud are optimally configured
Automatically detect if overly permissive access policies are present, and adjust them based on access patterns of similar users in your organization
Choose the optimal virtual machine size for your workload, because most GCP customers initially provision machines that are too small or too large.
This is all pretty awesome, but in actuality, this is old news.

The Magalix Agent (which can be found in the Google Cloud Marketplace) has been doing this since day 1. Just last week with the release of KubeAdvisor, we now enable developers and DevOps engineers to get continuously generated Recommendations specifically to save money on any cloud provider (including GCP), enact best practices for cluster configuration, and optimize resource usage with application performance.

KubeAdvisor helps you select the right VM type, the right capacity limits and resources, and can even suggest how to optimize your K8s clusters based on the billing model of your cloud provider.

Just like Google Cloud, we’ve found that Kubernetes users are often way over or under-provisioned, and can save as much as 80% on their cloud costs by using KubeAdvisor. In this article, we’ll learn how KubeAdvisor works, and how it can help save on cloud costs while optimizing for app performance on Kubernetes.