Kubecost Reviews

CAST AI significantly reduces your compute costs with automated cost management and optimization. Within minutes, you can quickly optimize your GKE clusters thanks to real-time autoscaling up and down, rightsizing, spot instance automation, selection of most cost-efficient instances, and more. What you see is what you get – you can find out what your savings will look like with the Savings Report available in the free plan with K8s cost monitoring. Enabling the automation will deliver reported savings to you within minutes and keep the cluster optimized. The platform understands what your application needs at any given time and uses that to implement real-time changes for best cost and performance. It isn’t just a recommendation engine. CAST AI uses automation to reduce the operational costs of cloud services and enables you to focus on building great products instead of worrying about the cloud infrastructure. Companies that use CAST AI benefit from higher profit margins without any additional work thanks to the efficient use of engineering resources and greater control of cloud environments. As a direct result of optimization, CAST AI clients save an average of 63% on their Kubernetes cloud bills.

For companies that depend on a modern, multi-cloud infrastructure to power their SaaS customer experience, Yotascale enables dynamic cloud cost management with unmatched insights, accuracy, and time to value to help reduce their cloud spend by up to 50%. Unlike first-generation solutions that are hard to use and even harder to configure, and don’t give real-time, proactive insights, Yotascale delivers real value in the first few days, and every day thereafter, because we make it easy for the right people to take the right course of action at the right time to get cloud costs under control. At Yotascale, we make it easy for teams to take ownership of cloud costs with: 95% accurate, granular cost attribution that matches the way you do business; all-in-one support for multi-cloud and containers (including Kubernetes, ECS, AKS and more); and highly actionable scenario-based recommendations at the application, service and workload level that make optimizing cloud costs simple, efficient, and predictable.