We have some super exciting news for you! Today, we launched a brand-new product dedicated to those who run Kubernetes on AWS Elastic Kubernetes Service (EKS) and want to slash their costs.
Our platform already offers cloud cost optimization for clusters in AWS, Azure, Google Cloud Platform, and DigitalOcean.
Analyze your EKS Cluster for free and get costs savings report!
Our new product to help teams optimize any EKS Kubernetes environment. The EKS Optimizer analyzes clusters to find opportunities for cost savings, generates a report, and then keeps on optimizing your setup in line with your cost policies.
Azure Kubernetes Service (AKS) and Google Kubernetes Engine (GKE) optimization solutions are already on our roadmap and coming in a few months.
Why optimize EKS?
“We built the EKS Optimizer, so teams no longer need to invest time and effort into monitoring, analyzing, and optimizing their Kubernetes environments on AWS. Our platform handles the provisioning, de-provisioning, and autoscaling of workloads for our customers, all the while negotiating the best possible resources available on AWS on their behalf in real time,” said Leon Kuperman, CTO and co-founder of CAST AI.
The EKS Optimizer is now available directly within the CAST AI platform. Following excellent feedback from partners and customers, the solution should also become available on the AWS Marketplace in the near future.
“A large number of companies have expressed interest in EKS optimization. Many organizations are urgently looking for ways to optimize their cloud bill. We have already signed contracts within industries such as e-commerce, data analytics, data science, cybersecurity, and SaaS application delivery,“ said Laurent Gil, Chief Product Officer and co-founder of CAST AI.
How does EKS Optimizer work?
Today, the majority of Kubernetes environments underutilize the resources assigned to them. CAST AI’s granular approach to autoscaling addresses resource requirements precisely, taking into account the actual work to be performed and required scale rather than following a predetermined DevOps formula.
By connecting existing EKS clusters in a read-only mode, you can get instant savings reports and identify opportunities for cutting your AWS Kubernetes costs. To proceed with full automation, all it takes is setting optimization policies and leaving AI in charge of optimizing your cloud bill.
For monolithic, Docker-based applications, the platform achieves cost savings of around 50%. For applications based on microservices, it reduces costs by 75-80%.
Use EKS with EC2 spot instances
The EKS Optimizer finally opens the doors to using EC2 spot instances that bring 80-90% of cost savings when compared to on-demand pricing.
Since spot instances can be interrupted at any moment, many companies refrain from using them. CAST AI solves this problem through several approaches, including burst scaling of pods when required. If AWS pulls the plug on an instance, the platform anticipates the interruption and takes measures to ensure that there is always an adequate capacity to avoid service disruption.
“Cloud cost optimization is an essential practice for every company that wants to use containerization effectively,” said Robert Duncan, CISO of DirectLine UK.
Thanks to a unique blend of automation and optimization algorithms, CAST AI opens the next chapter in DevOps automation, empowering teams to reap the full benefits of their cloud investments without any extra work.
See how EKS Optimizer slashes cloud costs live at KubeCon Europe 2021
We’re going to show you how EKS Optimizer achieves the incredibly high cost savings in our booth and demos by our CTO during KubeCon Europe 2021.