The premise behind CAST AI is there is huge potential to reduce public cloud costs by using tools that can analyze cloud spending and suggest ways to optimize the cost, including finding cutting-edge cloud processing instances that may be offered below market rates.
CAST AI: Companies Spend Three Times More Than They Should on Cloud Costs
Overprovisioning results in significant cost with no material benefit whatsoever
April 25, 2022
CAST AI, the AI-driven cloud optimization company offering a full Kubernetes automation and cost optimization platform, analyzed infrastructure utilization reports for more than 400 organizations to quantify how much they overspend on cloud costs. These organizations included large enterprises running applications across tens of thousands of CPUs, down to small companies running their applications on just a few nodes. CAST AI’s cluster analysis tool is free to use, and provides detailed insight into how a company’s cloud resources are provisioned, as well as specific opportunities for optimization and cost savings.
“We performed a detailed analysis for hundreds of organizations running their applications in the cloud,” said Laurent Gil, co-founder and chief product officer, CAST AI. “Our advanced AI engine provides full visibility into how much you’re currently paying for cloud resources, as well as how much you would save if those resources were optimized.”
“CAST AI will then instantly rebalance and optimize your cluster configuration in perpetuity, while hitting the cost savings target within just a few minutes,” continued Yuri Frayman, chief executive officer, CAST AI. “All of this is directly reflected in the bill you get from your cloud provider. After aggregating anonymous data, we have unparalleled insight into exactly how much companies overspend. Between 50 to 75 percent on average.”
CAST AI’s analysis surfaced a number of key findings, both in terms of overprovisioning and how much companies overspend as a direct result. These include:
- On average, organizations spend 3x more than they should on cloud costs.
- 98 percent of organizations had substantial cost savings.
- The main driver for this is the over-provisioning of expensive resources, resulting in significant cost with no material benefit whatsoever.
- Almost 2/3 of the cost waste is the result of CPUs and memory that are provisioned but not utilized, combined with the selection of cost inefficient VMs with expensive CPUs and too large memory ratio.
- The remaining waste comes from under leveraging the use of spot instances for containers that are qualified to be spot friendly.
Provisioning remains a significant challenge for organizations of all sizes. Cloud providers typically have more than 600 different instance types to choose from, so even the most experienced and technically adept DevOps and SRE professionals benefit considerably from automation; it is difficult and time consuming to select the right types and quantity of VMs while making sure that the infrastructure is continuously rightsized.
With new advances in AI it is now easy to make this process both instant and automated, so that requested, provisioned and utilized CPUs are 100 percent in sync, and remain in sync over time. This is what CAST AI’s advanced platform was specifically designed to address, resulting in significant cost savings for customers while providing unique insights into cloud overprovisioning and overspend.
About CAST AI:
CAST AI is a cloud optimization platform that cuts cloud bills in half for AWS, GCP, and Azure customers. Powered by AI, it analyzes multiple data points to find an optimal cost-performance ratio. The platform delivers a cost-efficient, high-performing, and resilient infrastructure for all types of Kubernetes workloads. Headquartered in Miami, US, CAST AI has a European branch in Vilnius, Lithuania.
Learn more: https://cast.ai/
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CAST AI takes advantage of cloud-native technologies, containerization and Kubernetes to break the proprietary barriers that exist between clouds
The good thing about using AI in cloud automation is that it can make decisions based on somewhat correlated variables with a limited amount of information.
Cloud automation solutions reduce or eliminate all the manual effort your team invests into configuring virtual machines, creating VM clusters, setting up virtual networks and more.