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How CAST AI Can Help Reduce Cloud Costs And Over-Provisioning

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Many organizations are struggling to manage cloud costs, which are being made worse by economic problems and inflation. More than ever, organizations need to get a hold of their cloud costs and ensure that their applications are being run to maximum efficiency. Many are running machines where only 40% of the compute is not being used.

In this episode of TFiR Let’s Talk, Swapnil Bhartiya sits down with Laurent Gil, Co-Founder and CPO at CAST AI, to discuss how the company’s cloud optimization platform helps organizations reduce their cloud costs. He goes into detail about the challenges organizations are facing with over-provisioning and the potential cost savings they can make by using CAST AI.

Key highlights from this video interview are:

  • CAST AI built an engine to compute how many resources your application needs on any of the big three providers: AWS, Google Cloud and Azure. From there, it works out how much compute your application needs automatically and can optimize accordingly to only use the resources needed. Gil goes in-depth about the AI engine and how it optimizes costs.
  • Cloud costs are a serious challenge, particularly in light of potential economic difficulties around the world. Gil discusses the challenges companies are facing with cloud costs and the need for projects to help them with observability and reducing costs.
  • Gil feels that over-provisioning is not a mistake but a complex problem. He explains that out of the several 1,000 applications using the free version of their product for cost reporting, the average over-provisioning they see is 40%. He discusses why it’s an impossible task for humans to grapple with and that is why we need a machine instead.
  • According to CAST AI, 40% of your compute is not used. There are also around 600 VMs which are all different and choosing the right sizing can bring about a saving of approximately 7%. Gil shares some key statistics and insights into managing cloud costs and the reduction of costs they see from using their platform.
  • Gil explains the impact on cloud cost due to multi-hybrid cloud. He discusses how you can do a pricing arbitrage across the cloud and the extreme cost savings that can be achieved. He also goes into detail about the use case of hybrids and how the CAST AI engine assesses where it is best to run the machines whether on-prem or cloud.
  • CAST AI works well at optimizing costs on-premises as well as cloud. Gil explains how on-premises cost optimization is centered around freeing up resources that you do not need anymore and how by using it better you can cut your electricity cost. He discusses the direct correlation between cost utilization and resource utilization with on-prem.

Connect with Laurent Gil (LinkedIn, Twitter)
Learn more about CAST AI (Twitter)

The summary of the show is written by Emily Nicholls.

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