Press release

Futuriom Highlights CAST AI in Research on Cloud Cost Management and FinOps

Cloud computing growth shows no signs of slowing down in 2023, so the questions of cloud cost optimization and FinOps become more pressing than ever. The newest report from Futuriom, an independent technology analyst, discusses the most critical challenges, potential solutions, and innovators – including CAST AI, the complete Kubernetes automation platform.

Futuriom’s research demonstrates that while cloud investment will continue to grow fast, concerns about cloud cost management (CCM) are also rising. Almost half of the surveyed IT managers plan to accelerate or keep the current cloud investment pace, and 28% seek solutions to help them save costs.

Cloud complexity is growing, and the need for improved cost visibility is evident among businesses seeking to make better decisions about the services they use. According to Futuriom’s findings, CXOs have reached a new level of awareness, driving demand for platforms able to identify, track, and optimize cloud costs. Achieving this goal calls for increasing automation in cloud infrastructure to streamline related processes.

The report highlights CAST AI’s ability to automate cloud cost optimization and use data algorithms to identify the cheapest place to run compute at any time. “Cloud cost optimization has become one of the strongest themes in 2023, as companies like to optimize and rationalize their cloud spending. CAST AI is ahead of the curve with AI-driven cloud compute optimization that can help companies save money instantly, which will be in high demand in this environment,” commented Futuriom’s Chief Analyst Scott Raynovich.

Download a complimentary copy and learn more about how companies approach cloud cost optimization and FinOps in 2023.

About Cast AI

Cast AI is the leading Kubernetes automation platform. Unlike traditional solutions that merely monitor clusters and provide recommendations, Cast AI leverages advanced machine learning algorithms to continuously analyze and automatically optimize clusters in real-time, cutting cloud costs, securing Kubernetes applications, and boosting DevOps efficiency.


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