CAST AI, the leading Kubernetes automation platform, today announced that it was included in The Cloud Cost Management And Optimization Solutions Landscape – a Forrester report designed to help the independent research firm’s clients understand, identify, and explore the vendors and service providers that align with the most critical business technology issues. For the Landscape, Forrester provides an overview of Cloud Cost Management and Optimization solutions companies can use to optimize their cloud costs.

According to the Forrester report, “Despite a down economy, the annual average enterprise cloud spend continues to grow. In 2023, the average global public cloud annual spend was $35 million, which is a $2 million increase year-over-year. As this number increases, cloud leaders are facing outsized pressure from executive teams and boards to ensure each dollar spent is maximized in value.”

Forrester said that cloud cost management and optimization solutions play a central role in companies’ FinOps journeys, and emphasized the need to rightsize overprovisioned instances, and choose the appropriate type of instance, using automation.

CAST AI goes beyond monitoring clusters and making recommendations that DevOps teams need to evaluate and manually implement. The company’s platform cuts AWS, Azure, and GCP customers’ cloud costs by over 50% by utilizing advanced machine learning algorithms that analyze and automatically optimize Kubernetes clusters in real-time.

“We are honored to be included in Forrester’s Landscape. We are on a mission to remedy manual, inefficient processes in cloud computing using automation. We will continue to push the boundaries of innovation as we further expand the capabilities of Kubernetes automation platform,” said Laurent Gil, co-founder and chief product officer at CAST AI.

About CAST AI:

CAST AI is the leading Kubernetes automation platform that cuts AWS, Azure, and GCP customers’ cloud costs by over 50%. CAST AI goes beyond monitoring clusters and making recommendations. The platform utilizes advanced machine learning algorithms to analyze and automatically optimize clusters in real time, reducing customers’ cloud costs, improving performance and security, and boosting DevOps and engineering productivity.

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