CAST AI, the leading Kubernetes cost automation and management platform, joins other cloud and innovation leaders at the forthcoming Google Cloud Next ’23.

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The team standing behind the Kubernetes automation platform will be sharing actionable cost reduction recommendations throughout the event in booth 443. Our experts will be available to deliver personalized product demonstrations and help you with cost, performance, and management challenges.

Come experience how our platform works, meet our engineers, and discuss future partnership opportunities! Book a meeting with our team via this link.

“While Google Cloud supports digital transformation across many businesses, technologies such as CAST AI help speed the process. Our platform has helped countless Google Cloud clients reduce their cloud expenditures and make the most of every dollar spent on cloud services. Cloud-native teams can do so much more by lowering expenses and boosting performance, and we are excited to share practical GKE optimization ideas with you,” commented Laurent Gil, Chief Product Officer at CAST AI.

Google Cloud Next ’23 brings together everyone interested in creating a future cloud that is accessible, scalable, and socially responsible. It will take place between August 29-31 at Moscone Center in San Francisco, CA.

The event offers an opportunity for visionaries, tech leaders, and entrepreneurs to debate their difficulties, develop solutions, and investigate game-changing technology. Attendees may hear about the most recent Google Cloud advancements in AI, productivity, security, and data, as well as roadmaps for popular Google products. The event is jam-packed with training sessions, demos, hands-on laboratories, and keynotes from renowned experts.

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, and improving performance and reliability to bolster DevOps and engineering productivity.

Learn more:

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