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In today’s age of generative AI, cloud costs are skyrocketing to unprecedented levels. The reason behind this surge is not just the increase in computing usage; it’s the lack of efficiency in how enterprises utilize their resources. Shockingly, it’s estimated that businesses will waste a staggering $44.5 billion on unnecessary cloud spending this year alone.
One company facing this challenge head-on is Akamai Technologies. With a vast and intricate cloud infrastructure spread across multiple platforms and stringent security requirements to uphold, they needed a solution to optimize costs, security, and speed across their cloud environments. This is where Cast AI, a Kubernetes automation platform, stepped in to save the day.
Thanks to Cast AI’s AI agents, Akamai was able to slash their cloud costs by an impressive 40% to 70%, depending on the workload. Dekel Shavit, Akamai’s senior director of cloud engineering, emphasized the importance of continuous optimization without compromising performance, especially when dealing with real-time security events.
Specialized agents play a crucial role in Cast AI’s platform, constantly monitoring, analyzing, and taking action to enhance application performance, security, efficiency, and cost. By leveraging machine learning models with reinforcement learning based on historical data and learned patterns, coupled with infrastructure-as-code tools on various clouds, Cast AI provides a fully automated solution for customers.
Akamai’s unique challenges, such as supporting a diverse range of customers with varying security needs and coping with sudden spikes in demand due to security attacks, required a solution that could dynamically optimize their Kubernetes infrastructure across multiple clouds. Cast AI fulfilled this need by automating tasks like autoscaling, workload rightsizing, and cost-efficient instance selection, resulting in significant savings for Akamai.
The integration of spot instances, which offer discounted cloud capacity, proved to be a game-changer for Akamai, especially when dealing with complex workloads like Apache Spark. With Cast AI’s assistance, they were able to harness the power of spot instances without the need for extensive engineering efforts, leading to substantial time and cost savings.
In conclusion, Cast AI has not only helped Akamai cut down on cloud costs but has also streamlined their infrastructure management, allowing the team to focus on delivering features to customers at a faster pace. The seamless integration of automation tools with human decision-making processes has proven to be invaluable for Akamai’s operations.
Don’t miss out on the opportunity to learn more about cutting-edge AI solutions at VB Transform. This month’s event will feature discussions on the latest AI stack in healthcare and the challenges of deploying multi-model AI systems in a complex, regulated environment. Register now to be a part of this enlightening experience.