Optimizing Cloud Costs with AI: A Case Study of Akamai Technologies
In the age of generative AI, cloud costs are soaring, with enterprises expected to waste $44.5 billion on unnecessary spending this year. Akamai Technologies, a cybersecurity and content delivery provider with a complex cloud infrastructure, faced this challenge head-on.
To address this issue, Akamai turned to Cast AI, an application performance automation platform that utilizes AI agents to optimize cost, security, and speed across cloud environments. The results were impressive, with Akamai cutting between 40% to 70% of cloud costs, depending on workload.
Specialized Agents for Application Performance
Cast AI’s Application Performance Automation (APA) platform operates through specialized agents that continuously monitor, analyze, and take action to improve application performance, security, efficiency, and cost. With machine learning models and reinforcement learning based on historical data, APA offers a fully automated solution for optimizing cloud infrastructure.
Founder and President Laurent Gil emphasized the importance of observability as a foundation for automation, with Cast AI supporting incremental adoption and human-centric workflows to complement decision-making.
Challenges Faced by Akamai
Akamai’s large and complex cloud infrastructure serves a wide range of customers, including financial institutions and credit card companies, with strict security requirements and performance expectations. Scaling capacity in real-time to address security attacks posed a significant challenge, requiring a balance between complexity and cost.
Automating Kubernetes Infrastructure
Implementing Cast AI allowed Akamai to optimize the costs of running its core infrastructure in real-time on multiple clouds, scaling applications based on demand without sacrificing performance. The platform’s core features, including autoscaling, bin packing, and cost analytics, provided insights and savings that were previously unattainable.
By leveraging spot instances on Apache Spark workloads with Cast AI, Akamai achieved significant cost savings without manual intervention, freeing up their team to focus on innovation and feature development for customers.
Overall, the integration of Cast AI enabled Akamai to automate infrastructure management, resulting in time savings and improved efficiency in delivering services to customers.
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