In the digital epoch we inhabit, the exorbitant costs of cloud computing have become a glaring issue, with enterprises squandering resources at an alarming rate. Projections for this year indicate a staggering waste of up to $44.5 billion on superfluous cloud expenditures. Akamai Technologies, a behemoth in the realms of cybersecurity and content delivery services, grapples with a complex array of multi-cloud infrastructures and stringent security compliance demands, necessitating the quest for a solution to streamline cloud costs.

Amidst this backdrop, Akamai has turned to the Kubernetes automation platform, Cast AI, leveraging its AI-driven agents to dynamically optimize costs, security, and velocity within its cloud environment. This strategic integration has yielded a remarkable reduction in cloud expenditures, with savings ranging from 40% to 70%, contingent upon the specific workloads.

Dekel Shavit, Senior Director of Cloud Engineering at Akamai, underscores the criticality of a continuous approach to infrastructure optimization and cost reduction, particularly during security incidents where latency is an anathema. Akamai sought a solution that could real-time optimize core infrastructure across multiple cloud environments, adapting to fluctuating demands without compromising application performance.

With Cast AI at its disposal, Akamai's DevOps team has been liberated from the monthly drudgery of manually tweaking Kubernetes workloads. Hundreds of Cast agents now perform automatic optimizations on a second-by-second basis, significantly enhancing the efficiency of cloud resource utilization. This enables Akamai to nimbly navigate through unexpected surges in traffic.

Cast AI's core competencies extend to automatic scaling, in-depth Kubernetes automation, automatic selection of the most cost-effective computing instances, and workload rationalization. Akamai has achieved a clear cost analysis within a mere two minutes, a feat previously unattainable. By harnessing Spot instances, Akamai has not only slashed costs but also bolstered operational efficiency, allowing for a sharper focus on delivering faster services to clients.

Shavit highlights the most significant boon: Akamai's team is no longer burdened with managing infrastructure. Cast AI's agents have seamlessly taken over this task, freeing the team to concentrate on developing new features and accelerating product delivery.

The integration of Cast AI has not only resulted in substantial cloud cost savings of 40% to 70% but has also empowered Akamai's DevOps team with real-time, second-by-second optimizations. Consequently, Akamai's team has gained the bandwidth to focus on rapidly launching enhanced features and services for their clients.