Real-World Examples of AI-Based Cloud Cost Optimization

1. E-commerce Companies

Companies working in e commerce are often characterized by the fluctuating intensity of customer interest throughout the year. During the shopping peak or flash sales, platforms need to be able to accommodate increased traffic without impacting performance. For e-commerce businesses, AI-based cloud cost optimization enables dynamic scaling – the technology adjusts computing resources in real-time to supplement increased demand.

Example: An online retail business has an AI function that does it for its server resources during the annual Black Friday or Cyber Monday sales. When customer traffic increases, the system adds a server with more resources; after the holiday season, it turns it off. It prevents the company from over-provisioning during a single couple of days in the year and saving thousands of dollars.

2. Media and entertainment

Media and entertainment companies have a strong need for high-performance cloud resources to manage streaming, content creation, and delivery. AI-driven cloud cost optimization enables these companies to place workloads intelligently to various cloud regions and providers to optimize costs and performance.

Example: A video streaming platform leverages AI to distribute its video encoding workloads across multiple cloud regions . By choosing the most affordable regions based on factors such as energy prices and resource allocation, the platform reduces costs while providing a seamless streaming experience for consumers.

3. Finance and Banking

Finance and banking industries depend heavily on data analysis and modeling. AI-powered cloud cost optimization offers finance institutes predictive analytics of historical data that helps in future presentation of their cloud budget for brightness. A financial services company may use AI to predict future cloud usage and costs based on its use in the past quarter. The predictions help the company save on expenses by budgeting more effectively and allocating resources more efficiently

Example : A bank experiences a surge in loan applications every spring due to home buying season. Their AI-powered cloud cost optimization tool predicts this increase and automatically scales up compute resources for a few months. This prevents slowdowns during peak application times and reduces costs by automatically scaling back resources to normal levels after the season ends.

Since most businesses are adopting cloud computing for IT infrastructure and operational use, cloud costs become a concern to manage. AI-based cloud cost optimization is a new trend that provides a unique way of spending on cloud services using artificial intelligence. AI-based cloud cost optimization is a cost-effective & efficient way for businesses to use their cloud investment better while saving unnecessary costs. This resource discusses how AI-based cloud cost optimization works, its benefits, and how businesses can use it to manage it properly.