What is the practice of mapping instance types and sizes to workload performance and capacity requirements at the lowest feasible cost?

The practice of mapping instance types and sizes to workload performance and capacity requirements at the lowest feasible cost is known as "Cost Optimization". This is a key aspect of cloud computing and involves understanding how to manage and control costs while maximizing the effectiveness and efficiency of your resources.

Here are the steps:

1. Identify the Workload: The first step is to understand the nature of the workload. This includes understanding the performance requirements, the capacity requirements, and the nature of the workload (e.g., is it compute-intensive, memory-intensive, etc.).

2. Choose the Right Instance Type: Based on the nature of the workload, choose the right instance type. For example, if the workload is compute-intensive, choose a compute-optimized instance type.

3. Choose the Right Instance Size: Once the instance type is chosen, choose the right instance size. This is based on the capacity requirements of the workload.

4. Monitor and Adjust: Once the instances are deployed, continuously monitor the performance and adjust the instance type and size as needed. This is to ensure that the workload is running efficiently and cost-effectively.

5. Use Cost Management Tools: Use cost management tools provided by the cloud provider to track and manage costs. These tools can provide insights into cost trends and can help identify opportunities for cost savings.

6. Implement Cost Optimization Strategies: Implement strategies such as using reserved instances for predictable workloads, using spot instances for flexible workloads, and using auto-scaling to adjust capacity based on demand.

By following these steps, you can map instance types and sizes to workload performance and capacity requirements at the lowest feasible cost.