Amazon’s RDS simplifies the usage of traditional relational database services by bundling the database software and underlying compute instance into a single, comprehensive service.
Determining what RDS instance type and size to use for a given database workload can be a challenge. Databases often have complex usage patterns across CPU, memory and I/O, and may have cyclical or sporadic loads, making them difficult to optimize. Simply looking for “whitespace” or underutilized resources can be risky.
Densify’s Cloud-Learning Optimization Engine—Cloe—learns the patterns of RDS utilization across all resource types, providing a detailed characterization of the database workloads. By employing a multidimensional catalog, Densify also understands what instance families and sizes are available for each database type in each region, enabling precise alignment of instance types with resource demands.
Cloe is “Reserved Instances-Aware” and considers your standard RI coverage, protecting existing investments. If your instances have existing standard RI coverage, the recommendations will be deferred until the current RI expires.
Even though there are often fewer RDS instances than other AWS services, they can be quite expensive and are often responsible for a large portion of the monthly bill. Densify automatically identifies opportunities to optimize RDS instances so you don’t have to pay for expensive resources that you don’t need.