Dynamic Resource Optimization
Dynamic Resource Optimization (DRO) automatically and transparently helps customers optimize their cloud spending. It analyzes resource utilization and executes optimization actions using post-provisioned techniques which are transparent to the application. DRO operates in real time to ensure optimal provisioning as workloads change.
DRO uses machine learning to continuously optimize resource provisioning with application needs. It operates with minimal or no user interaction and application down time. Simply put, DRO is a software solution that takes care of the entire process while the user sits back and enjoys the cost benefits.
Most cloud optimization solutions available today simply report infrastructure spending and resource utilization. They do not analyze the data nor automate optimization actions, leaving the burden on overworked IT staff! In dynamic cloud environments where new applications are constantly being provisioned, it’s simply not practical to manually monitor and optimize the infrastructure.
Dynamic Resource Optimization combines machine learning techniques with automation to relieve customers of this burden.
1. Reactive: In this mode, FittedCloud identifies optimization opportunities that can be implemented immediately and automatically. Reactive optimization involves continuous monitoring and adjustment of resources based on utilization.
2. Predictive: Machine learning algorithms are used to identify historical utilization patterns so that resources can be provisioned to match actual utilization. This mode can achieve maximum cost reduction.
3. User-driven Policies: The third component of DRO is user-driven policies. It could be done manually through user input or in form of actionable advisories where appropriate actions are attached to recommendations so that customers can simply click to execute them. This gives customers complete control over their environment and full visibility into cost optimization.
Flexible Automation Options
FittedCloud issues actionable advisories to alert customers to available optimization opportunities. Appropriate actions are attached to each advisory that customers can simply click to execute them. Actionable advisories give customers complete visibility and control over the optimization actions that can be implemented to help reduce cloud spend.
Full automation allows lights out resource provisioning driven by user-specified policies or machine learning. Customers simply create policies and enable resource optimization. The software drives the provisioning – completely automatically, transparently, optimally.