Federator.ai learns application resource usage patterns and predicts the needed resources down to the container level. Federator.ai has the following key features:

• Multi-layer workload prediction:
  Federator.ai applies multiple analytics tools, such as machine learning and signal processing, to predict containerized application and node resource usage as the basis for pod resource recommendations. Federator.ai supports both physical and virtual CPUs and memories.
• Policy-driven planning of CPU and memory:
  Federator.ai plans cluster-wide CPU and memory allocation for different types of applications according to the policy specified by users.