Federator.ai helps enterprises optimize cloud resources, maximize application performance, and save significant cost without excessive over-provisioning or under-provisioning of resources, meeting the service-level requirements of their applications.
Enterprises often lack understanding of the resources needed to support their applications. This leads to either excessive over-provisioning or under-provisioning of resources (CPU, memory, storage). Using machine learning, Federator.ai determines the optimal cloud resources needed to support any workload on OpenShift and helps users find the best-cost instances from cloud providers for their applications.
Resource planning and optimization
By installing Federator.ai as an operator on OpenShift, you can predict what resources (e.g. CPU, Memory) are needed to support each of your applications without guessing. Imagine you are running hundreds of applications on OpenShift, and you need to allocate the right amount of cloud resources to support each of them. Federator.ai helps you do effective resource planning without excessive over-provisioning or under-provisioning your resources.
Cloud cost optimization
If you are running your applications on public clouds, you need to decide which instances from the cloud providers you need to subscribe to. You are charged for the cloud instances every minute, whether your applications utilize the resources or not. Federator.ai helps you determine the best-cost instances from cloud providers in supporting each of your application workloads. The typical cost savings on cloud instances using Federator.ai ranges from 20% to 70%.
Application performance optimization
In a dynamic environment, workloads can change quickly. Through auto-scaling, Kubernetes helps scale up and down the resources supporting your applications. Your application performance (throughput and latency) depends on the effectiveness of your auto-scaling. Using machine learning, Federator.ai significantly enhances your auto-scaling capability on OpenShift and optimizes your application performance.
