Industry-Leading Chunghwa Telecom Adopts Federator.ai for Green IT and Intelligent Continuous Cloud Operations
Maximize GPU Efficiency in MultiTenant LLM Training: Federator.ai GPU Booster on High-End GPU Servers Cuts Job Times by 50% and Doubles GPU Utilization
How to Configure An Application on Federator.ai for Autoscaling Kafka Consumer
The overall cost savings in Cloud operations that Federator.ai can achieve are from 35% up to 90%, according to client reports. The savings include reducing idle resources by up to 35%, applying the most cost-effective instance types by up to 40% savings, and choosing the best purchasing models from cloud providers by up to 70% savings.
ML-based workload predictions show the idle resources in current allocations and recommend the best way to reduce idle resources to maximize cost savings.
Identify different applications and their future workloads to adopt suitable cloud instances with the best blend of cost-saving plans without exposure to the risk of downtime.
Compare the cost based on the current cluster configuration and future requirements from different cloud service providers to formulate the most cost-effective purchasing plan.
©Copyright 2012-2024 ProphetStor Data Services, Inc. All Rights Reserved.