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Server Load Prediction System:
Improving the Efficiency of Computing Resource Management
Improving the Efficiency of Computing Resource Management
AI-based systems
production
6
3%
IT budget planning and tender procedures
by
reducing costs for purchased software licenses
months in advance
Customer
A large technology holding company producing trucks and automotive equipment in Russia
CHALLENGES/FEATURES
extensive IT infrastructure
equipment shortage
most of the servers are located within the holding's boundaries
Development of a system for forecasting server demand for efficient use of current capacity
Task
solution
Technical solution
A prototype of a server load forecasting system for resource management in a digital manufacturing ecosystem that:
based on 50+ factors that affect server performance
collects data on factors from 100+ servers
collects data on CPU, GPU, HDD and other metrics
Result
Business values
The model allowed us to clearly understand:
forecast of the efficiency of using current server capacities
be prepared for peak loads in advance and plan the purchase of new servers in normal mode
IT resource efficiency
minimal risk of server equipment downtime
Stability of production
the risk of equipment failure decreased by 3%
identify potentially dangerous periods of peak loads in the future and warn responsible specialists in advance
Budget savings
reducing the labor intensity of monitoring
equipment purchase plan in advance – 6 months
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