Automated Virtual Machine Shutdown Based on Inactivity and Cost Thresholds
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Solution Overview
Problem
In cloud environments, there is no automated method to shut down inactive virtual machines, leading to unnecessary energy and compute costs, and manual calculations for cost estimation are inaccurate and time-consuming.
Innovation Solution
An automated virtual machine shut down method based on operating conditions, such as inactivity time or cost thresholds, which includes configuring a worker role to monitor and manage virtual machines, calculate costs, and send alerts or initiate shut downs, using a service to track status and store data in an SQL database.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If virtual machines are manually monitored and shut down, then energy and compute costs are reduced, but user time and operational complexity increase
Solution Approach 1:
The system enables virtual machines to automatically monitor their own operational status and trigger shutdown actions based on predefined conditions (inactivity time, cost thresholds) without requiring continuous user intervention. The automated monitoring service tracks VM status and executes shutdown decisions autonomously, eliminating the need for manual user monitoring while reducing energy and compute costs.
2Productivity
If automated shut down is implemented, then operational efficiency is improved, but system complexity increases
Solution Approach 1:
The automated shutdown system is segmented into distinct functional components: a monitoring service that tracks VM status, a decision engine that evaluates shutdown conditions (inactivity time, cost thresholds), and an execution module that triggers shutdown actions. This segmentation allows each component to perform its specific function independently, improving operational efficiency while managing system complexity through modular design.
3Loss of information
If manual cost calculation is performed, then cost awareness is achieved, but accuracy and time consumption are compromised
Solution Approach 1:
The system implements automated feedback loops where the monitoring service continuously collects VM operational data (runtime, resource usage), the decision engine calculates actual costs based on this data against predefined thresholds, and the system provides cost information back to users. This automated feedback mechanism ensures accurate cost calculation and real-time cost awareness without requiring manual computations, eliminating the inaccuracies and time consumption associated with manual methods.
Data Source
AI summary
There is provided a virtual machine control with the ability to configure a virtual machine's behavior when certain conditions are met. The conditions include configuring a virtual machine based on an amount of time of inactivity. The conditions include configuring a virtual machine based on exceeding a cost for a given time frame. The virtual machine control removes the need to have a user manually monitor and shut down unused virtual machines. Accordingly, the virtual machine is automatically commanded to shut down if it exceeds a threshold operational cost or is inactive beyond a threshold amount of time. The virtual machine control also provides a calculation of the projected cost of running a virtual machine.