Flexible Triggering of Cloud Functions to Reduce Resource Scale Out
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Solution Overview
Problem
Cloud computing costs increase due to resource scale out, which can be triggered without regard to loading and cost, leading to inefficient resource utilization and higher expenses.
Innovation Solution
Implementing flexible triggering of cloud functions, where the execution of code can be adjusted or varied based on the status of monitored resources within a specified time window, allowing for variable triggering to minimize resource usage and costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If triggered code executes based on specified trigger without regard to resource loading, then code execution reliability is improved, but resource utilization efficiency deteriorates and costs increase
Solution Approach 1:
The patent applies dynamics by making the trigger execution time flexible rather than fixed. The system monitors resource loading conditions and dynamically adjusts the actual execution time within a permissible time window, allowing the trigger mechanism to adapt to changing resource states and optimize execution timing based on real-time conditions
Solution Approach 2:
The patent changes the parameter of trigger execution time from a fixed specified time to a flexible time window. By monitoring resource loading parameters and adjusting execution timing within the window, the system transforms static trigger parameters into dynamic ones that respond to resource conditions, thereby improving resource utilization while maintaining execution reliability
2Productivity
If resource scale out is triggered without regard to loading status, then computing task completion is ensured, but resource costs and power consumption increase
Solution Approach 1:
The patent implements feedback by continuously monitoring resource loading conditions and using this information to determine optimal execution timing. The system receives feedback about resource status and adjusts trigger execution accordingly, ensuring tasks complete while minimizing unnecessary resource scale-out and associated energy consumption
Solution Approach 2:
The patent applies preliminary action by monitoring resource loading conditions in advance within the time window before the specified trigger time. The system proactively identifies optimal execution moments based on predicted or current resource states, preventing unnecessary resource scale-out before it occurs, thereby reducing energy consumption while ensuring task completion
Data Source
AI summary
Methods, systems, and computer program products are described herein for flexible triggering of triggered code (e.g. cloud functions). Flexible triggering may reduce costs, for example, by adjusting triggered code execution to avoid resource scale out (e.g. additional resources and/or power consumption). A specified (e.g. preferred) execution trigger may be modified or replaced, for example, by a flexible trigger configured to provide variable triggering. Triggering may be varied, for example, based on the status of one or more monitored resources in an execution environment. Variable triggering may be constrained by a time window (e.g. before, during and/or after a specified trigger). Flexible triggers may be specified (e.g. trigger type, parameters and constraints), for example, in service level agreements, by tenants and/or by cloud providers.