Telemetry-Driven Workload Orchestration for Multi-Objective Allocation
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Solution Overview
Problem
Cloud computing environments face challenges in consistently optimizing the assignment of workloads among compute nodes to balance multiple resource allocation objectives such as cost savings, responsiveness, and resource utilization, as initial configurations often compromise on one objective at the expense of others, and dynamic adjustments are difficult to implement effectively.
Innovation Solution
An orchestrator server system that dynamically assigns and adjusts workloads among managed nodes based on real-time telemetry data and resource allocation objectives, using data analytics to identify trends, predict future resource utilization, and apply adjustments to achieve Pareto-efficient resource allocation, ensuring that multiple objectives are met without compromising on any one.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If additional hardware resources and higher operating speeds are allocated to workloads, then cloud service responsiveness is improved, but power usage and heat production increase
Solution Approach 1:
The patent implements dynamic workload assignment that continuously monitors and adjusts resource allocation based on changing conditions. The system transitions from static initial configurations to dynamic reassignment, allowing compute nodes to adapt their power consumption and performance levels according to real-time workload phases and multiple competing objectives, thereby resolving the contradiction between speed and energy use
Solution Approach 2:
The system changes operational parameters by adjusting workload assignments across compute nodes based on monitored performance metrics and objective satisfaction levels. By modifying assignment parameters dynamically rather than maintaining fixed allocations, the system can shift between power-efficient and performance-optimized states to balance responsiveness against power consumption
2Loss of energy
If workload assignment is optimized for cost savings through reduced power usage, then operational costs decrease, but cloud service responsiveness deteriorates
Solution Approach 1:
The system employs parameter changes by adjusting workload assignments to satisfy multiple objectives simultaneously. Rather than fixing parameters for single-objective optimization, the system dynamically modifies assignment parameters to balance power consumption against service responsiveness, using monitored telemetry data to determine optimal parameter settings that achieve cost savings without severe performance degradation
Solution Approach 2:
The patent implements feedback mechanisms that monitor both power consumption metrics and service responsiveness indicators. This feedback loop enables the system to detect when optimization for power savings begins to degrade responsiveness, triggering reassignment adjustments that restore acceptable service levels while maintaining improved energy efficiency
3Reliability
If initial workload assignment is configured to meet certain objectives, then those specific objectives are satisfied, but other objectives are insufficiently satisfied
Solution Approach 1:
The patent applies universality by designing a workload assignment system that serves multiple objectives simultaneously rather than being specialized for a single objective. The multi-objective optimization framework enables the same assignment mechanism to satisfy diverse goals including power efficiency, responsiveness, load balancing, and resource utilization, making the system versatile across different operational priorities
Solution Approach 2:
The system transitions from static single-objective optimization to dynamic multi-objective optimization. By continuously monitoring satisfaction levels across multiple objectives and adjusting assignments in response to changing conditions, the system adapts to balance competing goals, ensuring reliable achievement of various objectives rather than excelling at one while failing others
4Device complexity
If workload assignment remains static after initial configuration, then implementation complexity is reduced, but the system fails to consistently satisfy objectives as workloads change over time
Solution Approach 1:
The patent implements self-service by enabling the workload assignment system to automatically monitor its own performance, detect objective satisfaction deficiencies, and trigger reassignment operations without external intervention. This self-managing capability allows the system to maintain reliable objective satisfaction through dynamic adaptation while keeping operational complexity hidden from users
Solution Approach 2:
The system employs feedback loops that continuously monitor workload characteristics and objective satisfaction levels. When changes in workload phases cause objectives to become insufficiently satisfied, the feedback mechanism triggers automated reassignment. This feedback-driven approach maintains reliability without requiring complex manual management, as the system self-corrects based on monitored conditions
Data Source
AI summary
Technologies for allocating resources of managed nodes to workloads to balance multiple resource allocation objectives include an orchestrator server to receive resource allocation objective data indicative of multiple resource allocation objectives to be satisfied. The orchestrator server is additionally to determine an initial assignment of a set of workloads among the managed nodes and receive telemetry data from the managed nodes. The orchestrator server is further to determine, as a function of the telemetry data and the resource allocation objective data, an adjustment to the assignment of the workloads to increase an achievement of at least one of the resource allocation objectives without decreasing an achievement of another of the resource allocation objectives, and apply the adjustments to the assignments of the workloads among the managed nodes as the workloads are performed. Other embodiments are also described and claimed.