Serverless Cluster Power Control for SLO-Aware Core Scaling
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Solution Overview
Problem
Conventional serverless computing systems face challenges in optimizing power consumption while maintaining service level objectives (SLOs), often leading to overprovisioning and high power consumption due to operating at maximum frequency and varying SLO requirements across functions.
Innovation Solution
Implementing a dynamic power management system that measures latency and frequency levels, reallocates cores, and adjusts frequency to meet SLOs, while reducing power consumption by scaling down or shutting off cores when necessary.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the system operates at maximum frequency to meet SLOs, then service level objectives are maintained, but power consumption increases
Solution Approach 1:
The system dynamically adjusts the frequency of processor cores based on real-time SLO requirements and workload conditions. Instead of operating at fixed maximum frequency, the system continuously monitors SLO compliance and scales frequency up or down accordingly, maintaining reliability while optimizing power consumption through adaptive frequency modulation
Solution Approach 2:
The system changes the operational parameters of processor cores by adjusting frequency levels based on measured latency and SLO requirements. The system implements multiple frequency levels and dynamically selects appropriate frequency settings to meet SLOs while minimizing power consumption, rather than always operating at maximum frequency
2Use of energy by moving object
If the system scales down cores to reduce power consumption, then power usage decreases, but SLO compliance may be compromised
Solution Approach 1:
The system implements continuous feedback monitoring of SLO compliance and latency measurements. Based on this feedback, the system dynamically adjusts core scaling decisions - only scaling down when SLOs are comfortably met, and scaling up when latency increases or SLO compliance is at risk, ensuring reliable SLO maintenance while optimizing power consumption
Solution Approach 2:
The system performs preliminary measurements of latency at different frequency levels and uses this data to predict when SLO compliance might be compromised. By proactively adjusting core scaling before SLO violations occur, the system prevents performance degradation while maintaining power efficiency
3Use of energy by moving object
If the system dynamically reallocates cores and adjusts frequency, then power consumption is optimized, but system complexity increases
Solution Approach 1:
The system implements self-service mechanisms where the power management subsystem autonomously monitors SLO compliance, measures latency, and makes frequency adjustment decisions without requiring complex external control. The system serves itself by automatically adapting to workload changes and SLO requirements, reducing the need for complex manual configuration or external intervention
Data Source
AI summary
Embodiments dynamically measure latency for a plurality of functions with a plurality of corresponding frequency levels within a serverless computing cluster; measure a transition latency from an idle state to an active state for the plurality of functions; determine whether a target response time to perform a service level objective (SLO) within the serverless computing cluster is going to be missed; dynamically reallocate at least one core and changing a frequency level across the plurality of functions by scaling down in response to a determination that the target response time to perform the SLO within the serverless computing cluster is going to be met; and dynamically reallocate the at least one core and changing the frequency level across the plurality of functions by scaling up in response to a determination that the target response time to perform the SLO within the serverless computing cluster is going to be missed.