Dual List Structure for Virtualization Metrics Aggregation
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Solution Overview
Problem
Current techniques for diagnosing issues in virtualization service operations lack efficiency, as they overwhelm storage capacity and are impractical for storing and analyzing execution metrics, leading to undiagnosed performance degradations in cloud computing environments.
Innovation Solution
Implementing a system that generates and aggregates execution metrics using a dual list structure for efficient storage and retrieval, allowing for in-memory processing and compression of data, facilitating faster lookup and better CPU utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If execution metrics for all virtualization service operations are stored in detail, then diagnostic information completeness is improved, but storage capacity is overwhelmed
Solution Approach 1:
The patent combines multiple individual execution metrics into aggregated metrics that represent groups of similar operations. Instead of storing each operation's metrics separately, the system merges them into consolidated records that capture essential performance characteristics while occupying minimal storage space, thus preventing storage capacity from being overwhelmed while retaining diagnostic value
Solution Approach 2:
The patent inverts the traditional approach by not storing raw individual metrics but instead storing pre-aggregated summary metrics. This inversion allows the system to maintain diagnostic information about operation patterns and performance trends without the storage burden of detailed individual records, effectively resolving the contradiction between information completeness and storage capacity
2Measurement precision
If raw execution metrics are stored without aggregation, then data detail is improved, but processing speed is reduced
Solution Approach 1:
The patent applies preliminary aggregation to execution metrics before they are stored and processed. By pre-computing aggregated values such as average execution times and operation counts for groups of similar operations, the system eliminates the need for time-consuming processing of individual raw metrics during analysis, thus improving processing speed while maintaining sufficient data detail through the aggregated representations
3Reliability
If historical execution metrics are retained for long periods, then diagnostic capability is improved, but storage requirements increase
Solution Approach 1:
The patent merges historical execution metrics into aggregated records that consolidate information from multiple time periods. By combining individual operation metrics into grouped aggregated metrics that capture performance trends over time, the system extends the effective diagnostic window without proportionally increasing storage requirements, as the aggregated structure efficiently compresses historical data
Data Source
AI summary
Techniques are provided for aggregating execution metrics for virtualization service operations executed by a virtualization service provider on a host computer while handling requests from a virtualization service client running in a computer system emulator on the host computer. A dual list structure may be used to aggregate execution metrics. A first list may be populated with entries that represent aggregated execution metrics, aggregated over a current interval, for different types of supported virtualization service operations. At the end of the current interval, the entries in the first list may be pushed into a second list of entries that represent historical aggregated execution metrics for historical intervals, a new interval may be initialized, and the first list may be populated with entries representing aggregated execution metrics for the new interval. Managing aggregated execution metrics using a dual list structure facilitates more efficient storage, retrieval, and aggregation.