Distributed Tracing System Cost Analysis
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Solution Overview
Problem
Detailed tracing operations during development and debugging can adversely affect system performance by consuming large amounts of processing, storage, and network bandwidth, leading to performance degradation and resource exhaustion.
Innovation Solution
A distributed tracing system divides trace objectives across multiple application instances, performs cost analysis to identify burdensome objectives, and optimizes data collection by analyzing periodicities, allowing for lightweight, non-intrusive tracing workloads that provide a holistic view of application performance while minimizing resource consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If detailed tracing operations are performed during development and debugging, then tracing data completeness and analysis accuracy are improved, but system performance deteriorates due to consuming large amounts of processing, storage, and network bandwidth
Solution Approach 1:
The patent divides the tracing system into multiple independent tracer instances distributed across different devices. Each tracer collects a subset of tracing data, and the results are aggregated to form a complete picture. This segmentation allows detailed tracing to be performed without overloading a single system, thus maintaining both data completeness and system performance.
Solution Approach 2:
The patent implements cost analysis to determine an optimal subset of tracing objectives to deploy. Rather than collecting all possible tracing data (excessive action), the system selects a partial set that provides statistically significant results while consuming acceptable resources. This resolves the contradiction by performing enough tracing to maintain accuracy without exhausting system resources.
2Loss of information
If trace objectives are deployed on separate instances of an application running on different devices, then tracing data comprehensiveness is improved, but device resource consumption increases
Solution Approach 1:
The tracing workload is segmented and distributed across multiple application instances on different devices. Each device runs a lightweight tracer that collects a portion of the required data, reducing the resource burden on any single device while collectively achieving comprehensive tracing coverage.
Solution Approach 2:
The system performs cost analysis on potential trace objectives and selects those with acceptable resource consumption parameters. By changing the parameters of trace objectives (selecting lighter-weight objectives), the system achieves comprehensive data collection across distributed devices without excessive resource consumption on any individual device.
3Loss of energy
If cost analysis is performed to identify burdensome trace objectives, then resource budget compliance is improved, but tracing setup complexity increases
Solution Approach 1:
The system performs automated cost analysis of trace objectives to identify which ones are burdensome. This self-service approach allows the tracing system to automatically select an optimal set of objectives that comply with resource budgets without requiring manual configuration or complex setup by users, thus maintaining resource compliance while minimizing setup complexity.
Data Source
AI summary
A tracing system may perform cost analysis to identify burdensome or costly trace objectives. For a burdensome objective, two or more objectives may be created that can be executed independently. The cost analysis may include processing, storage, and network performance factors, which may be budgeted to collect data without undue performance or financial drains on the application under test. A larger objective may be recursively analyzed to break the larger objective into smaller objectives which may be independently deployed.