Post-deployment Impact Detection via Telemetry Analysis
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Solution Overview
Problem
Current technologies lack a scalable and reliable method to measure the positive or negative impacts of deployments or isolated features on customer workloads, leading to potential performance degradations that are not detected by pre-deployment benchmark tests.
Innovation Solution
A flighting framework that leverages telemetry information from periodic workloads to determine the impact of changes by analyzing pre- and post-deployment performance metrics, using statistical tests to adapt to changing performance thresholds and identify early regressions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If pre-deployment benchmark tests are used to assess deployment impact, then deployment validation is performed, but performance degradations are not detected reliably
Solution Approach 1:
The patent implements feedback by continuously collecting telemetry data from production systems after deployment and comparing post-deployment metrics with pre-deployment baselines. This closed-loop feedback mechanism enables reliable detection of performance degradations that pre-deployment tests miss, directly resolving the contradiction between deployment validation and degradation detection reliability.
Solution Approach 2:
The patent establishes pre-deployment performance baselines before changes are released to production. By capturing telemetry data and defining expected performance ranges in advance, the system prepares reference points that enable accurate post-deployment comparison, improving both validation reliability and degradation detection precision.
2Reliability
If flighting is used to progressively roll out changes, then deployment risk is reduced, but impact measurement capability is limited
Solution Approach 1:
The patent creates a universal telemetry collection framework that serves multiple functions simultaneously: it monitors system health for stability, measures deployment impact by comparing pre- and post-deployment metrics, and provides data for both flighting progression decisions and overall deployment validation. This multi-functional approach eliminates the information loss limitation while maintaining flighting benefits.
Solution Approach 2:
The system implements continuous feedback through telemetry collection that provides actionable information at each flighting stage. By measuring actual performance impacts in real-world conditions and feeding this information back to deployment decision-makers, the system enables informed progression decisions while capturing complete impact measurement data that traditional flighting would miss.
3Measurement precision
If telemetry information is collected and analyzed, then performance metrics are determined, but system complexity increases
Solution Approach 1:
The patent implements self-service by having the system automatically collect its own telemetry data, perform baseline comparisons, and generate impact assessments without requiring external intervention. The telemetry infrastructure serves itself by utilizing existing system logs, metrics, and event data that are already being collected for operational purposes, thereby improving measurement precision without proportionally increasing system complexity.
Solution Approach 2:
The telemetry analysis system is designed to be multi-functional, serving both operational monitoring purposes and deployment impact assessment purposes simultaneously. By reusing existing telemetry infrastructure and data collection mechanisms for dual purposes, the system achieves precise performance metric measurement without the complexity overhead of dedicated separate systems.
Data Source
AI summary
System, methods, apparatuses, and computer program products are disclosed for determining post-deployment impact of a deployment based on telemetry information. Telemetry information is analyzed to determine a periodic workload executing on one or more of a plurality of endpoints. Pre-deployment performance metrics and post-deployment performance metrics are then determined based on telemetry information generated before the deployment and after the deployment, respectively. The post-deployment impact of the deployment may then be determined by comparing the pre-deployment performance metrics and the post-deployment performance metrics. Actions may be performed based on the post-deployment impact.