Application SLI Score Error Budget Monitoring
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Solution Overview
Problem
There is no straightforward way for technology or business teams to determine if an application is working as expected, leading to subjective assessments and conflicts between teams regarding where to focus efforts.
Innovation Solution
A system and method for application operational tracking that ingest service level indicator (SLI) metrics, calculate SLI scores, weight them, combine into an application SLI score, calculate an error budget, and generate notifications to implement restrictions on application enhancements when the budget is breached, aligning business and technology teams' objectives.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If subjective assessment is used to determine application performance, then teams can make decisions without quantitative data, but conflicts arise between business and technology teams regarding where to focus efforts
Solution Approach 1:
The system implements continuous feedback by monitoring SLI metrics and automatically comparing them against SLO thresholds. This creates an objective feedback loop that replaces subjective assessment with quantifiable data, showing exactly whether the application meets agreed-upon service levels and guiding team decisions accordingly
Solution Approach 2:
The error budget concept acts as an intermediary between business and technology teams. It translates technical performance metrics into a business-understandable resource that both teams can agree upon, serving as a neutral mediator that eliminates conflicts by providing a shared framework for decision-making
2Measurement precision
If quantitative performance measurement is implemented, then objective decision-making is enabled, but system complexity increases due to multiple metrics and calculations
Solution Approach 1:
The system segments the complex monitoring task into distinct components: SLI metric collection, SLO threshold definition, error budget calculation, and automated decision-making rules. Each component handles a specific aspect of performance measurement, making the overall system more manageable and understandable despite the quantitative complexity
Solution Approach 2:
The error budget serves as a simplifying intermediary that aggregates multiple complex SLI metrics into a single, intuitive value. Instead of requiring teams to interpret multiple individual metrics, the error budget provides a unified quantitative measure that directly indicates whether the application is within acceptable performance parameters
3Reliability
If error budget monitoring is implemented, then automated restrictions can be applied when performance degrades, but deployment flexibility is reduced
Solution Approach 1:
The system dynamically adjusts deployment flexibility based on real-time performance conditions. When error budget thresholds are met, the system automatically permits deployments; when thresholds are breached, restrictions are applied. This dynamic approach maintains reliability through automated protection while preserving flexibility under normal operating conditions
Solution Approach 2:
The automated restriction mechanism uses feedback from error budget monitoring to make real-time decisions about deployment permissions. The system continuously monitors performance, provides feedback on budget consumption, and automatically adjusts deployment flexibility based on current application health, ensuring stability without permanently restricting adaptability
Data Source
AI summary
A method for application operational monitoring may include an operational monitoring computer program: (1) ingesting a plurality of service level indicator (SLI) metrics for an application, each SLI metric identifying a number of successful observations and a number of total observations; (2) calculating a SLI score for each SLI metric based on the number of successful observations and the number of total observations for the SLI metric; (3) weighting the SLI score for each SLI metric; (4) combining the weighted SLI scores into an application SLI score; (5) calculating a calculated error budget based on the application SLI score; (6) determining that the calculated error budget exceeds an error budget for the application; (7) generating a notification in response to the calculated error budget breaching the error budget; and (8) causing implementation of a restriction on the application, wherein the restriction prevents enhancements to the application.