SLO-Based CICD Framework Using Burn Rates for Chaos Testing
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Solution Overview
Problem
Existing CICD methodologies rely on SLIs for alerting, which are noisy, require significant developer effort, and are sensitive to production volume changes, leading to false positives and unmonitored issues.
Innovation Solution
A SLO-based CICD framework that uses SLOs for Canary deployments, chaos engineering, and performance testing, avoiding threshold-based and cause-based alerts by employing multi-window burn rates and dynamic chaos fault injection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Difficulty of detecting and measuring
If SLI-based alerting is used for monitoring, then detection capability is improved, but false positives increase and developer effort increases
Solution Approach 1:
The patent changes the monitoring parameter from SLI (Service Level Indicator) to SLO (Service Level Objective) burn rate. Instead of alerting on individual metric thresholds, the system calculates the burn rate of error budget over time windows, transforming the monitoring approach from reactive threshold-based alerting to proactive budget consumption tracking, thereby reducing false positives while maintaining detection capability
Solution Approach 2:
The patent introduces SLO burn rate as an intermediary metric between raw SLIs and alerting decisions. The burn rate calculation serves as a mediator that aggregates multiple SLIs and contextual factors into a single reliability indicator, filtering out noise and reducing false alerts while preserving true issue detection
2Difficulty of detecting and measuring
If SLI-based alerting is used for monitoring, then detection capability is improved, but developer effort increases
Solution Approach 1:
The system implements self-service monitoring by automatically calculating SLO burn rates and generating alerts based on predefined policies, eliminating the need for developers to manually configure and manage multiple SLI thresholds. The automated burn rate calculation and alerting reduce developer operational effort while maintaining comprehensive monitoring coverage
Solution Approach 2:
The SLO burn rate mechanism serves multiple functions simultaneously: it monitors service health, predicts future reliability, triggers alerts, and guides remediation priorities. This multi-functional approach replaces numerous individual SLI-based monitoring configurations with a single universal metric, significantly reducing developer effort
3Ease of operation
If threshold-based alerts are used, then simple detection is achieved, but sensitivity to production volume changes causes false positives
Solution Approach 1:
The patent implements dynamic alerting thresholds based on SLO burn rate calculations that adapt to changing production volumes. Instead of static thresholds, the system dynamically adjusts expectations based on actual service performance and error budget consumption patterns, allowing alerts to remain sensitive to true issues while being insensitive to normal volume fluctuations
Solution Approach 2:
The system performs preliminary analysis by calculating historical burn rates and establishing baseline expectations before setting alert thresholds. This preliminary characterization of normal behavior allows the system to distinguish between expected variations due to production volume changes and actual reliability issues, reducing false positives
Data Source
AI summary
A Service Level Objective (SLO)-based Continuous Integration/Continuous Development (CICD) framework is disclosed, which enables SLO-based Canary deployments, SLO-based chaos engineering, and/or SLO-based performance testing. The SLO-based CICD framework enhances and simplifies CICD pipelines and brings the pipelines in line with Site Reliability Engineering (SRE) best practices. By relying on SLOs rather than SLIs, the SLO-based CICD framework avoids the use of threshold-based alerts, which can be noisy and error prone, and the thresholds associated with threshold-based alerts can change over time due to changes in production volume. The SLO-based CICD framework uses multi-window burn rates when evaluating SLOs, which removes the reliance on a static, predefined thresholds of SLI threshold-based alerting, and removes sensitivity of such evaluations to changes in production volume.