Cloud Service Operational Management via Dynamic Error Budget Thresholds
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Solution Overview
Problem
Cloud computing systems face challenges in determining the optimal balance between developing new software applications and improving existing ones, as excessive focus on either can lead to subpar performance or delayed deployments.
Innovation Solution
A cloud computing system utilizes a combination of service level agreements (SLAs) and error budgets to determine a switching threshold, allowing operations to shift between new builds and performance enhancements, ensuring guaranteed performance metrics are met while allowing for new feature deployments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If operations are mainly focused on developing new builds of software applications, then new features and updates can be deployed, but performance of existing software applications may suffer
Solution Approach 1:
The system dynamically changes operational parameters by adjusting the switching threshold based on error budget consumption rates. When error budget is consumed slowly, the threshold allows more new build deployments; when consumed quickly, the threshold restricts deployments to preserve performance of existing applications. This resolves the contradiction by making the operational focus adaptive rather than fixed.
Solution Approach 2:
The patent implements dynamic operation shifting where the system automatically transitions between development-focused and performance-focused modes based on real-time monitoring of error budget consumption. The switching threshold is not static but adapts to current system state, allowing the balance between new features and existing application performance to be continuously optimized.
2Reliability
If excessive focus is placed on improving performance of existing software applications, then performance metrics are maintained, but deployment of new builds with updated features is delayed or limited
Solution Approach 1:
The system modifies the switching threshold parameter dynamically based on the rate of error budget consumption. When performance improvement activities consume the error budget slowly, the threshold is adjusted to permit faster deployment of new builds, thus maintaining performance metrics while improving productivity in releasing updates.
Solution Approach 2:
The system continuously monitors error budget consumption rates and uses this feedback to adjust the switching threshold in real-time. This feedback loop ensures that performance improvements are pursued only when they do not excessively consume the error budget, thereby maintaining performance metrics while enabling continuous deployment of new builds when appropriate.
3Ease of operation
If a fixed switching threshold is used to determine when to shift operations, then operational decisions are simple to make, but flexibility to adapt to varying error budget consumption rates is reduced
Solution Approach 1:
The patent transforms the static switching threshold into a dynamic one that automatically adapts to varying error budget consumption rates. The system calculates the threshold based on the observed consumption rate, maintaining ease of operation through automated calculation while achieving adaptability to different operational contexts and error budget scenarios.
Data Source
AI summary
Techniques for managing operation in cloud computing systems are disclosed herein. In one embodiment, a method can include receiving data representing a guaranteed value of a performance metric of a cloud service and an error budget and deriving a switching threshold based on a combination of the value of the performance metric and the error budget. The method also includes determining a current value of the performance metric of the cloud service and causing the cloud computing system to selectively switch between operational modes for providing the cloud service based on a comparison between the determined current value of the performance metric and the switching threshold.