Serverless Root Cause Analysis for Cloud Application Diagnostics
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Solution Overview
Problem
Users of remote computing resource services face challenges in effectively identifying and resolving application performance issues due to the complexity and cost of using multiple tools for observability, which increases the mean time to resolution and fails to adapt to changing application infrastructure.
Innovation Solution
The implementation of user-supplied diagnostics that allow customers to define analysis operations and time windows for root cause analysis, utilizing an API to monitor resources and perform serverless compute functions, thereby facilitating automated identification and resolution of performance issues.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple tools are used for observability to identify application performance issues, then measurement precision is improved, but device complexity increases and loss of time increases
Solution Approach 1:
The patent combines multiple observability tools (logging, metrics, traces) into a single unified platform provided by the computing resource service provider. This consolidation maintains comprehensive measurement precision while reducing device complexity by eliminating the need for customers to deploy and manage multiple separate tools.
Solution Approach 2:
The unified observability platform performs multiple functions including logging, metrics collection, trace analysis, and automated root cause analysis within a single system. This multi-functionality approach maintains comprehensive observability capabilities while simplifying the overall system architecture.
2Measurement precision
If multiple tools are used for observability to identify application performance issues, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The system implements automated root cause analysis that performs self-service by automatically analyzing logs, metrics, and traces to identify performance issues without requiring manual intervention from customers. This automation maintains comprehensive observability while significantly reducing the mean time to resolution.
Solution Approach 2:
The system pre-configures analysis operations and time windows for root cause analysis, so that when performance issues occur, the analysis is already prepared and can execute immediately. This preliminary preparation maintains measurement precision while reducing response time.
3Measurement precision
If logging and resource usage data are provided to customers, then measurement precision is improved, but ease of operation deteriorates
Solution Approach 1:
The system acts as an intermediary between the raw logging and resource usage data and the customer. Instead of providing raw data that requires complex analysis, the system processes and analyzes the data, then presents actionable insights to customers. This maintains data availability while dramatically improving ease of operation.
Solution Approach 2:
The system performs automated analysis of logging and resource usage data, serving itself by identifying patterns and root causes without requiring customer expertise in data analysis. This approach maintains comprehensive data availability while making the system easy to use for customers regardless of their technical expertise.
Data Source
AI summary
A computing resource services provider receives user diagnostics comprising analysis operations to be performed on one or more computing resources. The computing resource services provider monitors resources indicated by the user diagnostics. When one or more computing resources exceed a threshold value or otherwise indicate abnormalities in computing resource usage, the computing resource services provider performs one or more analysis operations to determine one or more causes for increased computing resource usage. Results of the one or more analysis operations are presented to a user once the computing resource services provider completes the one or more analysis operations.