Cloud Deployment Validation Engine for Automated Fault Diagnosis
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Solution Overview
Problem
Datacenter operators face difficulties in detecting and diagnosing failures across multiple servers and operating system instances, especially timing-dependent or transient issues, due to the lack of integrated error-detection mechanisms, leading to prolonged configuration and installation times for cloud services.
Innovation Solution
A cloud deployment infrastructure validation engine that automates install validation and failure diagnostics through a generic, flexible framework for authoring and executing state validators, diagnostics, and remedial actions, consuming data from installation log files and real-time events, and enabling self-healing operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual correlation and interpretation of error logs and events is performed across multiple systems, then diagnostic accuracy can be achieved, but time consumption and operational complexity increase significantly
Solution Approach 1:
The system performs self-diagnosis by automatically correlating error logs and events across multiple systems without requiring manual operator intervention. The validation engine autonomously identifies failures, determines root causes, and suggests resolutions, enabling the system to serve its own diagnostic needs efficiently.
Solution Approach 2:
A validation engine acts as an intermediary component that sits between multiple datacenter systems and the operator. This engine automatically collects, correlates, and analyzes error logs and events from various sources, presenting unified diagnostic information to operators without requiring them to manually correlate data across systems.
2Difficulty of detecting and measuring
If integrated error-detection mechanisms are implemented across multiple servers, then diagnostic capability improves, but system complexity increases
Solution Approach 1:
The validation engine is designed as a universal system that can detect and diagnose errors across multiple different server types, operating systems, and datacenter components through a single unified platform. This multi-functional approach improves detection capability without requiring separate complex mechanisms for each system type.
Solution Approach 2:
The system merges multiple error-detection mechanisms from different servers and systems into a single integrated validation engine. By combining log collection, event correlation, and diagnostic analysis into one unified system, the solution improves overall detection capability while managing complexity through consolidation rather than proliferation of separate mechanisms.
3Productivity
If automated validation and diagnostic systems are deployed, then installation time and service configuration speed improve, but implementation complexity and resource requirements increase
Solution Approach 1:
The validation engine performs preliminary validation and diagnostic actions automatically during the installation and configuration process. By proactively detecting and diagnosing issues as they arise rather than waiting for manual intervention, the system accelerates installation speed while managing complexity through automation of routine diagnostic tasks.
Solution Approach 2:
The system implements continuous feedback loops where validation results and diagnostic information are automatically fed back into the installation and configuration process. This enables real-time adjustments and automated remediation actions that speed up service deployment while managing complexity through closed-loop control rather than requiring complex manual coordination.
Data Source
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AI summary
Embodiments of the invention provide a set of validators that can be used to determine whether an installation is operating within desired parameters and is in compliance with any requirements. The validators may be provided with a software application or release, for example, and may be run during and/or after installation to test the application operation. A set of self-healing operations may be triggered when faults are detected by the validators. This allows a software application to auto-diagnose and auto-self-heal any detected faults.