Changelog Correlation in Multi-Tenant Cloud Services
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Solution Overview
Problem
In large-scale multi-tenant cloud services, it is challenging to determine the source of anomalies following changes to hardware or software components due to the complexity of thousands of servers and networking components, making it difficult to identify impacted components and correlate changes with anomalies.
Innovation Solution
Implementing a changelog transformation and correlation system that collects, transforms, and correlates changelogs from various services to identify changes and their impacts on components, providing a user interface for tenants to view potential or actual impacts on their services.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If a large number of servers and networking components are deployed to provide multi-tenant cloud services, then service capacity and coverage are improved, but system complexity increases making it difficult to identify the source of anomalies
Solution Approach 1:
The patent segments the complex system by introducing a change management service that separately tracks and manages changes to individual components (servers, networking equipment, software). This segmentation allows anomalies to be traced to specific components rather than searching through the entire complex system, resolving the contradiction by maintaining high component quantity while managing complexity through organized tracking.
Solution Approach 2:
The change management service acts as an intermediary between the deployed components and the monitoring system. It collects change information from various components and presents it in a unified manner, reducing the complexity of managing thousands of individual components while maintaining the ability to track each one's changes and identify anomaly sources.
2Adaptability or versatility
If hardware and software changes are made to improve service functionality, then service capabilities are enhanced, but the difficulty of determining the source of anomalies increases
Solution Approach 1:
The system performs preliminary action by requiring that all changes to components be registered with the change management service before implementation. This advance registration creates a record of what changes are made, when they are made, and what components are affected, enabling easy traceability when anomalies occur without hindering service functionality enhancements.
Solution Approach 2:
The change management service provides feedback by tracking changes and correlating them with service anomalies. When an anomaly occurs, the system can query the change management service for recent changes to affected components, providing immediate feedback about potential causes without requiring complex manual investigation.
3Measurement precision
If comprehensive tracking of all component changes is implemented, then anomaly source identification is improved, but system complexity and data management burden increase
Solution Approach 1:
The change management service provides multi-functionality by handling various types of changes (hardware, software, configuration) through a single unified system. It can track changes across different component types and service areas using consistent data structures and query interfaces, improving anomaly tracking precision while reducing data management complexity through standardization.
Data Source
AI summary
Technologies are described herein for changelog transformation and correlation in a multi-tenant cloud service. Components within the multi-tenant cloud service generate changelogs that describe changes made to hardware or software components within the multi-tenant cloud service. The changelogs are received and transformed from different schemas into a common schema. A central change management service (“CCMS”) exposes a network service application programming interface (“API”), or other type of interface, through which other network services can obtain the changelogs that have been transformed into the common schema. For example, services can obtain changelogs in order to correlate changes to anomalies or other events taking place in the multi-tenant cloud service, to identify upstream or downstream components that might be impacted by a change, to provide a user interface for viewing the changelogs, the correlation, or the potential impact of a change, and/or to perform other types of functions.