Cloud Log Correlation via Unique Instance IDs
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Solution Overview
Problem
Existing cloud systems face challenges in accurately and efficiently detecting anomalies, identifying root causes, and monitoring health due to the complexity of correlating logs from different services in OpenStack networks, which is exacerbated by the lack of a global ID and redundant IDs, leading to computational inefficiencies and inaccuracies.
Innovation Solution
A framework is introduced that utilizes an authentication token and multi-layer log processing, along with a unique instance ID in the data model of logs, to enhance log correlation and encapsulation, enabling precise tracing and tracking of correlated logs across cloud components, and employs analytics engines for anomaly detection and root cause analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional log correlation methods are used in cloud systems, then existing infrastructure can be utilized, but the complexity of correlating logs from different services increases computational cost and reduces efficiency
Solution Approach 1:
The patent segments log correlation into service-specific correlation units, where each service maintains its own correlation context. This divides the complex global correlation problem into multiple simpler local correlation tasks, reducing overall computational complexity while maintaining correlation accuracy across services.
Solution Approach 2:
The patent introduces a correlation context as an intermediary structure that mediates between different services. Each service uses correlation contexts to store and manage relevant log information, enabling efficient log correlation without requiring complex global correlation algorithms across all services.
2Reliability
If multiple redundant IDs are used in cloud services, then service identification capability is enhanced, but the difficulty of root cause analysis increases
Solution Approach 1:
The patent creates a universal correlation context structure that serves multiple functions: identifying services, tracking transactions, and facilitating root cause analysis. This single multi-functional structure replaces multiple redundant ID mechanisms, maintaining service identification reliability while simplifying root cause analysis through unified log correlation.
3Measurement precision
If comprehensive monitoring of all cloud transactions is implemented, then health summary accuracy is improved, but the cost and complexity of anomaly detection increases
Solution Approach 1:
The patent segments monitoring into service-specific correlation contexts that automatically capture only the logs relevant to each service's transactions. This selective monitoring approach maintains comprehensive health summary accuracy while reducing the overall complexity and cost of anomaly detection by avoiding unnecessary monitoring of unrelated transactions.
Solution Approach 2:
Each service uses its own correlation context to automatically correlate and summarize its transaction logs, enabling self-monitoring. This self-service approach reduces the need for complex centralized monitoring systems while maintaining accurate health summaries through distributed log correlation within each service.
4Reliability
If log correlation is performed across all services, then comprehensive health monitoring is achieved, but computational resources are consumed excessively
Solution Approach 1:
The patent segments computational tasks into service-specific correlation contexts, where each service independently correlates its own logs. This segmentation reduces the computational burden from processing all service logs simultaneously to processing only relevant logs in each service context, maintaining health monitoring reliability while significantly reducing computational resource consumption.
Data Source
AI summary
A framework to handle monitoring and automatic fault manifestation in cloud networks. Multiple techniques correlate the logs of different cloud services or generate independent capsules for each component, VM, storage, or transaction. In a first exemplary technique, an authentication token is provided by an authentication service for logs during a period of an event. In a second exemplary technique, a unique instance ID for multiple distinct processes may be created in a data model of notification logs or service logs.