Cloud Service Context Correlator for Non-Intrusive Log Analysis
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Solution Overview
Problem
Existing solutions for context correlation across cloud services are intrusive, require specific log formats, or tight coupling, making them unsuitable for loosely coupled cloud services without code changes.
Innovation Solution
A non-intrusive cloud service context correlator injects a global execution context identifier (GECID) into log messages, allowing correlation across multiple cloud services without requiring code changes, and can be applied to both synchronous and asynchronous REST flows.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If existing context correlation solutions are implemented, then context correlation capability is improved, but code changes and tight coupling are required
Solution Approach 1:
The patent introduces a context correlator as an intermediary component that sits between the logging framework and the cloud services. This correlator intercepts log messages, injects correlation identifiers, and formats them without requiring modifications to the cloud services themselves. The correlator acts as a mediator that enables context correlation while maintaining the independence and loose coupling of the underlying cloud services.
Solution Approach 2:
The solution segments the context correlation functionality into a separate, standalone component (the context correlator) that is distinct from the cloud services. This segmentation allows the correlation logic to be implemented independently, avoiding tight coupling with the service code while still enabling comprehensive context correlation across all services in the chain.
2Reliability
If log messages are formatted in a particular way, then context correlation is improved, but flexibility and adaptability are reduced
Solution Approach 1:
The context correlator dynamically changes the parameters of log messages by injecting correlation identifiers and formatting them according to a standardized scheme. This parameter transformation enables context correlation while the correlator's configuration-driven approach allows it to adapt to different log formats and service types without requiring code changes, thus maintaining flexibility.
Solution Approach 2:
The context correlator is designed as a universal component that can handle multiple types of cloud services and log formats. It provides multi-functional capability by working with synchronous and asynchronous REST flows, different service types, and various logging frameworks, all through a single standardized interface that doesn't require service-specific customization.
3Reliability
If cloud services are tightly coupled, then context correlation is improved, but system flexibility and independence are reduced
Solution Approach 1:
The context correlator serves as an intermediary layer that enables context correlation without requiring tight coupling between cloud services. Each service can independently log messages, and the correlator uniformly processes these messages across the service chain, maintaining service independence while achieving comprehensive correlation.
Solution Approach 2:
Each cloud service independently generates its own log messages with the context correlator injecting correlation identifiers. The services themselves don't need to be aware of or participate in the correlation mechanism - they simply continue their normal logging operations while the correlator automatically processes their messages, allowing services to remain independent and self-sufficient.
Data Source
AI summary
In accordance with an accordance, described herein is a system and method for providing non-intrusive context correlation across a plurality of cloud services in different cloud environments. A cloud service context correlator can be configured with each cloud service, and can pass a common identifier through the cloud services. The cloud service context correlator can identify one or more loggers in a cloud service and their types, and create a log formatter for each logger based on its type to inject the common identifier into log messages generated by the logger. The injected common identifier can correlate log messages from the cloud services, and can be used to search for the correlated log messages in a dashboard of a data visualization tool. The cloud service context correlator does not require code changes for each cloud service, and can be applied to a synchronous or asynchronous representational state transfer (REST) flow.