Assurance and Analytic Layers for Cloud Automation
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Solution Overview
Problem
Current information processing systems with virtualization infrastructure face challenges in implementing efficient data collection and event management, particularly in automating resources and workloads, which limits their flexibility and scalability.
Innovation Solution
The implementation of an apparatus with an assurance layer and an analytic layer, utilizing deterministic and indeterministic functional groupings of components to provide data collection and event management functionality, including network topology determination, root cause analysis, real-time stream processing, and batch processing, supports automation in service provider cloud environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If conventional data collection and event management approaches are used in virtualization infrastructure, then implementation is simpler, but automation capability and system intelligence are insufficient
Solution Approach 1:
The patent segments the data collection and event management system into distinct functional layers: an assurance layer for deterministic data collection and a analytic layer for indeterministic event management. This segmentation allows each layer to specialize in specific automation tasks, improving overall automation capability while managing complexity through modular design.
Solution Approach 2:
The patent introduces an intermediary event management layer that bridges the deterministic assurance functions and the indeterministic analytic functions. This intermediary component enables seamless data flow and coordination between layers, enhancing automation capability without requiring complete system redesign.
2Reliability
If deterministic functional grouping is used for data collection, then data reliability is improved, but real-time processing capability is reduced
Solution Approach 1:
The patent divides the processing system into two segments: the assurance layer handling deterministic, reliable data collection, and the analytic layer handling real-time, indeterministic processing. This segmentation allows each segment to optimize for its specific function without compromising the other.
Solution Approach 2:
The patent adds a temporal dimension to the architecture by introducing real-time stream processing capabilities in the analytic layer that operate parallel to the traditional batch processing in the assurance layer. This dimensional addition enables simultaneous reliable data collection and real-time processing.
3Loss of information
If comprehensive data collection is implemented across all virtualization resources, then system visibility is improved, but data processing overhead increases
Solution Approach 1:
The patent applies local quality by tailoring the data collection approach to specific resource types and failure modes within the virtualization infrastructure. Different collection strategies are applied locally based on the deterministic or indeterministic nature of the target resource, improving visibility while minimizing unnecessary processing overhead.
Solution Approach 2:
The patent implements partial data collection by focusing on critical performance indicators and failure-prone components rather than collecting all possible data from every resource. This selective approach maintains adequate system visibility while significantly reducing processing overhead.
Data Source
AI summary
An apparatus comprises at least one processing platform implemented using at least one processing device comprising a processor coupled to a memory. The processing platform comprises virtualization infrastructure, an assurance layer and an analytic layer. The assurance and analytic layers are configured to provide data collection and event management functionality to support automation relating to resources of the virtualization infrastructure and associated workloads. By way of example, the assurance and analytic layers illustratively comprise respective deterministic and indeterministic functional groupings of components. The functional groupings of components of the assurance and analytic layers are utilized to implement closed-loop remediation workflows and other types of automation relating to the virtualization infrastructure resources and their associated workloads.