Service Level Compliance Analysis for IT Infrastructure Optimization
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Solution Overview
Problem
In complex IT infrastructures, determining where improvements or modifications can be made to ensure Service Level Agreement (SLA) compliance is difficult due to the complexity of interdependencies and the cost implications of over or under specifying components, leading to potential contractual penalties.
Innovation Solution
A method and apparatus for analyzing a computer infrastructure by obtaining and processing service level objective compliance data, identifying suitable components for modification, and determining optimal configuration item values to meet SLA requirements, using a service level manager, data warehouse, and scenario analyzer to calculate differences and propose modifications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If components are over specified to ensure SLA compliance, then service reliability is improved, but cost increases and unnecessary redundancy occurs
Solution Approach 1:
The patent changes the parameters of configuration items by calculating the difference between actual compliance data and target compliance data. This allows determining optimal parameter values for components that meet SLA requirements without over-specification, thereby reducing cost and redundancy while maintaining reliability.
Solution Approach 2:
The patent implements a feedback mechanism by monitoring actual service level compliance and comparing it against target compliance levels. This feedback loop enables continuous optimization of component specifications, ensuring components are neither over-nor under-specified, thus balancing reliability with cost efficiency.
2Quantity of substance
If components are under specified to reduce cost, then initial investment is reduced, but SLA compliance is at risk and penalty risk increases
Solution Approach 1:
The patent dynamically adjusts configuration item parameters based on calculated differences between actual and target compliance. This ensures components are specified at the minimum necessary level to meet SLA requirements, avoiding both over-specification and under-specification, thus reducing cost while maintaining compliance.
Solution Approach 2:
The patent applies partial action by implementing monitoring and analysis for only the most critical configuration items that have the greatest impact on SLA compliance. This selective approach reduces overall system complexity and cost while ensuring essential compliance requirements are met.
3Measurement precision
If complex monitoring and analysis is implemented to determine optimal component modifications, then component identification accuracy is improved, but system complexity increases
Solution Approach 1:
The patent segments the complex infrastructure into individual configuration items and monitors them separately. By breaking down the overall SLA compliance into component-specific compliance metrics, the system achieves high identification accuracy without requiring a monolithic complex analysis system.
Solution Approach 2:
The patent introduces an intermediary analysis layer that sits between raw monitoring data and decision-making. This intermediary calculates compliance differences and identifies target configuration items, simplifying the overall system architecture while maintaining high accuracy in component identification.
Data Source
AI summary
According to one embodiment of the present invention, there is provided a method of analyzing a computer infrastructure providing a service, an intended quality level of the service being defined by at least one service level objective defining a service level quality objective and a related compliance level, the computer infrastructure comprising a plurality of components, the method comprising: obtaining first service level objective compliance data for a selected service level objective, the compliance data being calculated using data collected from the computer infrastructure; calculating second service level objective compliance data for the selected service level objective using in part the collected data and for a selected service level quality objective a value that meets that objective; calculating a difference between the first and second data; and identifying, based on the calculated difference, one or more components suitable for modification.