Flow Template-Based Capacity Planning for System Resource Optimization

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Solution Overview

Problem

The existing capacity planning process for systems hosting multiple flows is inefficient due to the need for manual setup of scenarios, leading to inaccurate capacity predictions and resulting in overprovisioning, which increases costs for customers.

Innovation Solution

A method that links running flows to templates describing their functions, allowing for the grouping and comparison of similar flows, generating performance summaries and reports that provide contextualized data to improve capacity planning and reduce overprovisioning.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If manual scenario setup is used for capacity planning, then measurement precision is improved, but device complexity and time consumption increase

Engineering Contradiction:

Improvecapacity prediction accuracyVSAvoidmanual setup complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The patent creates virtual copies of production flows as test flows based on flow templates. These test flows replicate the structure and behavior of actual flows without requiring manual scenario setup, enabling automated capacity planning while maintaining measurement precision through systematic performance testing

Inventive Principle:

Principle #26Copying

Solution Approach 2:

The patent performs preliminary actions by automatically generating test flows from templates before capacity planning execution. This preliminary template-based flow creation eliminates the need for manual scenario setup during actual capacity planning, reducing complexity while maintaining accuracy

Inventive Principle:

Principle #10Preliminary action

2Device complexity

If limited scenario sampling is used, then device complexity is reduced, but measurement precision deteriorates

Engineering Contradiction:

Improvescenario setup complexityVSAvoidcapacity prediction accuracy

Core Design Contradiction:

Device complexityVSMeasurement precision

Solution Approach 1:

The patent creates templates that serve multiple functions: they define flow structures, generate test scenarios, and enable automated capacity planning across multiple flows. This universal template approach allows comprehensive scenario coverage without increasing setup complexity, as one template can generate multiple test flows systematically

Inventive Principle:

Principle #6Universality (Multi-functionality)

Solution Approach 2:

The patent segments the capacity planning process into template definition and automated test flow generation. This segmentation allows complex scenario sampling to be broken down into manageable template components, enabling comprehensive testing without overwhelming manual setup complexity

Inventive Principle:

Principle #1Segmentation

3Reliability

If 100% overhead capacity is provisioned for prediction inaccuracy, then reliability is improved, but loss of substance increases

Engineering Contradiction:

Improvecapacity planning reliabilityVSAvoidoverprovisioning cost

Core Design Contradiction:

ReliabilityVSLoss of substance

Solution Approach 1:

The patent implements feedback by systematically collecting performance data from test flows and using it to refine capacity predictions. This feedback loop enables accurate capacity planning without excessive overhead, as the system learns from actual performance measurements to optimize capacity allocation and reduce unnecessary overprovisioning

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The patent enables dynamic capacity planning by continuously gathering performance data and adjusting capacity predictions based on actual measurements. This dynamic approach replaces static 100% overhead provisioning with adaptive capacity allocation that matches actual needs, reducing waste while maintaining reliability

Inventive Principle:

Principle #15Dynamics

4Productivity

If performance data is collected without contextualization, then productivity is improved, but loss of information increases

Engineering Contradiction:

Improveperformance data collection efficiencyVSAvoidperformance context information

Core Design Contradiction:

ProductivityVSLoss of information

Solution Approach 1:

The patent introduces templates as intermediaries between raw performance data and meaningful insights. Templates provide the contextual framework that connects performance measurements to flow functions and characteristics, enabling efficient data collection while preserving essential context information through the template-Flow-performance data relationship

Inventive Principle:

Principle #24Intermediary (Mediator)

Data Source

PatentUS11456933B2Generating and updating a performance report

Publication Date: 2022.09.27 INTERNATIONAL BUSINESS MACHINE CORPORATION

AI summary

A computer-implemented method for generating and updating a performance report for a system adapted to run a plurality of flows, which enables the performance data of individual running flows to be compared to flows with a similar function. This is achieved by linking each of the running flows to one of a plurality of templates which describes a function of a flow. Each template may have an associated performance summary generated for it, based on the performance data of the running flows linked to the template. A performance report can be generated from a plurality of the performance summaries. The performance report can then be updated by running a plurality of test flows on the spare capacity of the system, while obtaining test performance data from the test flows. The test performance data can be compared to performance data of running flows on the system linked to the template.