Dynamic Observability Adjustment for Distributed Applications

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Solution Overview

Problem

As data production increases with advancements in computing power and the growth of IoT devices, the overhead associated with processing larger amounts of observability data becomes significant, leading to increased storage costs, network costs, and computational resource expenses.

Innovation Solution

A computer-implemented method that dynamically adjusts the amount of observability data produced and evaluated by distributed applications based on real-time performance characteristics. When a portion of the distributed application is degraded, the method increases the observability data production for that portion and correlated portions, while reducing data production in low-risk situations.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If continuous monitoring of observability data is maintained for all portions of distributed applications, then real-time performance detection and issue resolution capability is improved, but processing overhead, storage costs, and computational resource expenses increase significantly

Engineering Contradiction:

Improvereal-time performance detection capabilityVSAvoidprocessing overhead and computational resource expenses

Core Design Contradiction:

ReliabilityVSLoss of energy

Solution Approach 1:

The system dynamically adjusts the amount of observability data collected from different portions of distributed applications based on real-time performance characteristics. When degradation is detected, data collection is increased for affected portions; when portions are healthy, data collection is reduced. This dynamic adaptation resolves the contradiction by making monitoring intensity flexible rather than static.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The patent applies different monitoring intensities to different portions of the distributed application based on their specific performance state. Healthy portions receive minimal monitoring while degraded portions receive intensive monitoring. This localized quality approach ensures reliable detection where needed while minimizing processing overhead in stable regions.

Inventive Principle:

Principle #3Local quality

2Measurement precision

If the amount of observability data production is increased to improve monitoring coverage and detection accuracy, then measurement precision and reliability are improved, but the overhead of processing larger amounts of data increases

Engineering Contradiction:

Improveperformance monitoring accuracyVSAvoiddata processing efficiency

Core Design Contradiction:

Measurement precisionVSProductivity

Solution Approach 1:

The system applies partial action by collecting full-detail observability data only when and where degradation is detected, rather than continuously collecting excessive data from all portions. This resolves the contradiction by matching data collection intensity to actual monitoring needs, achieving sufficient measurement precision without the burden of processing unnecessarily large data volumes.

Inventive Principle:

Principle #16Partial or excessive action

Solution Approach 2:

The patent changes the parameter of data collection volume based on performance conditions. When performance is healthy, data collection parameters are reduced; when degradation occurs, parameters are increased to capture detailed observability information. This dynamic parameter adjustment maintains measurement precision while optimizing processing efficiency.

Inventive Principle:

Principle #35Parameter changes

3Loss of information

If observability data is collected from all portions of distributed applications at high frequency, then comprehensive understanding of system health is improved, but storage costs and network costs increase

Engineering Contradiction:

Improvecompleteness of system health informationVSAvoidstorage and network resources consumed

Core Design Contradiction:

Loss of informationVSQuantity of substance

Solution Approach 1:

The patent segments the distributed application into multiple portions and applies different data collection strategies to each segment based on their performance state. This segmentation allows the system to maintain comprehensive health understanding by monitoring degraded portions intensively while reducing data collection from healthy portions, thereby reducing overall storage and network resource consumption.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system implements periodic evaluation of performance characteristics and adjusts data collection frequency accordingly. Rather than continuous high-frequency collection from all portions, the system periodically assesses health status and modulates monitoring intensity, achieving comprehensive health understanding while minimizing resource consumption during stable periods.

Inventive Principle:

Principle #19Periodic action

Data Source

PatentUS12287696B1Dynamically adjusting observability based on real-time performance

Publication Date: 2025.04.29 INTERNATIONAL BUSINESS MACHINE CORPORATION

AI summary

A computer-implemented method, according to one approach, includes: receiving observability data produced by a first portion of a distributed application. The observability data is evaluated and in response to determining that the observability data indicates the first portion of the distributed application is degraded, the amount of the observability data produced by the first portion of the distributed application is increased. Additionally, the amount of observability data produced by other portions of the distributed application that are correlated with the first portion of the distributed application is also increased.