Automated Severity Assignment for API Services Using Tenant Telemetry

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Solution Overview

Problem

Manual assessment of API failures in online services often fails to consider the importance of the failing API, leading to inefficient resource allocation and delayed remediation.

Innovation Solution

Automatically assigning a severity level to computing services like APIs based on tenant telemetry data, which tracks usage patterns to differentiate between critical and non-critical services, enabling tailored responses to failures.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If manual review is used to assess API failures, then human judgment can evaluate the importance of failing APIs, but the process delays remediation and fails to consistently identify critical services

Engineering Contradiction:

Improveaccuracy of failure importance assessmentVSAvoidtime to remediate failure

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The system automatically assigns severity levels to computing services using telemetry data without requiring manual human assessment. The service itself (through automated systems) evaluates its own importance based on usage patterns, eliminating the delay and inconsistency of manual review while maintaining accurate identification of critical services.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system pre-calculates and stores severity levels for computing services based on historical telemetry data before failures occur. When a failure happens, the pre-assigned severity level is immediately available for rapid response, eliminating the time loss associated with post-failure manual assessment while ensuring consistent identification of critical services.

Inventive Principle:

Principle #10Preliminary action

2Productivity

If manual assessment of API importance is performed, then resource allocation can be adjusted based on criticality, but the process wastes time and monetary resources on low-importance failures

Engineering Contradiction:

Improveefficiency of resource allocationVSAvoidwaste of time and monetary resources

Core Design Contradiction:

ProductivityVSLoss of energy

Solution Approach 1:

The automated severity assignment system enables the organization to efficiently allocate resources by automatically identifying which services are critical versus non-critical. This eliminates wasteful expenditure of time and money on low-importance failures while ensuring adequate resources are directed to high-severity services, dramatically improving resource allocation efficiency.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system changes the parameter of service criticality assessment from subjective manual judgment to objective automated measurement based on telemetry data. This parameter change enables precise differentiation between critical and non-critical services, allowing optimal resource allocation and eliminating waste on low-importance failures while maintaining focus on essential services.

Inventive Principle:

Principle #35Parameter changes

3Quantity of substance

If telemetry data from all users including synthetic users is used, then comprehensive usage patterns are captured, but the severity assignment is skewed by automated processing routines that do not represent real user impact

Engineering Contradiction:

Improvevolume of usage data collectedVSAvoidaccuracy of business impact assessment

Core Design Contradiction:

Quantity of substanceVSMeasurement precision

Solution Approach 1:

The system extracts and separates synthetic user telemetry data from real user telemetry data. By taking out the synthetic user component, the system prevents automated processing routines from skewing severity assignments, ensuring that business impact assessment accurately reflects real user experience while maintaining comprehensive data collection from actual users.

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

Instead of including all users and then filtering, the system inverts the approach by specifically isolating and excluding synthetic user data before analysis. This inversion ensures that only genuine user impact metrics influence severity assignment, improving measurement precision while maintaining the benefits of comprehensive telemetry collection from real users.

Inventive Principle:

Principle #13The other way round (Inversion)

Data Source

PatentUS11030024B2Assigning a severity level to a computing service using tenant telemetry data

Publication Date: 2021.06.08 MICROSOFT TECHNOLOGY LICENSING LLC

AI summary

Systems and methods for determining a severity level of a computing service. One system includes an electronic processor that is configured to receive telemetry data associated with one or more tenants of an online service providing services through a plurality of computing services and calculate, based on the telemetry data, a number of accesses of each of the plurality of computing services during a predetermined time period. The electronic processor is also configured to, for each of the plurality of computing services, assign a severity level to each computing service based on the number of accesses of each computing service during the predetermined time period. The electronic processor is further configured to, in response to detecting a failure of one of the plurality of computing services, initiate a response to the failure based on the severity level assigned to the one of the plurality of computing services.