Event-Structured Observability System for Federated Data Platforms

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Solution Overview

Problem

Current data observability systems relying on discrete metrics, logs, and traces are inefficient and incomplete, struggling to effectively collect and store contextual data for extended periods, leading to difficulties in identifying and addressing issues in complex federated network and database platforms.

Innovation Solution

The implementation of an event-structured observability system that uses linked observable data elements to provide granular insights, enabling efficient storage and processing of data across various levels, integrating with existing systems through observability protocols like OpenTelemetry, and facilitating event-based actions such as error detection and alerting.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of manufacture

If discrete metrics, logs, and traces are used for data observability, then data collection is simple, but data completeness and contextual understanding deteriorate

Engineering Contradiction:
Improvedata collection simplicityVSAvoiddata completeness
Core Design Contradiction:
Ease of manufactureVSLoss of information

Solution Approach 1:

The patent combines discrete metrics, logs, and traces into a unified event-structured data model where all observability data is represented as events with standardized schemas. This merging preserves data completeness while maintaining collection simplicity through a unified interface.

Inventive Principle:
Principle #5Merging (Combining)

Solution Approach 2:

The event-structured data model serves multiple functions simultaneously: it captures metrics, logs, and traces in a unified format, enables contextual enrichment, supports flexible querying, and maintains backward compatibility with existing collection mechanisms.

Inventive Principle:
Principle #6Universality (Multi-functionality)

2Duration of action of stationary object

If traditional observability systems store data for extended periods, then historical analysis capability improves, but storage efficiency and operational performance deteriorate

Engineering Contradiction:
Improvedata retention periodVSAvoidoperational efficiency
Core Design Contradiction:
Duration of action of stationary objectVSProductivity

Solution Approach 1:

The patent segments observability data into event-structured records with standardized schemas that can be independently stored, queried, and managed. This segmentation enables efficient storage strategies where historical data is retained without compromising system performance, as events can be queried selectively rather than scanning entire data sets.

Inventive Principle:
Principle #1Segmentation

3Measurement precision

If granular observability data is collected and stored, then data-driven insights improve, but system complexity and instrumentation overhead increase

Engineering Contradiction:
Improveobservability granularityVSAvoidinstrumentation complexity
Core Design Contradiction:
Measurement precisionVSDevice complexity

Solution Approach 1:

The patent changes the parameter representation by transforming diverse observability data types into a unified event structure with standardized parameters. This allows granular data collection without increasing instrumentation complexity, as the same event-based interface handles all data types consistently.

Inventive Principle:
Principle #35Parameter changes

4Reliability

If contextual data is collected for sufficient time bands, then issue identification capability improves, but data storage requirements and processing overhead increase

Engineering Contradiction:
Improveissue identification capabilityVSAvoiddata storage volume
Core Design Contradiction:
ReliabilityVSQuantity of substance

Solution Approach 1:

The patent creates a simplified copy or representation of complex observability data through event-structured records. Instead of storing raw, voluminous data, the system stores standardized event representations that preserve essential contextual information while reducing storage requirements and enabling efficient processing.

Inventive Principle:
Principle #26Copying

Data Source

PatentUS11700192B2Apparatuses, methods, and computer program products for improved structured event-based data observability
Publication Date: 2023.07.11 ATLASSIAN PTY LTD
  • US11700192B2 patent drawing
  • US11700192B2 patent drawing
  • US11700192B2 patent drawing

AI summary

Embodiments of the present disclosure provide improved data observability mechanisms. Specifically, embodiments provide for managing event-structured observability data in a federated network and database platform. The improved mechanisms enable improved analysis of data-driven errors and/or storage of associated data for purposes of data observability processing actions and/or rendering for user analysis. Example embodiments are configured for receiving a data stream representing operational engagement of an event-structured service hosted by the federated network and database platform. Some example embodiments are further configured for generating event-structured observability data from the data stream utilizing an event processing pipeline. The example embodiments are further configured for storing the event-structured observability data in at least one event-structured observability data repository of the federated network and database platform. The example embodiments are further configured for initiating an event-driven observability action based on the event-structured observability data.