Extensibility Platform for Centralized Observability Data Ingestion
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Solution Overview
Problem
Monitoring and logging of distributed web services are challenging due to complex data dependencies and operational nuances, leading to difficulties in associating logged data across services and risking software application breakdowns when monitoring is not centralized.
Innovation Solution
An extensibility platform that provides a centralized monitoring system, allowing solution packaging and managing multi-tenancy of observability data ingestion pipelines, with a Flexible Meta Model (FMM) for data modeling and tenant-specific solution subscriptions, enabling customized extension points and data-type dependencies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If monitoring is done in a discrete and non-centralized fashion for each web service, then monitoring can be implemented independently for each service, but it becomes difficult to associate logged data across different web services and risks breaking the software application
Solution Approach 1:
The patent merges discrete monitoring functions into a centralized monitoring system that collects and processes logs from multiple web services through a common pipeline. The centralized system associates logged data across services by maintaining context about service dependencies and data flows, preventing data association loss while preserving independent monitoring capabilities through standardized interfaces.
Solution Approach 2:
The patent introduces a centralized monitoring system as an intermediary between web services and log analysis. This mediator collects logs from various services, maintains their associations through context information, and provides unified monitoring without requiring direct integration between services, thus preserving operational independence while enabling data association.
2Productivity
If monitoring code is added for one web service without accounting for dependencies, then monitoring can be implemented quickly, but it risks breaking the software application already running in the cloud
Solution Approach 1:
The patent performs preliminary analysis of service dependencies and data flows before implementing monitoring. The centralized system pre-configures monitoring parameters and associations based on understood service relationships, allowing rapid deployment of monitoring code while ensuring it accounts for dependencies and maintains application stability.
Solution Approach 2:
The patent creates a universal monitoring interface that works across multiple web services with different dependencies. This multi-functional approach allows the same monitoring code to be applied universally while the centralized system adapts to specific service dependencies, enabling fast implementation without compromising reliability through one-size-fits-all monitoring.
3Loss of information
If a centralized monitoring system is implemented, then logged data can be associated across web services and application stability is maintained, but system complexity increases
Solution Approach 1:
The patent segments the centralized monitoring system into modular components: log collection modules, processing modules, and association modules. Each component handles specific tasks independently, reducing overall system complexity while maintaining data association capabilities. The segmented architecture allows independent development and deployment of monitoring functions.
4Adaptability or versatility
If customized monitoring solutions are created for each tenant, then specific tenant needs are met, but system maintenance and updates become difficult
Solution Approach 1:
The patent implements local quality by allowing each tenant to have customized monitoring parameters and configurations specific to their needs, while the core monitoring infrastructure remains standardized. This enables tenant-specific adaptations without creating entirely separate systems, making maintenance and updates easier through centralized management of common components.
Data Source
AI summary
According to one or more embodiments of the disclosure, an example method herein may comprise: providing a core technology stack for an extensibility platform; managing a plurality of solution packages within the extensibility platform that are separated from the core technology stack, each of the plurality of solution packages defining a data model, access to that data model, and dependencies for that data model, wherein the plurality of solution packages have one or more globally shared core solution packages; operating according to one or more tenant-based solution packages within the plurality of solution packages within the extensibility platform, the one or more tenant-based solution packages defining corresponding tenant-specified models and configurations for soft-coded customized extension points for the extensibility platform; and managing multi-tenancy of an observability data ingestion pipeline of the extensibility platform according to the plurality of solution packages including the soft-coded customized extension points for the extensibility platform.