Related-Content Interface for Unified Machine Data Search
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing tools lack the ability to quickly and easily search and analyze large sets of raw machine data to visually identify data subsets of interest, particularly in IT environments with diverse data systems containing structured, semi-structured, and unstructured data.
Innovation Solution
A data intake and query system that utilizes a late-binding schema to process and store machine data, enabling flexible schema development and field-searchable events, allowing for real-time analysis and insights through a common information model across disparate data sources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If tools search data systems separately and collect results over a network, then data can be retrieved from diverse sources, but the analysis process becomes piecemeal and inefficient
Solution Approach 1:
The patent combines multiple separate data system searches into a single unified search operation. The system integrates connections to diverse data sources (databases, cloud services, file systems) and allows analysts to search all these sources simultaneously through one interface, consolidating what would otherwise require multiple separate search operations and result collections into a single efficient operation.
Solution Approach 2:
The system creates a universal search interface that works across multiple different data system types and formats. Rather than requiring separate tools for each data source, the platform provides a single multi-functional tool that can search databases, cloud storage, file systems, and other data sources through a common interface, making the search capability adaptable to diverse data environments.
2Adaptability or versatility
If data systems store massive quantities of raw data, then greater flexibility for analysis is enabled, but searching and analyzing the data becomes increasingly challenging
Solution Approach 1:
The system introduces an intermediary layer between the raw data storage systems and the analyst. This intermediary platform handles the complexity of searching across diverse data sources by providing standardized interfaces, automatic data discovery, and unified search capabilities. The intermediary absorbs the complexity of dealing with multiple data formats and systems, presenting a simplified interface to analysts while maintaining flexible access to all underlying data.
3Productivity
If pre-processing extracts specified data items for efficient retrieval, then analysis speed improves, but only a fraction of generated data can be analyzed
Solution Approach 1:
The system implements dynamic data retrieval capabilities that can adapt to different analysis needs. Rather than statically pre-processing and storing only specific data items, the platform can dynamically retrieve and analyze different portions of raw data based on the specific query and analysis requirements. This allows the system to maintain speed by using intelligent retrieval strategies while simultaneously providing access to the full quantity of generated data when needed.
Data Source
AI summary
Systems and methods are provided for a data intake and query system providing a user interface including corresponding content from a system external to the data intake and query system, such as an observability system. On receipt of input from a client device, the data intake and query system may generate a user interface including the corresponding content. To generate the user interface, the data intake and query system may access a unique identifier corresponding to updated data for the external system. The data intake and query system may then determine whether the updated data includes corresponding data. If so, the data intake and query system may include visualizations based on the corresponding data.