Multi-Tabbed Dashboard Layouts for Flexible Data Retrieval
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Solution Overview
Problem
Analyzing and searching massive quantities of machine data from diverse sources in IT environments is challenging due to the variety of data types and formats, making it time-consuming and inefficient to derive insights.
Innovation Solution
A data intake and query system utilizing a late-binding schema that applies extraction rules during search time, enabling flexible schema development and field-searchable events to facilitate efficient retrieval and analysis of machine data across disparate data sources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If pre-processing data to extract specified data items is performed, then retrieval efficiency of extracted data is improved, but flexibility to analyze all generated data is reduced
Solution Approach 1:
The system performs preliminary indexing of data fields during data ingestion, creating a searchable index structure that enables fast retrieval. This preliminary action prepares the data for efficient querying without requiring full data processing at search time, thus maintaining both retrieval efficiency and flexibility to analyze various data types.
Solution Approach 2:
The system dynamically adjusts the schema and indexing parameters based on the actual data structure and query requirements. By changing the schema interpretation at search time rather than being fixed during ingestion, the system can efficiently retrieve data for any analysis purpose without pre-processing limitations.
2Adaptability or versatility
If raw data is stored for later analysis, then flexibility to analyze all data is improved, but search and analysis performance deteriorates
Solution Approach 1:
The system segments the data into indexed fields and raw data storage. The indexed fields provide fast search performance for common queries, while the raw data is preserved for comprehensive analysis. This segmentation allows the system to optimize for both speed and flexibility by serving different query types through different data access paths.
Solution Approach 2:
The system introduces an intermediary indexing layer between the raw data storage and the query processing. This intermediary structure translates search queries into efficient data retrieval operations, maintaining flexibility to analyze all data while significantly improving search performance through the indexed intermediary layer.
3Adaptability or versatility
If diverse data from multiple sources is collected, then comprehensive analysis capability is improved, but system complexity increases
Solution Approach 1:
The system implements a universal data ingestion and indexing framework that handles multiple data types and sources through a common schema-based approach. The same indexing mechanisms work for diverse data from different sources, reducing the need for source-specific processing logic and thereby managing complexity while maintaining comprehensive analysis capability.
Solution Approach 2:
The system uses parameterized schema definitions that can be dynamically configured for different data sources. By changing schema parameters rather than modifying core system logic, the system adapts to diverse data formats without increasing fundamental system complexity, enabling comprehensive multi-source analysis.
Data Source
AI summary
Embodiments described herein are directed to facilitating efficient management of a multi-tabbed dashboard. In one embodiment, a dashboard definition associated with a multi-tabbed dashboard is obtained. The dashboard definition may include, among other things, a layout definition portion that defines layouts for corresponding dashboard sections of the multi-tabbed dashboard. The dashboard definition may be used to determine a data retrieval operation for which to initiate execution to obtain data for use in rendering a visualization element in a dashboard section. In accordance with determining a data retrieval operation to execute, initiating execution of the data retrieval operation and, in response thereto, obtaining data based on the execution of the data retrieval operation. Thereafter, the obtained data may be provided for use in rendering the visualization element in the dashboard section of the multi-tabbed dashboard.