Data Intake System for Heterogeneous Machine Data Integration
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Solution Overview
Problem
Analyzing and searching massive quantities of machine data from diverse sources in data centers and networks is challenging due to the heterogeneity of data formats and systems, leading to difficulties in integration and efficient data retrieval.
Innovation Solution
A data intake and query system that uses a flexible schema to process and store machine data as events with timestamps, allowing for field-searchable and late-binding schema approaches to extract insights without prior storage, enabling efficient querying and analysis across disparate data sources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is stored in raw format for later analysis, then data availability is improved, but storage requirements and system complexity increase significantly
Solution Approach 1:
The system performs preliminary transformation of data from multiple sources into a unified event format before storage. This pre-processing step converts heterogeneous data (logs, metrics, traces) into a standardized schema with consistent fields, enabling efficient storage and query without requiring complex storage infrastructure later
Solution Approach 2:
The patent introduces an intermediary event format that acts as a mediator between diverse data sources and the analysis system. This standardized event structure serves as a common language, allowing data from different sources to be unified and stored efficiently without requiring source-specific storage mechanisms
2Productivity
If data is transformed and stored in a standardized format, then query efficiency is improved, but data processing time and computational resources increase
Solution Approach 1:
Data transformation is performed in advance during the data collection phase, where raw data from sources is immediately converted into standardized event format. This preliminary action ensures that when queries are executed later, the data is already in the optimal format for efficient retrieval and analysis, eliminating the need for time-consuming transformation during query execution
Solution Approach 2:
The system segments the data processing into distinct phases: data collection, transformation to event format, and query execution. By separating these operations, the system can optimize each phase independently, performing transformation during collection when data is incoming, and executing optimized queries against the pre-transformed data
3Adaptability or versatility
If heterogeneous data from multiple sources is integrated, then analytical capabilities are improved, but system complexity and integration difficulty increase
Solution Approach 1:
The patent implements a universal event format that can accommodate data from any source type. The standardized schema with common fields (source, timestamp, host, etc.) and flexible value types creates a multi-functional data structure that handles logs, metrics, traces, and other data types through a single unified approach, eliminating the need for source-specific processing logic
Solution Approach 2:
The standardized event format serves as an intermediary layer between heterogeneous data sources and the analysis system. This mediator absorbs the complexity of different data formats and presents a consistent interface, allowing the system to integrate diverse sources without exposing the underlying complexity to the query and analysis layers
Data Source
AI summary
A computer implemented method includes establishing, by a data intake and query system, a network connection between the data intake and query system and an application and infrastructure monitoring platform. The data intake and query system receives a data stream from the application and infrastructure monitoring platform. The computer implemented method further includes transforming the data stream while receiving the data stream to obtain a transformed data stream. Further, the transformed data stream is analyzed while receiving the data stream to generate analysis results, which are presented.