SNMP Manager Configuration With Automated OID-to-MIB Mapping
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Solution Overview
Problem
Analyzing and searching massive quantities of machine data from diverse sources is time-consuming and inefficient due to varying data types and formats, making it challenging to derive insights from raw machine data.
Innovation Solution
An event-based data intake and query system with a late-binding schema that processes and indexes machine data on demand, allowing flexible schema definition and extraction of values during search time, enabling efficient retrieval and analysis of machine data across disparate sources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If data is pre-processed and extracted based on anticipated analysis needs, then retrieval efficiency is improved, but data flexibility and ability to analyze all generated data is reduced
Solution Approach 1:
The patent implements a dynamic schema binding approach where the schema is not fixed at data ingestion time but is bound later during query execution. This allows the system to adapt to different analysis needs dynamically, enabling both efficient retrieval through indexing and flexible analysis of all data types without pre-processing constraints
Solution Approach 2:
The system performs preliminary indexing of raw data without full schema processing, creating a lightweight structure that enables fast retrieval while deferring the complex schema binding and data extraction operations to query time, thus maintaining both speed and flexibility
2Adaptability or versatility
If massive quantities of raw data are stored for later retrieval, then data analysis flexibility is improved, but search and analysis performance deteriorates
Solution Approach 1:
The patent segments the data processing into distinct phases: raw data storage with minimal processing, schema definition, and query-time binding. This segmentation allows raw data to be stored efficiently while enabling structured search performance through indexed schemas that are applied selectively during query execution
Solution Approach 2:
The system introduces an intermediary schema layer that sits between the raw data storage and the query processing. This schema acts as a mediator that can be bound to different data types on demand, enabling efficient structured search while maintaining the flexibility to handle diverse raw data formats
3Loss of information
If diverse data types from multiple sources are analyzed, then insight derivation opportunities are improved, but analysis complexity and time consumption increases
Solution Approach 1:
The patent changes the temporal parameter of schema binding from data ingestion time to query execution time. This parameter change allows the system to handle diverse data types efficiently by applying appropriate schemas only when needed for specific analyses, reducing overall processing time while maintaining full insight derivation capability
Data Source
AI summary
Techniques are described for automating the configuration of a simple network management protocol (SNMP) manager device for enabling collection of SNMP data from one or more SNMP-enabled devices. Based upon SNMP object identifiers (OIDs) received from an SNMP-enabled device, processing is performed to map the OIDs to one or more SNMP management information bases (MIBs) corresponding to the OIDs. The identification of the OIDs and mapping the OIDs to one or more MIBs is performed in an automated manner and substantially free of any human or manual intervention. The identified one or more MIBs are then used to configure the SNMP manager to enable SNMP communications between the SNMP-enabled device and the SNMP manager. In certain implementations, the identified one or more MIBs are loaded into system memory by the SNMP manager.