SNMP and Microsoft Fabric Integration

Input and output integration overview

The SNMP plugin allows you to collect a variety of metrics from SNMP (Simple Network Management Protocol) agents. It provides flexibility in how data is retrieved, whether collecting single metrics or entire tables.

The Microsoft Fabric plugin writes metrics to Real time analytics in Fabric services, enabling powerful data storage and analysis capabilities.

Integration details

SNMP

This plugin uses polling to gather metrics from SNMP agents, supporting retrieval of individual OIDs and complete SNMP tables. It can be configured to handle multiple SNMP versions, authentication, and other features.

Microsoft Fabric

This plugin allows you to leverage Microsoft Fabric’s capabilities to store and analyze your Telegraf metrics. Eventhouse is a high-performance, scalable data-store designed for real-time analytics. It allows you to ingest, store and query large volumes of data with low latency. The plugin supports both events and metrics with versatile grouping options. It provides various configuration parameters including connection strings specifying details like the data source, ingestion types, and which tables to use for storage. With support for streaming ingestion and event streams, this plugin enables seamless integration and data flow into Microsoft’s analytics ecosystem, allowing for rich data querying capabilities and near-real-time processing.

Configuration

SNMP

[[inputs.snmp]]
  agents = ["udp://127.0.0.1:161"]

  [[inputs.snmp.field]]
    oid = "RFC1213-MIB::sysUpTime.0"
    name = "sysUptime"
    conversion = "float(2)"

  [[inputs.snmp.field]]
    oid = "RFC1213-MIB::sysName.0"
    name = "sysName"
    is_tag = true

  [[inputs.snmp.table]]
    oid = "IF-MIB::ifTable"
    name = "interface"
    inherit_tags = ["sysName"]

    [[inputs.snmp.table.field]]
      oid = "IF-MIB::ifDescr"
      name = "ifDescr"
      is_tag = true

Microsoft Fabric

[[outputs.microsoft_fabric]]
  ## The URI property of the resource on Azure
  connection_string = "https://trd-abcd.xx.kusto.fabric.microsoft.com;Database=kusto_eh;Table Name=telegraf_dump;Key=value"

  ## Client timeout
  # timeout = "30s"

Input and output integration examples

SNMP

1. Basic SNMP Configuration: Collect metrics from a local SNMP agent using typical SNMP community string settings. This setup is ideal for local monitoring of device performance.
2. Advanced SNMPv3 Setup: Securely collect metrics using SNMPv3 with authentication and encryption to enhance security. This configuration is recommended for production environments.
3. Collect Interface Metrics: Configure the plugin to collect interface metrics from the device’s SNMP table. Utilize fields to capture specific data points for traffic analysis.
4. Join Two SNMP Tables: By using translation fields, join data from two SNMP tables for a comprehensive view of correlated performance metrics.

Microsoft Fabric

1. Real-time Monitoring Dashboards: Utilize the Microsoft Fabric plugin to feed live metrics from your applications into a real-time dashboard on Microsoft Fabric. This allows teams to visualize key performance indicators instantly, enabling quick decision-making and timely responses to performance issues.

2. Automated Data Ingestion from IoT Devices: Use this plugin in scenarios where metrics from IoT devices need to be ingested into Azure for analysis. Using the plugin’s capabilities, data can be streamed continuously, facilitating real-time analytics and reporting without complex coding efforts.

3. Cross-Platform Data Aggregation: Leverage the plugin to consolidate metrics from multiple systems and applications into a single Azure Data Explorer table. This use case enables easier data management and analysis by centralizing disparate data sources within a unified analytics framework.

4. Enhanced Event Transformation Workflows: Integrate the plugin with Eventstreams to facilitate real-time event ingestion and transformation. By configuring different metrics and partition keys, users can manipulate the flow of data as it enters the system, allowing for advanced processing before the data reaches its final destination.

Feedback

Thank you for being part of our community! If you have any general feedback or found any bugs on these pages, we welcome and encourage your input. Please submit your feedback in the InfluxDB community Slack.