Arista LANZ and Microsoft Fabric Integration

Input and output integration overview

The Arista LANZ plugin is designed for reading latency and congestion metrics from Arista LANZ, helping users monitor their network performance effectively.

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

Integration details

Arista LANZ

This plugin provides a consumer for use with Arista Networks’ Latency Analyzer (LANZ). Metrics are read from a stream of data via TCP through port 50001 on the switches management IP. The data is in Protobuffers format, allowing for efficient transportation and parsing of data. LANZ is utilized to monitor network latency and congestion in real-time, which is vital for maintaining optimal performance in networking environments. The underlying technology, Arista’s latency analysis, provides insights into various network operations and infrastructure behaviors, making it a crucial tool for network engineering and management.

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

Arista LANZ

[[inputs.lanz]]
  ## URL to Arista LANZ endpoint
  servers = [
    "tcp://switch1.int.example.com:50001",
    "tcp://switch2.int.example.com:50001",
  ]

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

Arista LANZ

1. Real-Time Latency Monitoring: This plugin can be used to set up a monitoring dashboard that tracks real-time latency metrics across multiple interfaces. By gathering and visualizing this data, network admins can swiftly identify and rectify latency issues before they impact service quality. The challenge lies in efficiently handling the influx of metrics from various sources without overwhelming the infrastructure or incurring excessive processing delays.

2. Congestion Analysis for Traffic Engineering: Users can leverage the LANZ plugin to analyze congestion records, enabling the optimization of network traffic flows. By applying historical pattern recognition to the metrics collected, IT teams can make informed decisions on traffic management strategies, thus improving overall network efficiency. This requires implementing robust data storage and analysis capabilities to derive actionable insights from the raw metrics.

3. Integration with Alerting Systems: Integrate the metrics from this plugin with alerting systems to automatically notify network engineers of any significant changes in latency or congestion. By setting thresholds based on historical data trends, this use case enhances proactive incident management, allowing teams to address potential issues proactively. The technical challenge here is establishing the right balance in threshold settings to minimize false positives while ensuring genuine issues are flagged promptly.

4. Network Optimization Reports: Utilize the metrics gathered through the LANZ plugin to generate periodic reports that detail network performance, latency trends, and congestion events. These reports can help stakeholders understand network health over time and guide infrastructure investments. The challenge involves structuring and formatting the output data to make it comprehensible and actionable for various audiences.

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

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