Netflow and Splunk Integration

Powerful performance with an easy integration, powered by Telegraf, the open source data connector built by InfluxData.

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This is not the recommended configuration for real-time query at scale. For query and compression optimization, high-speed ingest, and high availability, you may want to consider using the Netflow plugin with InfluxDB.

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Powerful Performance, Limitless Scale

Collect, organize, and act on massive volumes of high-velocity data. Any data is more valuable when you think of it as time series data. with InfluxDB, the #1 time series platform built to scale with Telegraf.

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Input and output integration overview

The Netflow plugin is designed to collect traffic flow data from devices using the Netflow v5, v9 and IPFIX protocols. By capturing detailed flow information, this plugin supports network observability and analysis, enabling administrators to monitor traffic patterns and performance metrics effectively.

This output plugin facilitates direct streaming of Telegraf collected metrics into Splunk via the HTTP Event Collector, enabling easy integration with Splunk’s powerful analytics platform.

Integration details

Netflow

The Netflow plugin serves as a collector for flow data using protocols such as Netflow v5, Netflow v9, and IPFIX. This plugin allows users to gather important flow metrics from devices that support these protocols, including a variety of operational insights about traffic patterns, source/destination information, and protocol usage. The plugin leverages templates sent by flow devices to decode incoming data correctly, and it supports private enterprise number mappings for vendor-specific information. With features like adjustable service addresses and buffer sizes, the plugin provides flexibility in how it can be deployed within various network architectures, making it an essential tool for network monitoring and analysis.

Splunk

Use Telegraf to easily collect and aggregate metrics from many different sources and send them to Splunk. Utilizing the HTTP output plugin combined with the specialized Splunk metrics serializer, this configuration ensures efficient data ingestion into Splunk’s metrics indexes. The HEC is an advanced mechanism provided by Splunk designed to reliably collect data at scale via HTTP or HTTPS, providing critical capabilities for security, monitoring, and analytics workloads. Telegraf’s integration with Splunk HEC streamlines operations by leveraging standard HTTP protocols, built-in authentication, and structured data serialization, optimizing metrics ingestion and enabling immediate actionable insights.

Configuration

Netflow

[[inputs.netflow]]
  ## Address to listen for netflow,ipfix or sflow packets.
  ##   example: service_address = "udp://:2055"
  ##            service_address = "udp4://:2055"
  ##            service_address = "udp6://:2055"
  service_address = "udp://:2055"

  ## Set the size of the operating system's receive buffer.
  ##   example: read_buffer_size = "64KiB"
  ## Uses the system's default if not set.
  # read_buffer_size = ""

  ## Protocol version to use for decoding.
  ## Available options are
  ##   "ipfix"      -- IPFIX / Netflow v10 protocol (also works for Netflow v9)
  ##   "netflow v5" -- Netflow v5 protocol
  ##   "netflow v9" -- Netflow v9 protocol (also works for IPFIX)
  ##   "sflow v5"   -- sFlow v5 protocol
  # protocol = "ipfix"

  ## Private Enterprise Numbers (PEN) mappings for decoding
  ## This option allows to specify vendor-specific mapping files to use during
  ## decoding.
  # private_enterprise_number_files = []

  ## Log incoming packets for tracing issues
  # log_level = "trace"

Splunk

[[outputs.http]]
  ## Splunk HTTP Event Collector endpoint
  url = "https://splunk.example.com:8088/services/collector"

  ## HTTP method to use
  method = "POST"

  ## Splunk authentication token
  headers = {"Authorization" = "Splunk YOUR_SPLUNK_HEC_TOKEN"}

  ## Serializer for formatting metrics specifically for Splunk
  data_format = "splunkmetric"

  ## Optional parameters
  # timeout = "5s"
  # insecure_skip_verify = false
  # tls_ca = "/path/to/ca.pem"
  # tls_cert = "/path/to/cert.pem"
  # tls_key = "/path/to/key.pem"

Input and output integration examples

Netflow

  1. Traffic Analysis and Visualization: Use the Netflow plugin to collect traffic flow data and visualize it in real-time using an analytics platform. Administrators can create dashboards that display traffic patterns and anomalies, helping them understand bandwidth usage and user behavior.

  2. Network Performance Optimization: Integrate the Netflow plugin with performance monitoring tools to identify bottlenecks and optimize the network. Analyze collected metrics to pinpoint areas where network resources can be improved, enhancing overall system performance.

  3. Anomaly Detection for Security: Leverage the Netflow data for security analysis by feeding it into an anomaly detection system. This can help identify unusual traffic patterns that may indicate potential security threats, enabling quicker responses to prevent breaches.

  4. Customized Alerts for Network Events: Configure threshold-based alerts using the Netflow plugin metrics to notify network administrators of unusual spikes or drops in traffic. This proactive monitoring can help in quickly addressing potential issues before they escalate.

Splunk

  1. Real-Time Security Analytics: Utilize this plugin to stream security-related metrics from various applications into Splunk in real-time. Organizations can detect threats instantly by correlating data streams across systems, significantly reducing detection and response times.

  2. Multi-Cloud Infrastructure Monitoring: Integrate Telegraf to consolidate metrics from multi-cloud environments directly into Splunk, enabling comprehensive visibility and operational intelligence. This unified monitoring allows teams to detect performance issues quickly and streamline cloud resource management.

  3. Dynamic Capacity Planning: Deploy the plugin to continuously push resource metrics from container orchestration platforms (like Kubernetes) into Splunk. Leveraging Splunk’s analytics capabilities, teams can automate predictive scaling and resource allocation, avoiding resource bottlenecks and minimizing costs.

  4. Automated Incident Response Workflows: Combine this plugin with Splunk’s alerting system to create automated incident response workflows. Metrics collected by Telegraf trigger real-time alerts and automated remediation scripts, ensuring rapid resolution and maintaining high system availability.

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.

Powerful Performance, Limitless Scale

Collect, organize, and act on massive volumes of high-velocity data. Any data is more valuable when you think of it as time series data. with InfluxDB, the #1 time series platform built to scale with Telegraf.

See Ways to Get Started

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