Netflow and Redis Integration

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

info

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.

5B+

Telegraf downloads

#1

Time series database
Source: DB Engines

1B+

Downloads of InfluxDB

2,800+

Contributors

Table of Contents

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

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.

The Redis plugin enables users to send metrics collected by Telegraf directly to Redis. This integration is ideal for applications that require robust time series data storage and analysis.

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.

Redis

The Redis Telegraf plugin is designed for writing metrics to RedisTimeSeries, a specialized Redis database module for time series data. This plugin facilitates the integration of Telegraf with RedisTimeSeries, allowing for the efficient storage and retrieval of timestamped data. With RedisTimeSeries, users can take advantage of enhanced capabilities for managing time series data, including aggregated views and range queries. The plugin offers various configuration options to enable the flexibility needed to connect securely to your Redis database, including support for Authentication, Timeouts, data type conversions, and TLS configurations. The underlying technology leverages Redis’ efficiency and scalability, making it an excellent choice for high-volume metric environments, where real-time processing is essential.

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"

Redis

[[outputs.redistimeseries]]
  ## The address of the RedisTimeSeries server.
  address = "127.0.0.1:6379"

  ## Redis ACL credentials
  # username = ""
  # password = ""
  # database = 0

  ## Timeout for operations such as ping or sending metrics
  # timeout = "10s"

  ## Enable attempt to convert string fields to numeric values
  ## If "false" or in case the string value cannot be converted the string
  ## field will be dropped.
  # convert_string_fields = true

  ## Optional TLS Config
  # tls_ca = "/etc/telegraf/ca.pem"
  # tls_cert = "/etc/telegraf/cert.pem"
  # tls_key = "/etc/telegraf/key.pem"
  # insecure_skip_verify = false

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.

Redis

  1. Monitoring IoT Sensor Data: Utilize the Redis Telegraf plugin to collect and store data from IoT sensors in real-time. By connecting the plugin to a RedisTimeSeries database, users can analyze trends in temperature, humidity, or other environmental factors. The ability to query historical sensor data efficiently will aid in predictive maintenance and help in resource management.

  2. Financial Market Data Aggregation: Employ this plugin to track and store time-sensitive financial data from various sources. By sending metrics to Redis, financial institutions can aggregate and analyze market trends or price changes over time, providing them with actionable insights derived from reliable time series analytics.

  3. Application Performance Monitoring (APM): Implement the Redis plugin for gathering application performance metrics such as response times and CPU usage. Users can visualize their application’s performance over time with RedisTimeSeries, allowing them to identify bottlenecks and optimize resource allocation swiftly.

  4. Energy Consumption Tracking: Leverage this plugin to monitor energy usage in buildings over time. By integrating with smart meters and sending data to RedisTimeSeries, municipalities or enterprises can analyze energy consumption patterns, helping to implement energy-saving measures and sustainability practices.

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

Related Integrations

HTTP and InfluxDB Integration

The HTTP plugin collects metrics from one or more HTTP(S) endpoints. It supports various authentication methods and configuration options for data formats.

View Integration

Kafka and InfluxDB Integration

This plugin reads messages from Kafka and allows the creation of metrics based on those messages. It supports various configurations including different Kafka settings and message processing options.

View Integration

Kinesis and InfluxDB Integration

The Kinesis plugin allows for reading metrics from AWS Kinesis streams. It supports multiple input data formats and offers checkpointing features with DynamoDB for reliable message processing.

View Integration