NSQ and Grafana 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 NSQ and 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.

See Ways to Get Started

Input and output integration overview

The NSQ Telegraf plugin reads metrics from the NSQD messaging system, allowing for real-time data processing and monitoring.

This plugin enables Telegraf to stream metrics directly to Grafana dashboards in real-time, leveraging Grafana Live for instantaneous data visualization and operational insights.

Integration details

NSQ

The NSQ plugin interfaces with NSQ, a real-time messaging platform, enabling the reading of messages from NSQD. This plugin is categorized as a service plugin, meaning it actively listens for metrics and events rather than polling them at regular intervals. With an emphasis on reliability, it prevents data loss by tracking undelivered messages until they are acknowledged by outputs. The plugin allows for configurations such as specifying NSQLookupd endpoints, topics, and channels, and it supports multiple data formats for flexibility in data handling.

Grafana

Telegraf can be used to send real-time data to Grafana using the Websocket output plugin. Metrics collected by Telegraf are instantly pushed to Grafana dashboards, enabling real-time visualization and analysis. This plugin is ideal for use cases where low latency, live data visualization is essential, such as operational monitoring, real-time analytics, and immediate incident response scenarios. It supports authentication headers, customizable data serialization formats (like JSON), and secure communication via TLS, offering flexibility and ease of integration in dynamic, interactive dashboard environments.

Configuration

NSQ

# Read metrics from NSQD topic(s)
[[inputs.nsq_consumer]]
  ## Server option still works but is deprecated, we just prepend it to the nsqd array.
  # server = "localhost:4150"

  ## An array representing the NSQD TCP HTTP Endpoints
  nsqd = ["localhost:4150"]

  ## An array representing the NSQLookupd HTTP Endpoints
  nsqlookupd = ["localhost:4161"]
  topic = "telegraf"
  channel = "consumer"
  max_in_flight = 100

  ## Max undelivered messages
  ## This plugin uses tracking metrics, which ensure messages are read to
  ## outputs before acknowledging them to the original broker to ensure data
  ## is not lost. This option sets the maximum messages to read from the
  ## broker that have not been written by an output.
  ##
  ## This value needs to be picked with awareness of the agent's
  ## metric_batch_size value as well. Setting max undelivered messages too high
  ## can result in a constant stream of data batches to the output. While
  ## setting it too low may never flush the broker's messages.
  # max_undelivered_messages = 1000

  ## Data format to consume.
  ## Each data format has its own unique set of configuration options, read
  ## more about them here:
  ## https://github.com/influxdata/telegraf/blob/master/docs/DATA_FORMATS_INPUT.md
  data_format = "influx"

Grafana

[[outputs.websocket]]
  ## Grafana Live WebSocket endpoint
  url = "ws://localhost:3000/api/live/push/custom_id"

  ## Optional headers for authentication
  # [outputs.websocket.headers]
  #   Authorization = "Bearer YOUR_GRAFANA_API_TOKEN"

  ## Data format to send metrics
  data_format = "influx"

  ## Timeouts (make sure read_timeout is larger than server ping interval or set to zero).
  # connect_timeout = "30s"
  # write_timeout = "30s"
  # read_timeout = "30s"

  ## Optionally turn on using text data frames (binary by default).
  # use_text_frames = false

  ## TLS configuration
  # tls_ca = "/path/to/ca.pem"
  # tls_cert = "/path/to/cert.pem"
  # tls_key = "/path/to/key.pem"
  # insecure_skip_verify = false

Input and output integration examples

NSQ

  1. Real-Time Analytics Dashboard: Integrate this plugin with a visualization tool to create a dashboard that displays real-time metrics from various topics in NSQ. By subscribing to specific topics, users can monitor system health and application performance dynamically, allowing for immediate insights and timely responses to any anomalies.

  2. Event-Driven Automation: Combine NSQ with a serverless architecture to trigger automated workflows based on incoming messages. This use case could involve processing data for machine learning models or responding to user actions in applications, thus streamlining operations and enhancing user experience through rapid processing.

  3. Multi-Service Communication Hub: Use the NSQ plugin to act as a centralized messaging hub among different microservices in a distributed architecture. By enabling services to communicate through NSQ, developers can ensure reliable message delivery while maintaining decoupled service interactions, significantly improving scalability and resilience.

  4. Metrics Aggregation for Enhanced Monitoring: Implement the NSQ plugin to aggregate metrics from multiple sources before sending them to an analytics tool. This setup enables businesses to consolidate data from various applications and services, creating a unified view for better decision-making and strategic planning.

Grafana

  1. Real-Time Infrastructure Dashboards: Deploy Telegraf to stream server health metrics directly to Grafana dashboards, enabling IT teams to visualize infrastructure performance in real-time. This setup allows immediate detection and response to critical system events.

  2. Interactive IoT Monitoring: Integrate IoT device metrics collected by Telegraf and push live data into Grafana, creating dynamic and interactive dashboards for monitoring smart city projects or manufacturing processes. This real-time visibility significantly enhances responsiveness and operational efficiency.

  3. Instantaneous Application Performance Analysis: Stream application metrics in real-time from production environments into Grafana dashboards, enabling development teams to rapidly detect and diagnose performance bottlenecks or anomalies during deployments, minimizing downtime and improving reliability.

  4. Live Event Analytics: Utilize Telegraf to capture and stream real-time audience or system metrics during major live events directly into Grafana dashboards. Event organizers can dynamically monitor and react to changing conditions or trends, significantly enhancing audience engagement and operational decision-making.

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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