NSQ and OpenTSDB Integration

Input and output integration overview

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

The OpenTSDB plugin facilitates the integration of Telegraf with OpenTSDB, allowing users to push time-series metrics to an OpenTSDB backend seamlessly.

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.

OpenTSDB

The OpenTSDB plugin is designed to send metrics to an OpenTSDB instance using either the telnet or HTTP mode. With the introduction of OpenTSDB 2.0, the recommended method for sending metrics is via the HTTP API, which allows for batch processing of metrics by configuring the ‘http_batch_size’. The plugin supports several configuration options including metrics prefixing, server host and port specification, URI path customization for reverse proxies, and debug options for diagnosing communication issues with OpenTSDB. This plugin is particularly useful in scenarios where time series data is generated and needs to be efficiently stored in a scalable time series database like OpenTSDB, making it suitable for a wide range of monitoring and analytics applications.

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"

OpenTSDB

[[outputs.opentsdb]]
  ## prefix for metrics keys
  prefix = "my.specific.prefix."

  ## DNS name of the OpenTSDB server
  ## Using "opentsdb.example.com" or "tcp://opentsdb.example.com" will use the
  ## telnet API. "http://opentsdb.example.com" will use the Http API.
  host = "opentsdb.example.com"

  ## Port of the OpenTSDB server
  port = 4242

  ## Number of data points to send to OpenTSDB in Http requests.
  ## Not used with telnet API.
  http_batch_size = 50

  ## URI Path for Http requests to OpenTSDB.
  ## Used in cases where OpenTSDB is located behind a reverse proxy.
  http_path = "/api/put"

  ## Debug true - Prints OpenTSDB communication
  debug = false

  ## Separator separates measurement name from field
  separator = "_"

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.

OpenTSDB

1. Real-time Infrastructure Monitoring: Utilize the OpenTSDB plugin to collect and store metrics from various infrastructure components. By configuring the plugin to push metrics to OpenTSDB, organizations can have a centralized view of their infrastructure health and performance over time.

2. Custom Application Metrics Tracking: Integrate the OpenTSDB plugin into custom applications to track key performance indicators (KPIs) such as response times, error rates, and user interactions. This setup allows developers and product teams to visualize application performance trends and make data-driven decisions.

3. Automated Anomaly Detection: Leverage the plugin in conjunction with machine learning algorithms to automatically detect anomalies in time-series data sent to OpenTSDB. By continuously monitoring the incoming metrics, the system can train models that alert users to potential issues before they affect application performance.

4. Historical Data Analysis: Use the OpenTSDB plugin to store and analyze historical performance data for capacity planning and trend analysis. This provides valuable insights into system behavior over time, helping teams to understand usage patterns and prepare for future growth.

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.