Webhooks and Apache Druid Integration

Input and output integration overview

The Webhooks plugin allows Telegraf to receive and process HTTP requests from various external services via webhooks. This plugin enables users to collect real-time metrics and events and integrate them into their monitoring solutions.

This plugin allows Telegraf to send JSON-formatted metrics to Apache Druid over HTTP, enabling real-time ingestion for analytical queries on high-volume time-series data.

Integration details

Webhooks

This Telegraf plugin is designed to act as a webhook listener by starting an HTTP server that registers multiple webhook endpoints. It provides a way to collect events from various services by capturing HTTP requests sent to defined paths. Each service can be configured with its specific authentication details and request handling options. The plugin stands out by allowing integration with any Telegraf output plugin, making it versatile for event-driven architectures. By enabling efficient reception of events, it opens possibilities for real-time monitoring and response systems, essential for modern applications that need instantaneous event handling and processing.

Apache Druid

This configuration uses Telegraf’s HTTP output plugin with json data format to send metrics directly to Apache Druid, a real-time analytics database designed for fast, ad hoc queries on high-ingest time-series data. Druid supports ingestion via HTTP POST to various components like the Tranquility service or native ingestion endpoints. The JSON format is ideal for structuring Telegraf metrics into event-style records for Druid’s columnar and time-partitioned storage engine. Druid excels at powering interactive dashboards and exploratory queries across massive datasets, making it an excellent choice for real-time observability and monitoring analytics when integrated with Telegraf.

Configuration

Webhooks

[[inputs.webhooks]]
  ## Address and port to host Webhook listener on
  service_address = ":1619"

  ## Maximum duration before timing out read of the request
  # read_timeout = "10s"
  ## Maximum duration before timing out write of the response
  # write_timeout = "10s"

  [inputs.webhooks.filestack]
    path = "/filestack"

    ## HTTP basic auth
    #username = ""
    #password = ""

  [inputs.webhooks.github]
    path = "/github"
    # secret = ""

    ## HTTP basic auth
    #username = ""
    #password = ""

  [inputs.webhooks.mandrill]
    path = "/mandrill"

    ## HTTP basic auth
    #username = ""
    #password = ""

  [inputs.webhooks.rollbar]
    path = "/rollbar"

    ## HTTP basic auth
    #username = ""
    #password = ""

  [inputs.webhooks.papertrail]
    path = "/papertrail"

    ## HTTP basic auth
    #username = ""
    #password = ""

  [inputs.webhooks.particle]
    path = "/particle"

    ## HTTP basic auth
    #username = ""
    #password = ""

  [inputs.webhooks.artifactory]
    path = "/artifactory"

Apache Druid

[[outputs.http]]
  ## Druid ingestion endpoint (e.g., Tranquility, HTTP Ingest, or Kafka REST Proxy)
  url = "http://druid-ingest.example.com/v1/post"

  ## Use POST method to send events
  method = "POST"

  ## Data format for Druid ingestion (expects JSON format)
  data_format = "json"

  ## Optional headers (may vary depending on Druid setup)
  # [outputs.http.headers]
  #   Content-Type = "application/json"
  #   Authorization = "Bearer YOUR_API_TOKEN"

  ## Optional timeout and TLS settings
  timeout = "10s"
  # 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

Webhooks

1. Real-time Notifications from Github: Integrate the Webhooks Input Plugin with Github to receive real-time notifications for events such as pull requests, commits, and issues. This allows development teams to instantly monitor crucial changes and updates in their repositories, improving collaboration and response times.

2. Automated Alerting with Rollbar: Use this plugin to listen for errors reported from Rollbar, enabling teams to react swiftly to bugs and issues in production. By forwarding these alerts into a centralized monitoring system, teams can prioritize their responses based on severity and prevent escalated downtime.

3. Performance Monitoring from Filestack: Capture events from Filestack to track file uploads, transformations, and errors. This setup helps businesses understand user interactions with file management processes, optimize workflow, and ensure high availability of file services.

4. Centralized Logging with Papertrail: Tie in all logs sent to Papertrail through webhooks, allowing you to consolidate your logging strategy. With real-time log forwarding, teams can analyze trends and anomalies efficiently, ensuring they maintain visibility over critical operations.

Apache Druid

1. Real-Time Application Monitoring Dashboard: Use Telegraf to collect metrics from application servers and send them to Druid for immediate analysis and visualization in dashboards. Druid’s low-latency querying allows users to interactively explore system behavior in near real-time.

2. Security Event Aggregation: Aggregate and forward security-related metrics such as failed logins, port scans, or process anomalies to Druid. Analysts can build dashboards to monitor threat patterns and investigate incidents with millisecond-level granularity.

3. IoT Device Analytics: Collect telemetry from edge devices via Telegraf and send it to Druid for fast, scalable processing. Druid’s time-partitioned storage and roll-up capabilities are ideal for handling billions of small JSON events from sensors or gateways.

4. Web Traffic Behavior Exploration: Use Telegraf to capture web server metrics (e.g., requests per second, latency, error rates) and forward them to Druid. This enables teams to drill down into user behavior by region, device, or request type with subsecond query performance.

Feedback

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