Webhooks and M3DB 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 stream metrics to M3DB using the Prometheus Remote Write protocol, enabling scalable ingestion through the M3 Coordinator.

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.

M3DB

This configuration uses Telegraf’s HTTP output plugin with prometheusremotewrite format to send metrics directly to M3DB through the M3 Coordinator. M3DB is a distributed time series database designed for scalable, high-throughput metric storage. It supports ingestion of Prometheus remote write data via its Coordinator component, which manages translation and routing into the M3DB cluster. This approach enables organizations to collect metrics from systems that aren’t natively instrumented for Prometheus (e.g., Windows, SNMP, legacy systems) and ingest them efficiently into M3’s long-term, high-performance storage engine. The setup is ideal for high-scale observability stacks with Prometheus compatibility requirements.

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"

M3DB

# Configuration for sending metrics to M3
[outputs.http]
  ## URL is the address to send metrics to
  url = "https://M3_HOST:M3_PORT/api/v1/prom/remote/write"

  ## HTTP Basic Auth credentials
  username = "admin"
  password = "password"

  ## Data format to output.
  data_format = "prometheusremotewrite"

  ## Outgoing HTTP headers
  [outputs.http.headers]
    Content-Type = "application/x-protobuf"
    Content-Encoding = "snappy"
    X-Prometheus-Remote-Write-Version = "0.1.0"

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.

M3DB

1. Large-Scale Cloud Infrastructure Monitoring: Deploy Telegraf agents across thousands of virtual machines and containers to collect metrics and stream them into M3DB through the M3 Coordinator. This provides reliable, long-term visibility with minimal storage overhead and high availability.

2. Legacy System Metrics Ingestion: Use Telegraf to gather metrics from older systems that lack native Prometheus exporters (e.g., Windows servers, SNMP devices) and forward them to M3DB via remote write. This bridges modern observability workflows with legacy infrastructure.

3. Centralized App Telemetry Aggregation: Collect application-specific telemetry using Telegraf’s plugin ecosystem (e.g., exec, http, jolokia) and push it into M3DB for centralized storage and query via PromQL. This enables unified analytics across diverse data sources.

4. Hybrid Cloud Observability: Install Telegraf agents on-prem and in the cloud to collect and remote-write metrics into a centralized M3DB cluster. This ensures consistent visibility across environments while avoiding the complexity of running Prometheus federation layers.

Feedback

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