Fireboard and Apache Druid Integration

Input and output integration overview

The Fireboard plugin enables users to gather real-time temperature readings from Fireboard thermometers using the Fireboard REST API.

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

Fireboard

This plugin gathers real-time temperature data from Fireboard thermometers. Fireboard is a smart thermometer system that utilizes a REST API to provide user access to temperature monitoring. This plugin allows users to retrieve temperature readings efficiently, utilizing the provided authentication token. It can be configured with an optional server URL and custom HTTP timeout settings, providing flexibility depending on the user’s network conditions or potential changes to the Fireboard API. The metrics captured are essential for monitoring environments that require precise temperature control, thereby aiding in applications such as cooking, brewing, or any scenario where temperature variations are critical.

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

Fireboard

[[inputs.fireboard]]
  ## Specify auth token for your account
  auth_token = "invalidAuthToken"
  ## You can override the fireboard server URL if necessary
  # url = https://fireboard.io/api/v1/devices.json
  ## You can set a different http_timeout if you need to
  ## You should set a string using an number and time indicator
  ## for example "12s" for 12 seconds.
  # http_timeout = "4s"

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

Fireboard

1. Smart Cooking Assistant: Integrate the Fireboard plugin into a smart kitchen ecosystem to monitor and adjust cooking temperatures in real-time. This setup can leverage the temperature data to automate processes like turning on or off heating elements based on the current cooking stage, ensuring optimal results.

2. Remote Brewing Monitoring: Use this plugin as part of a remote brewing setup for beer production. Brewers can monitor temperatures from multiple fireboards placed in different tanks and receive alerts when temperatures deviate from desired ranges, allowing for timely interventions.

3. Environmental Monitoring System: Incorporate this plugin into a broader environmental monitoring system that tracks temperature changes in various settings, from server rooms to greenhouses. This data can help maintain optimal conditions and can even be tied to automated cooling or heating systems for efficient climate control.

4. Automated Alerting for Temperature Sensitive Products: Employ the Fireboard plugin to monitor temperatures of products requiring specific storage conditions, such as pharmaceuticals or perishables. When temperature thresholds are breached, automated alerts could be sent to management systems to initiate corrective actions, thereby preventing spoilage.

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.

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