Fireboard and Zabbix 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 Fireboard 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.

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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 sends metrics to Zabbix via traps, allowing for efficient monitoring of systems and applications. It supports automated configuration and data sending based on dynamic metrics collected by Telegraf.

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.

Zabbix

The Telegraf Zabbix plugin is designed to send metrics to Zabbix, an open-source monitoring solution, using the trap protocol. It supports various versions from 3.0 to 6.0, ensuring compatibility with recent updates. The plugin facilitates easy integration with the Zabbix ecosystem, allowing users to send collected metrics and monitor system performance seamlessly. Key functionalities include the ability to define the address and port of the Zabbix server, options for prefixing keys, determining the type of data sent (active vs. trapper), and features for low-level discovery (LLD) enabling dynamic item creation based on the metrics observed. Configuration options also allow for autoregistration and resending intervals for LLD data, ensuring that the metrics are up-to-date and relevant. Additionally, the trap format used for sending metrics is structured to facilitate efficient data transfer and processing in Zabbix.

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"

Zabbix

[[outputs.zabbix]]
  ## Address and (optional) port of the Zabbix server
  address = "zabbix.example.com:10051"

  ## Send metrics as type "Zabbix agent (active)"
  # agent_active = false

  ## Add prefix to all keys sent to Zabbix.
  # key_prefix = "telegraf."

  ## Name of the tag that contains the host name. Used to set the host in Zabbix.
  ## If the tag is not found, use the hostname of the system running Telegraf.
  # host_tag = "host"

  ## Skip measurement prefix to all keys sent to Zabbix.
  # skip_measurement_prefix = false

  ## This field will be sent as HostMetadata to Zabbix Server to autoregister the host.
  ## To enable this feature, this option must be set to a value other than "".
  # autoregister = ""

  ## Interval to resend auto-registration data to Zabbix.
  ## Only applies if autoregister feature is enabled.
  ## This value is a lower limit, the actual resend should be triggered by the next flush interval.
  # autoregister_resend_interval = "30m"

  ## Interval to send LLD data to Zabbix.
  ## This value is a lower limit, the actual resend should be triggered by the next flush interval.
  # lld_send_interval = "10m"

  ## Interval to delete stored LLD known data and start capturing it again.
  ## This value is a lower limit, the actual resend should be triggered by the next flush interval.
  # lld_clear_interval = "1h"

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.

Zabbix

  1. Dynamic Monitoring of Containerized Applications: Integration of the Zabbix plugin can be leveraged to monitor Docker containers dynamically. As containers are created and removed, the plugin can automatically update Zabbix with the appropriate metrics, ensuring that monitoring stays current without manual configuration. This enhances visibility into resource usage and performance metrics for microservices orchestrated with Kubernetes or Docker Swarm.

  2. Real-Time Performance Monitoring with Auto-registration: By enabling the autoregister feature, the plugin can automatically register hosts in Zabbix based on the metrics received. This scenario provides a streamlined approach to add new hosts to monitoring without manual setup, which is particularly useful in environments where hosts may frequently spin up and down, such as serverless architectures or cloud-based deployments.

  3. Leveraging Low-level Discovery for Flexible Metric Capture: Using low-level discovery, this plugin allows Zabbix to adaptively create items for metrics that are not predefined. In a scenario involving multiple network devices reporting different performance metrics, the plugin can dynamically inform Zabbix about new metrics as they appear, thus ensuring comprehensive monitoring capabilities that evolve with the monitored systems.

  4. Centralized Monitoring of Distributed Systems: The Zabbix plugin can be utilized in a centralized monitoring setup for distributed systems where multiple Telegraf instances are running across different geographical locations. By sending all metrics to a central Zabbix server, organizations can achieve a holistic view of their infrastructure’s performance and make informed operational decisions.

Feedback

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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

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