Fireboard and CrateDB 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.

The CrateDB plugin facilitates the writing of metrics to a CrateDB database, leveraging its PostgreSQL-compatible protocol to ensure a seamless experience for users.

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.

CrateDB

This plugin writes to CrateDB via its PostgreSQL protocol, allowing for metrics to be efficiently stored in a scalable database. CrateDB is designed for high-speed analytics, supporting time-series data and complicated queries, making it ideal for applications that require fast ingestion and analysis of large datasets. By utilizing the PostgreSQL protocol, the CrateDB output plugin ensures compatibility with existing PostgreSQL client libraries and tools, enabling a smooth integration for users who are already familiar with PostgreSQL’s ecosystem. The plugin provides options such as automatic table creation, connection parameters, and query timeouts, offering flexibility in how metrics are handled and stored within the database.

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"

CrateDB

[[outputs.cratedb]]
  ## Connection parameters for accessing the database see
  ##   https://pkg.go.dev/github.com/jackc/pgx/v4#ParseConfig
  ## for available options
  url = "postgres://user:password@localhost/schema?sslmode=disable"

  ## Timeout for all CrateDB queries.
  # timeout = "5s"

  ## Name of the table to store metrics in.
  # table = "metrics"

  ## If true, and the metrics table does not exist, create it automatically.
  # table_create = false

  ## The character(s) to replace any '.' in an object key with
  # key_separator = "_"

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.

CrateDB

1. Real-Time Analytics for IoT Devices: Collect and store metrics from thousands of IoT devices. By setting up a dynamic metrics table for each device, users can perform real-time analytics on the collected data, enabling quick insights into device performance, patterns, and potential failures. This setup benefits from CrateDB’s ability to handle high-throughput data ingestion while providing the necessary analytics capabilities to derive actionable insights.

2. Website Performance Monitoring: Track key performance metrics from web applications, such as request latency and user activity. By storing metrics in CrateDB, teams can leverage the power of SQL-like queries to analyze traffic patterns, user engagement, and server performance over time, leading to optimized application performance and enhanced user experiences.

3. Financial Transaction Analysis: Manage large volumes of financial transaction data for real-time fraud detection and analysis. With CrateDB’s scalable infrastructure, users can store, query, and analyze transaction metrics efficiently, allowing for the detection of anomalies and illicit activities based on transaction patterns and trends.

Feedback

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