In today’s increasingly climate-aware world, environmental factors such as temperature, humidity, air quality, and severe weather events directly impact IT operations, logistics, energy consumption, and field infrastructure. Despite its flexibility and power, Checkmk lacked native, contextualized support for real-time environmental data, particularly from specialized sources like astronomy, marine forecasts, or pollutant indices.
This gap sparked the creation of the Weather API Special Agent, a modular and scalable plugin designed to seamlessly integrate weather intelligence into Checkmk, enabling informed, real-time decisions across industries.
Checkmk lacked native, real-time support for environmental data, which is increasingly important for operational resilience. This was especially true for specific domains like astronomy, marine weather, or air quality indices. The Weather API Special Agent fills this gap, allowing Checkmk users to integrate contextual weather insights directly into their monitoring workflows.
The plugin is architected into three cohesive layers, ensuring clean separation of logic, robust execution and deep integration with the Checkmk ecosystem.
1. Collection & Parsing Layer – Domain-Specific Agent Sections
Each weather domain is handled by a dedicated module:
weather_current.py
: Real-time conditions (temperature, humidity, UV index) weather_forecast.py
: Multi-day forecasts with rainfall, temperature ranges, and weather outlooks weather_marine.py
: Maritime forecasts ideal for coastal or naval operations weather_air_quality.py
: Pollution levels (PM2.5, CO, NO₂, O₃…) with health indices (EPA, DEFRA) weather_alerts.py
: : Official alerts (e.g., storms, extreme heat) as live monitorable services weather_astronomy.py
: Solar/lunar cycles, moon phase, daylight indicators Each module is isolated and fault-tolerant, using fallback mechanisms to ensure resilience even in case of missing or inconsistent data.
2. Integration & Execution Layer – Dynamic and Secure
special_agent.py
: : Defines the agent’s logic, validating parameters (via Pydantic) and dynamically building execution commands based on user configuration. agent_weather_api.py
:Core executor making API requests to endpoints like /current.json, /forecast.json, and parsing them into Checkmk-compatible structures with multilingual and filtered output options. 3. Configuration Layer – Flexible Rulesets and Server-Side Context
With full support for cmk.rulesets.v1 and cmk.server_side_calls.v1, users can configure the plugin entirely via Checkmk’s WATO interface:
This configuration layer provides granular control without coding, supporting different use cases per host or environment.
Beyond real-time checks, the plugin integrates with Checkmk’s InventoryPlugin, enriching the host inventory with:
This transforms the inventory into a strategic observability layer, contextualizing infrastructure with its physical environment.
Designed with location flexibility in mind, the plugin supports:
This geographic flexibility allows tailored monitoring across distributed or multi-site operations.
To elevate data visibility, the plugin integrates with NagVis for geographic dashboards, enabling:
Dashboards auto-update with current conditions and status indicators (OK/WARN/CRIT), enabling rapid, location-based decision-making.
This plugin is already delivering tangible value across multiple sectors:
This project is more than an advanced weather monitoring solution, it’s a proof of concept that showcases the true power and flexibility of Checkmk’s architecture.
By leveraging APIs, modular design, and native Checkmk integration points (rulesets, inventory, special agents), this plugin demonstrates that virtually any external data source can be transformed into actionable monitoring.
As a DevOps Consultant Trainee at Lynxmind, he is building a strong foundation in automation, CI/CD and cloud infrastructure. With a hands-on approach and a drive to grow, he supports the team in streamlining processes and enhancing system reliability.