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zabbix-graphql-api/roadmap.md
Andreas Hilbig ec6ed422b1 feat: improve Zabbix version compatibility and optimize queries 
This commit introduces several improvements to ensure the API works seamlessly across Zabbix 6.0, 6.4, and 7.0+, while also optimizing data fetching performance.

Key changes:
- Zabbix Version Compatibility:
  - Added Zabbix version detection and static caching in ZabbixAPI.
  - Implemented name-based fallback for host/template group permissions to support Zabbix 6.0 (which lacks UUIDs for host groups).
  - Added manual host group expansion for Zabbix versions < 6.2.0 during user group import.
  - Added version-based guards for history.push (7.0+) and hostgroup.propagate (6.2+).
  - Updated documentation with detailed version compatibility notes.
  - Added src/test/zabbix_6_0_compatibility.test.ts to verify compatibility logic.

- Query Optimization:
  - Implemented dynamic output selection in ZabbixRequest to fetch only fields requested in GraphQL queries.
  - Added GraphqlParamsToNeededZabbixOutput to map GraphQL selections to Zabbix API output parameters.
  - Moved "Query Optimization" to achieved milestones in roadmap.md.

- Other:
  - Updated various tests to support the new version-aware logic.
  - Optimized imports and synchronized IDE settings.
2026-02-04 02:53:33 +01:00

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🗺️ Roadmap

This document outlines the achieved milestones and planned enhancements for the Zabbix GraphQL API project.

✅ Achieved Milestones

  • 🎯 VCR Product Integration: Developed a specialized GraphQL API as part of the VCR Product to enable the use of Zabbix as a robust base for monitoring and controlling IoT devices.

    • First use case: Control of mobile traffic jam warning installations on German Autobahns.

  • ⚡ Query Optimization: Optimized GraphQL API queries to reduce the amount of data fetched from Zabbix depending on the fields really requested.

    • Implementation: Added dynamic output selection and field pruning in ZabbixRequest.

  • 🔓 Open Source Extraction & AI Integration: Extracted the core functionality of the API to publish it as an Open Source project.

    • AI Integration: Enhanced with Model Context Protocol (MCP) and AI agent integration to enable workflow and agent-supported use cases.

📅 Planned Enhancements

  • 🏗️ Trade Fair Logistics Use Case: Extend the API to support trade fair logistics use cases by analyzing requirements from business stakeholders.

    • Analysis: Analysis of "Trade Fair Logistics" and derived requirements document.
    • Simulation:
      • Create mocked "real world sensor devices" relevant for the use case.
      • Create a sample device collecting relevant information from public APIs, e.g. weather conditions or traffic conditions at a given location.
      • Simulate the traffic conditions on the route by using the simulated sensor devices.
    • Configuration: Analyze a real-world transport and configure Zabbix by placing sensor devices at the right places of the route.

  • 📦 CI/CD & Package Publishing: Build and publish the API as an npm package as part of the .forgejo workflow to simplify distribution and updates.

  • 🧱 Flexible Usage: Transform the package into a versatile tool that can be used either standalone or as a core library (published to npmjs.com).

  • 🧩 Extension Project: Add support for problem and trigger-related queries through the zabbix-graphql-api-problems extension.

    • AI Integration: Leverage MCP + AI agents to automatically react to Zabbix problems within external workflows.