Andreas Hilbig
97a0f70fd6
- **Optimization**: Implemented automatic Zabbix parameter optimization by analyzing GraphQL selection sets. - **ZabbixRequest**: Added optimizeZabbixParams with support for skippable parameters and implied field dependencies (e.g., state -> items). - **Resolvers**: Updated allHosts, allDevices, allHostGroups, and templates to pass requested fields to data sources. - **Data Sources**: Optimized ZabbixQueryHostsGenericRequest and ZabbixQueryTemplatesRequest to skip unnecessary Zabbix API calls. - **Regression Tests**: Enhanced RegressionTestExecutor with new tests for optimization (REG-OPT, REG-OPT-NEG), state retrieval (REG-STATE), dependent items (REG-DEP), and empty results (REG-EMPTY). - **Documentation**: Created query_optimization.md How-To guide and updated roadmap.md, README.md, and tests.md. - **Bug Fixes**: Fixed deviceType tag assignment during host import and corrected ZabbixCreateHostRequest to support tags.
28 lines
2.3 KiB
Markdown
28 lines
2.3 KiB
Markdown
# 🗺️ Roadmap
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This document outlines the achieved milestones and planned enhancements for the Zabbix GraphQL API project.
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## ✅ Achieved Milestones
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- **🎯 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**.
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- *First use case*: Control of mobile traffic jam warning installations on **German Autobahns**.
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- **🔓 Open Source Extraction & AI Integration**: Extracted the core functionality of the API to publish it as an **Open Source** project.
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- *AI Integration*: Enhanced with **Model Context Protocol (MCP)** and **AI agent** integration to enable workflow and agent-supported use cases.
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## 📅 Planned Enhancements
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- **⚡ Query Optimization**: Optimize GraphQL API queries to reduce the amount of data fetched from Zabbix depending on the fields really requested and improve performance.
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- **🏗️ Trade Fair Logistics Use Case**: Extend the API to support trade fair logistics use cases by analyzing requirements from business stakeholders.
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- *Analysis*: Analysis of "Trade Fair Logistics" and derived [requirements document](docs/use-cases/trade-fair-logistics-requirements.md).
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- *Simulation*:
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- Create mocked "real world sensor devices" relevant for the use case.
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- Create a sample device collecting relevant information from public APIs, e.g. weather conditions or traffic conditions at a given location.
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- Simulate the traffic conditions on the route by using the simulated sensor devices.
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- *Configuration*: Analyze a real-world transport and configure Zabbix by placing sensor devices at the right places of the route.
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- **📦 CI/CD & Package Publishing**: Build and publish the API as an **npm package** as part of the `.forgejo` workflow to simplify distribution and updates.
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- **🧱 Flexible Usage**: Transform the package into a versatile tool that can be used either **standalone** or as a **core library** (published to [npmjs.com](https://www.npmjs.com/)).
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- **🧩 Extension Project**: Add support for **problem and trigger-related** queries through the `zabbix-graphql-api-problems` extension.
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- *AI Integration*: Leverage **MCP + AI agents** to automatically react to Zabbix problems within external workflows.
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