How Can I Automate and Track Windows Driver Updates with Intune and PostgreSQL?
Asked by
TechWizard42
Hey everyone, I'm currently diving into a Proof of Concept (POC) project aimed at automating and tracking Windows driver updates via Microsoft Intune. Here's the plan:
- I'll leverage Microsoft Graph API to gather information on driver updates such as groups, versions, and rollout statuses from Intune.
- The data collected will be stored in a PostgreSQL database for better visibility and reporting over time.
- The entire process will be encapsulated within a Docker container, enabling it to run automatically on a scheduled basis, perhaps weekly.
- Additionally, I'll use Swagger/Bruno for API testing and to keep documentation in check.
The ultimate goal is to gain detailed insights on:
- Which groups (like Pilot, Ring1, Ring2, etc.) have received what drivers.
- The success or failure rates associated with each deployment.
- Rollout timelines and compliance trends.
This setup should effectively bridge the visibility gap with Intune and Autopatch by providing structured data and historical context. If anyone has experience with similar projects—especially concerning the integration of Graph API with PostgreSQL or automating driver updates in Intune—I'd really appreciate hearing your insights or any optimization tips you've picked up along the way!
Answers
You're spot on with the idea! I’d treat this like a small ETL process. Use app-only auth for Graph, stage your data as JSON in PostgreSQL, manage your upserts with watermarks, and pay attention to throttling. Hitting those beta windowsDriverUpdateProfiles and handling group changes can really streamline your process. Also, consider using tools like Metabase or Grafana for reporting directly on your PostgreSQL data.
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Just a heads-up, there's a chance you're sharing duplicate content from a previous post. Always check if your ideas are fresh before posting!
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This seems a bit too polished; it gives off an AI-generated vibe, not sure if it's entirely original.
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Storing a workflow in a container means you're packaging your application and dependencies into a single unit that can run consistently across different environments. You can still schedule tasks within the container, perhaps using tools like GitHub Actions or Azure Jobs instead of relying solely on cron. This helps to avoid environment drift, making sure it runs smoothly wherever you deploy it.
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