n8n Workflow: Triage Docker Image Upgrades with LLM Risk
n8n Workflow: Triage Docker Image Upgrades with LLM Risk
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n8n Workflow: Triage Docker Image Upgrades with LLM Risk
Regular price
£4.99
Regular price
£4.99
Sale price
Unit price
/
per
Upgrade triage for Docker images—powered by an LLM risk verdict
This n8n workflow runs daily to detect pending Docker image tag upgrades in your What's Up Docker (WUD), pulls the relevant GitHub release notes and migration diffs, then uses an LLM (Ollama or OpenAI-compatible) to triage whether database/SQL changes look SAFE, CAUTION, DANGER, or UNKNOWN. Finally, it sends a clear verdict to ntfy, Slack, Discord, or your webhook.
What this workflow does
- Runs on a schedule: executes daily at 06:30.
- Detects pending upgrades: requests the container list from your WUD instance and filters to images with tag-based updates available.
- Maps to GitHub releases: resolves the associated GitHub repository from the WUD link template and determines the current vs target release tags.
- Collects migration evidence: fetches GitHub release notes for the target tag and compares tags to gather changed migration files and SQL patches.
- LLM risk triage: classifies upgrades using simple SQL patterns, then prompts the LLM to summarize why and provide pre-check SQL.
- Notifies where you want: posts the verdict, LLM summary, and a GitHub compare link to ntfy, Slack, Discord, or a custom webhook.
Use cases
- SaaS operators who want an early warning before applying container image updates that may include risky migrations.
- Automation engineers managing fleets of Docker services and needing standardized upgrade risk reporting.
- Teams that want LLM-assisted SQL pre-check guidance before production upgrade windows.
Technical details
- Scheduler: daily run at 06:30.
- Integrations: What's Up Docker (WUD), GitHub, ntfy, Slack, Discord, and webhook.
- LLM options: OpenAI-compatible Chat Completions endpoint or Ollama endpoint.
- n8n nodes/logic noted: if, set, code, sticky note, http request, and split in batches.
Set up your WUD base URL, configure your LLM provider/model and endpoint, and optionally add a GitHub token in the Template Config to help avoid low unauthenticated rate limits.
