FORMATION IA
Workflows IA avec n8n Auto-Hébergé pour les Équipes Techniques
Déployez, sécurisez et montez en charge n8n sur votre propre infrastructure pour des workflows IA en production.
Ce qu'elle couvre
Ce bootcamp de niveau praticien apprend aux équipes techniques à auto-héberger n8n sur Docker ou Kubernetes, à configurer la gestion des secrets et l'authentification, et à construire des workflows IA robustes intégrant des LLM, des bases vectorielles et des nœuds HTTP. Les participants travaillent sur des ateliers pratiques couvrant l'exécution en mode file d'attente, la mise à l'échelle des workers et les configurations haute disponibilité. À l'issue du programme, les équipes peuvent opérer une instance n8n prête pour la production et maintenir une bibliothèque de templates de workflows IA réutilisables.
À l'issue, vous saurez
- Deploy a production-ready n8n instance on Docker Compose or Kubernetes with persistent storage and TLS termination
- Configure encrypted credential storage, environment-based secrets, and role-based access control
- Build and test a multi-step AI workflow that chains an LLM call with a vector store retrieval and a downstream HTTP action
- Configure queue mode with Redis workers to handle concurrent workflow executions without data loss
- Implement monitoring dashboards and alerting for workflow failures using n8n execution logs and external observability tools
Sujets abordés
- Self-hosting n8n on Docker Compose and Kubernetes (Helm charts)
- Environment variables, secrets management, and credential encryption
- Queue mode with Redis and horizontal worker scaling
- High-availability deployment patterns and health checks
- Building AI workflows: LLM nodes, Langchain agents, and vector store integrations
- Webhook security, API authentication, and network isolation
- Error handling, retry logic, and workflow observability (logs + metrics)
- CI/CD for workflow version control and automated deployment
Modalité
Delivered as a 2–3 day in-person or remote bootcamp with live instructor-led sessions. Each module includes a hands-on lab on a shared cloud sandbox or participants' own infrastructure. Materials include pre-built workflow templates, a Helm values reference, and a secrets management checklist. Remote delivery uses breakout rooms for pair-programming labs. Minimum 70% hands-on time. A follow-up async Q&A session is recommended one week after delivery.
Ce qui fait que ça marche
- Standing up a dedicated staging environment that mirrors production before any live workflows are deployed
- Establishing a workflow naming convention and tagging system so the library remains navigable as it grows
- Integrating n8n execution logs into the team's existing observability stack (e.g. Grafana, Datadog) from day one
- Assigning a workflow owner per domain who is responsible for maintenance and incident response
Erreurs fréquentes
- Running n8n in a single-process mode in production, causing workflow queues to block under load
- Storing API keys and credentials as plain-text environment variables instead of using n8n's encrypted credential store
- Skipping webhook authentication and exposing n8n endpoints to the public internet without IP allowlisting
- Treating n8n workflow files as undocumented artefacts instead of version-controlling them alongside application code
Quand NE PAS suivre cette formation
A small startup with no dedicated DevOps resource that wants to get started with automation quickly — they are better served by n8n Cloud or a fully managed iPaaS like Make.com until they have the infrastructure maturity to self-host responsibly.
Fournisseurs à considérer
Sources
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