SYSTEM ARCHITECTURE
Built the production infrastructure that runs a global AI consulting platform’s RAG-powered agents.
The team had assembled a working set of AI agents using Open WebUI, n8n, and a vector database, but the deployment pipeline was manual. Every release meant SSH into a VPS, copy files, restart containers, hope nothing broke.
Latency was inconsistent. Agents would occasionally hit rate limits without backoff logic. There was no observability when an agent failed mid-request.
The founder needed a reliable production substrate so the team could ship new agents weekly without operational risk.
GitHub Actions deploying Open WebUI gateway + n8n workflows into hybrid AWS + GCP.
Reproducible local dev that mirrors production exactly.
Pinecone for embeddings + Chroma fallback for cost-controlled internal collections.
Grafana + Prometheus dashboards tracking p50/p95/p99 per agent.
Backoff layer in front of every Cloud LLM call with structured error logging.
Any team member can spin up an isolated staging env in under 10 minutes.
n8nPineconeChromaAWSGCPDockerKubernetesNginxTerraform
PythonGitHub ActionsGrafanaPrometheus
OpenAI
Anthropic ClaudeVertex AI
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