DeerFlow 2.0 Production Deployment — Docker Compose, Kubernetes, Message Gateways
Deploy DeerFlow to production with Docker Compose and Kubernetes. Connect Slack/Telegram message gateways for team access.

DeerFlow 2.0 Production Deployment — Docker Compose, Kubernetes, Message Gateways
In Part 3, we covered custom skills, MCP integration, and the sandbox system. This post covers deploying DeerFlow to production.
We'll bring up the full stack with Docker Compose, scale with Kubernetes, and connect Slack/Telegram gateways for team access.
1. Deployment Architecture
Production DeerFlow consists of 4 services:
This part is for subscribers
A subscription unlocks every premium series and its Jupyter notebooks.
You need a free account to subscribe. Cancel anytime.
Related Posts

OpenClaw vs DeerFlow 2.0 — Personal AI Assistant vs Multi-Agent Runtime
OpenClaw (333K stars) vs DeerFlow 2.0 (40K stars) comparison. Personal AI butler vs AI research team — architecture, channels, skills, and real benchmarks.

AgentScope Production Deployment — Runtime, Monitoring, Scaling
Docker deployment with agentscope-runtime, OpenTelemetry tracing, AgentScope Studio, RL fine-tuning, production checklist.

AgentScope Realtime Voice Agents — Build 3 Voice AI Apps
Build 3 real voice AI apps — chatbot, simultaneous interpreter, and customer service bot with RealtimeAgent + Gradio.