How to deploy AI agents in production
A practical guide compares deploying AI agents to VPS, Docker, and serverless platforms and walks through the trade-offs in cost, scalability, and ops overhead. The write-up is a useful bridge from prototyping to production-ready deployments for agent-based demos. (dev.to)
Pax (author) posted the guide to DEV on Mar 27, 2026, and the same walkthrough appears on Paxrel’s blog dated Mar 26, 2026. (dev.to) The article lists concrete monthly cost ranges for each model: VPS $5–$20, Docker on VPS $10–$30, serverless $1–$50 (pay-per-use), and managed platforms $20–$200. (dev.to) Provider-level examples and cheapest plans are enumerated: Hetzner $4.50/mo (2 vCPU, 4GB RAM, 40GB SSD), DigitalOcean $6/mo (1 vCPU, 1GB RAM, 25GB SSD), Vultr $6/mo (1 vCPU, 1GB RAM, 25GB SSD), and Contabo $6.50/mo (4 vCPU, 8GB RAM, 50GB SSD), with Paxrel using a Hetzner CX22 at ~$5.50/mo to run its agent stack. (dev.to) The post includes copy‑paste operational snippets: a Dockerfile based on python:3.12-slim, systemd log command journalctl -u ai-agent -f for live logs, and cron entries that run a social-post script every 6 hours and a monitoring report at 09:30 daily. (dev.to) Paxrel emphasizes trade-offs with reproducibility and isolation for Docker deployments and points out serverless is framed for event‑triggered agents (not always‑on), with the guide recommending process managers and monitoring to keep 24/7 agents reliable. (dev.to)
