n8n: guides & tutorials

Zapier Pro costs $69/month for 2,000 tasks and 20 Zaps. Hit your task cap mid-month and your workflows stop running until the next billing cycle — or you upgrade to the $103/month Team plan. If your automation volume is growing or your workflows touch internal systems and proprietary data, a self-hosted alternative gives you unlimited executions, full control over credentials and API keys, and a fixed monthly VPS cost that doesn't scale with task count.

TL;DR

• One docker-compose.yml: n8n + LiteLLM + Twenty CRM + shared PostgreSQL + Redis + Caddy
• Measured idle RAM: ~1.7 GB; peak: ~2.5 GB (parallel workflow executions with live LiteLLM calls)
• Minimum Liquid Web tier: 8 GB Managed VPS (~$33–$40/mo)
• Zapier Pro + unmanaged OpenAI API + HubSpot Starter: ~$69 + variable + $50/mo vs ~$33/mo self-hosted

Most sales teams that want AI-augmented automation end up in one of two bad places: paying for Zapier Pro, a direct OpenAI API key they can't audit, and HubSpot CRM — three separate subscriptions that don't compose well and bill regardless of usage. Or they write fragile Python scripts that break on every API change and nobody wants to maintain.

This guide deploys the middle path: Twenty CRM for pipeline management, n8n for visual workflow automation, and LiteLLM as an OpenAI-compatible AI proxy — all on a single Liquid Web 8 GB VPS. n8n calls LiteLLM for every AI task (lead enrichment summaries, proposal draft generation, inbound form classification), and LiteLLM provides budget caps, model fallbacks, and a unified request log.

Enterprise competitive intelligence tools — Crayon, Klue, Kompyte, Similarweb — charge $300–$2,000/month (quote-based, plan-dependent) for competitive monitoring dashboards. This same monitoring can be built with Apify for data collection, Claude for analysis, n8n for orchestration, and a free dashboard — for under $50/month (starting cost; scales with competitor count, Actor fees, and proxy usage).

This guide builds it step by step: from identifying what to monitor, to automated daily scrapes, to AI-powered change detection that alerts your team in Slack when competitors make moves that matter.

TL;DR:

Cloud API costs scale linearly with usage. Self-hosting Ollama + n8n + Coolify on a $20/month VPS removes per-token fees for local Ollama inference — you still pay for the VPS, bandwidth, and your time; throughput is limited by CPU/RAM. When workflows call Apify, email, or other SaaS APIs, data transits those providers — not only your server.

This guide covers the complete setup from bare VPS to production-ready AI pipeline, with official documentation links for every step.

TL;DR:

Prerequisites:

• A VPS with 4+ CPU cores, 8+ GB RAM, 80+ GB SSD ($16–$25/month range). Minimum 8 GB RAM required for running Llama 3.1 8B comfortably alongside n8n.
• A domain name pointed to the VPS IP
• Basic terminal/SSH knowledge
• 30–60 minutes of setup time

The n8n + Dify + Ollama stack is a common 2026 self-hosted pattern for teams that want open-source control over automation, LLM apps, and where models run: n8n runs event-driven workflows across SaaS and APIs; Dify ships LLM apps, agents, and knowledge bases; Ollama exposes a local OpenAI-compatible inference API on your hardware. None fully replaces the others, but teams often blur which layer owns which job.

This article maps each tool’s role, where capabilities overlap, how they compose into one architecture versus compete for the same budget and headcount, and a practical deployment roadmap you can adapt from a laptop toward production.

For how agent runtimes, MCP, and infra headlines affect wiring choices like these, see Top 10 AI and tech stories this week (March 17–24, 2026).

Trigger ComfyUI from n8n, generate images, and send them to Slack, S3, or your CMS. No manual clicking. This guide covers the ComfyUI API mode, building n8n workflows with HTTP Request nodes, dynamic prompts, batch generation, error handling, and the Make.com alternative. ComfyUI must be running with --listen to accept API requests — see ComfyUI on a cloud GPU for setup.

This guide is for developers who've outgrown n8n basics and want custom logic: Code nodes, sub-workflows, error handling, AI agents, and webhook-triggered scraping with Apify. You'll also see how to self-host n8n and when Make.com might fit better.

n8n is an open-source workflow automation tool. Apify provides cloud-hosted web scraping Actors. Together they form a powerful pipeline: Apify collects data, n8n orchestrates where it goes next — Google Sheets, Slack, databases, AI models, or downstream APIs.

This guide shows three integration patterns with working node configurations.

TL;DR by persona: Developers → n8n (self-host, Code nodes). Non-technical teams → Make.com (visual, affordable, AI). Maximum app coverage → Zapier (6,000+ apps, easiest). Startups watching cost → Make or self-hosted n8n. Enterprise → Zapier or Make with support contracts.

All three are visual, node-based automation platforms. They differ sharply on pricing, self-hosting, code support, and target user. This guide helps you choose and migrate.

n8n is a workflow automation tool that pairs well with Apify because it handles long-running jobs, large JSON payloads, and branching logic without the tight synchronous limits of simpler connectors. This guide covers setup, the official Apify node, webhook patterns for slow Actors, example workflows, and operational tips.