What is n8n? The Open-Source Workflow Automation Platform Explained

TL;DR — 3-4 sentence summary covering what n8n is, key differentiators (open-source, self-hosted, fair-code license), who should use it, and primary benefits vs. cloud alternatives

n8n is an open-source workflow automation platform that lets you connect apps, APIs, and AI models without writing extensive code. Unlike cloud-only competitors like Zapier or Make.com, n8n operates under a fair-code license and offers self-hosting options, giving you complete control over your data, workflows, and infrastructure costs. It’s ideal for developers who need custom integrations, operations teams managing sensitive data, and organizations wanting to avoid per-execution pricing that scales unpredictably with cloud alternatives.

The platform’s primary advantage is flexibility: you can deploy n8n on your own infrastructure using Docker, Kubernetes, or traditional VMs, then build workflows that integrate with 400+ pre-built nodes including Slack, GitHub, PostgreSQL, and AI providers like OpenAI and Anthropic. Self-hosting means you control data residency for compliance requirements (GDPR, HIPAA, SOC 2), avoid vendor lock-in, and eliminate per-workflow execution fees that can reach thousands monthly on cloud platforms.

n8n particularly excels when combining traditional automation with AI capabilities. You can chain together API calls to Claude or ChatGPT, process responses with custom JavaScript or Python code nodes, then trigger actions in tools like Jira, Linear, or PagerDuty based on AI analysis. For example, a workflow might analyze customer support tickets with GPT-4, extract action items, create GitHub issues, and notify your team in Slack—all running on your infrastructure.

The trade-off is operational responsibility: you manage updates, backups, and scaling. However, for teams already running infrastructure with Ansible, Terraform, or Kubernetes, adding n8n to your stack is straightforward. The platform also offers n8n Cloud for teams wanting the open-source flexibility without infrastructure management, though self-hosting remains the most cost-effective option for high-volume workflows.

What is n8n and Why It Matters in 2026 — Introduction to n8n as a node-based workflow automation platform, its fair-code licensing model, and why developers/ops teams choose it over SaaS alternatives like Zapier or Make.com

n8n is a node-based workflow automation platform that lets you connect apps, APIs, and databases through a visual interface—without vendor lock-in. Unlike SaaS tools like Zapier or Make.com, n8n uses a fair-code license (Apache 2.0 with Commons Clause), meaning you can self-host it for free, inspect the source code, and customize nodes to fit your infrastructure.

In 2026, developers and operations teams choose n8n because it runs on their own infrastructure—whether that’s a Kubernetes cluster, a Docker container on AWS EC2, or a local development environment. This matters when you’re automating sensitive workflows like syncing customer data from PostgreSQL to Salesforce, triggering Terraform deployments based on GitHub webhooks, or processing PII through AI models.

With n8n, you control your data flow. A typical workflow might look like this:

# Example: AI-powered incident response workflow
Trigger: Prometheus alert webhook
→ Extract error logs from Elasticsearch
→ Send to Claude API for root cause analysis
→ Create Jira ticket with AI summary
→ Post to Slack with recommended fixes

Caution: When using AI nodes (OpenAI, Anthropic Claude, or local LLMs) to generate system commands, always validate outputs before execution. AI models can hallucinate package names, incorrect flags, or dangerous commands. Never pipe AI-generated bash directly to sudo or production systems.

n8n’s 400+ pre-built nodes cover everything from Ansible playbooks to Stripe payments, but you can also write custom JavaScript functions or call any REST API. For teams already using infrastructure-as-code tools like Terraform or Ansible, n8n becomes the orchestration layer that connects monitoring (Datadog, Grafana) to remediation actions—all while keeping credentials in your own vault, not a third-party SaaS database.

Core Features and Architecture — Overview of n8n’s visual workflow editor, 400+ integrations, custom code nodes (JavaScript/Python), webhook triggers, scheduling, and self-hosted vs. cloud deployment options

n8n’s visual workflow editor uses a node-based canvas where you drag, connect, and configure automation steps. Each node represents an action—sending a Slack message, querying a PostgreSQL database, or calling the OpenAI API. The editor displays live data previews as you build, letting you inspect JSON responses and debug workflows in real-time.

With 400+ pre-built integrations, n8n connects to tools like GitHub, Airtable, Stripe, HubSpot, and AWS services. Each integration exposes specific operations—for example, the Jira node can create issues, update statuses, or search tickets. When a native integration doesn’t exist, HTTP Request nodes let you call any REST API directly.

Custom Code Capabilities

Code nodes execute JavaScript or Python for custom logic. Here’s a JavaScript example that enriches customer data before sending to Salesforce:

const items = $input.all();
return items.map(item => ({
  json: {
    fullName: `${item.json.firstName} ${item.json.lastName}`,
    enrichedAt: new Date().toISOString(),
    riskScore: item.json.orderValue > 10000 ? 'high' : 'low'
  }
}));

Caution: When using AI models like Claude or GPT-4 to generate code nodes that execute system commands or database queries, always validate the output in a staging environment. AI can hallucinate incorrect API endpoints or generate destructive operations.

Triggers and Scheduling

Workflows activate via webhook URLs, cron schedules (0 9 * * 1-5 for weekday mornings), or polling intervals. Webhook triggers are ideal for real-time events from Stripe payments or GitHub pushes.

Deployment Options

Self-hosted deployments give full control over data and customization. Deploy via Docker:

docker run -it --rm --name n8n -p 5678:5678 -v ~/.n8n:/home/node/.n8n n8nio/n8n

n8n Cloud handles infrastructure management while maintaining workflow portability—export JSON definitions and migrate between environments seamlessly.

n8n vs. Zapier vs. Make.com: Feature Comparison — Side-by-side comparison table covering pricing models, execution limits, custom code support, data privacy, AI integration capabilities, and ideal use cases for each platform

When choosing between workflow automation platforms, understanding their core differences helps you select the right tool for your needs. Here’s how n8n, Zapier, and Make.com stack up:

n8n excels with direct API access to Claude, ChatGPT, and custom AI models. You can build sophisticated chains using the HTTP Request node:

// n8n Code node example - AI command validation
const userCommand = $input.first().json.command;
const aiValidation = await $ai.chat({
  model: 'claude-3-5-sonnet-20241022',
  messages: [{
    role: 'user',
    content: `Validate this system command for safety: ${userCommand}`
  }]
});

return { command: userCommand, safe: aiValidation.includes('safe') };

⚠️ Caution: Always validate AI-generated system commands in a staging environment before production deployment. AI models can hallucinate dangerous commands like rm -rf / or expose credentials.

Zapier’s AI features are more limited to pre-built actions, while Make.com offers moderate flexibility with OpenAI integrations. For developers building AI-powered workflows with tools like Ansible or Terraform, n8n’s self-hosted option provides the control and unlimited executions needed for complex automation pipelines.

How n8n Handles AI Workflows — Explanation of AI agent nodes, LangChain integration, vector database connectors, and how n8n orchestrates multi-step AI workflows with tools like OpenAI, Anthropic, and local LLMs

n8n has evolved into a powerful AI orchestration platform, offering native nodes for building sophisticated AI agent workflows. The platform provides dedicated nodes for OpenAI, Anthropic Claude, Google PaLM, and Cohere, plus a generic HTTP node for connecting to local LLMs like Ollama or LM Studio running Llama 3 or Mistral models.

n8n’s LangChain nodes enable you to build conversational AI agents with memory, tool-calling capabilities, and retrieval-augmented generation (RAG). You can create agents that interact with external APIs, query databases, or execute workflow logic based on natural language inputs. For example, an AI agent can analyze Prometheus metrics, determine if an alert requires action, and automatically create a PagerDuty incident with context-aware descriptions.

Vector Database Connectors

The platform includes native integrations with Pinecone, Qdrant, Weaviate, and Supabase for vector storage. This allows you to build semantic search systems, chatbots with long-term memory, or documentation assistants. A typical workflow might embed Confluence documentation into Pinecone, then use Claude to answer support questions with relevant context retrieved from the vector store.

Multi-Step AI Orchestration

n8n excels at chaining AI operations across multiple steps. You can send user queries to GPT-4 for intent classification, route to specialized agents based on the result, retrieve relevant data from PostgreSQL, format it with a prompt template, and send the final response through Slack—all in a single workflow.

// Example AI node configuration for command validation
{
  "model": "gpt-4-turbo",
  "messages": [
    {"role": "system", "content": "Validate this Terraform command for safety"},
    {"role": "user", "content": "{{ $json.command }}"}
  ]
}

⚠️ Critical Warning: Always implement human-in-the-loop approval for AI-generated system commands. Never execute Ansible playbooks, Terraform plans, or kubectl commands directly from AI output without manual review. AI models can hallucinate dangerous commands that could delete production resources or expose sensitive data.

Pricing and Deployment Models — Breakdown of self-hosted (free), n8n Cloud pricing tiers, infrastructure costs for self-hosting, and total cost of ownership comparison with commercial alternatives

n8n offers flexible deployment options that significantly impact your total cost of ownership. The self-hosted version is completely free under the Fair Code license, giving you unlimited workflows and executions when running on your own infrastructure.

Running n8n on a basic DigitalOcean droplet ($12/month, 2GB RAM) or AWS t3.small instance (~$15/month) handles most small-to-medium workloads. For production deployments with PostgreSQL and Redis, expect $40-80/month. Using Docker Compose or Kubernetes with Terraform for infrastructure-as-code adds no licensing costs:

# Example Docker deployment cost: $0 software + infrastructure
docker run -d --name n8n -p 5678:5678 \
  -v ~/.n8n:/home/node/.n8n \
  n8nio/n8n

n8n Cloud Pricing (2026)

n8n Cloud eliminates infrastructure management with these tiers:

• Starter: $20/month (2,500 executions)
• Pro: $50/month (10,000 executions)
• Enterprise: Custom pricing (unlimited executions, SSO, SLA)

Cloud pricing includes automatic updates, monitoring with Prometheus-compatible metrics, and managed backups.

Cost Comparison with Alternatives

Compared to commercial platforms, n8n delivers substantial savings:

• Zapier Professional: $49/month (750 tasks) vs n8n Cloud Pro: $50/month (10,000 executions)
• Make.com Pro: $29/month (10,000 operations) vs n8n self-hosted: $15/month infrastructure only
• Workato: Starts at $10,000/year vs n8n Enterprise: typically $5,000-15,000/year

For AI-heavy workflows calling OpenAI, Anthropic Claude, or local LLMs, self-hosting avoids per-execution charges. A workflow making 50,000 AI API calls monthly costs the same $15 infrastructure fee, while Zapier would require their $299/month plan.

Caution: When using AI agents to generate infrastructure commands (Ansible playbooks, Kubernetes manifests), always validate outputs in staging environments before production deployment to prevent configuration errors.