The Builder's Dilemma: SaaS Sprawl vs. Linux Management

Every automation engineer eventually hits a wall. You start with a simple idea: automate a few workflows, maybe wrap a GPT-4 wrapper around a business process. You sign up for Zapier, Airtable, and a Vector Database provider. It works flawlessly.

Three months later, you check your bank statement. You are paying $500 a month for tools that are essentially just moving JSON blobs from Point A to Point B. As you scale, SaaS pricing models punish you for success. The more tasks you run, the more you bleed.

The alternative? Open source and self-hosting.

But let’s be honest—managing a fleet of Docker containers on a raw Linux VPS isn't 'free.' You pay with your time. You pay with debugging Nginx configs at 2 AM.

I am Avnish Yadav, and over the last few years, I’ve refined a philosophy on tool selection. It isn't about being a purist (open source everything) or a consumer (buy everything). It is about leverage. Here is how I build my stack, and the specific tools I use to power my agency and micro-SaaS projects.

The Framework: The 3-Question Test

Before I add a tool to my stack, I run it through a rigorous filter. I don't care about the hype; I care about the architecture.

1. Is this a Commodity or Core IP?

If the function is a commodity (e.g., sending transactional emails, processing credit cards), I pay. I am not going to build my own SMTP server and warm up IPs for three months. I will pay Resend or SendGrid.

If the function holds my logic, data structure, or prompts, I prefer to own/self-host. This allows me to migrate easily and prevents platform lock-in.

2. Does the Pricing Scale with Usage or Compute?

Zapier charges by the "task." This is a tax on inefficiency. If I have a loop that runs 10,000 times, I go bankrupt.
n8n (Self-hosted) charges by the server resources (CPU/RAM). If I write efficient code, I can run 100,000 executions on a $10 VPS. I always choose tools where pricing scales with compute, not arbitrary "steps."

3. Do I need a GUI or an API?

As a developer, I prefer code. But for client handoffs, GUIs are necessary. The sweet spot is tools that offer both—a low-code interface for speed, but full JSON/Code node access for complexity.

The Orchestration Layer: n8n vs. Zapier

This is the backbone of any automation stack. This is where the logic lives.

The "Default" Choice: Zapier

Zapier is incredible for 0-to-1. It connects to everything. But for an engineer, it’s suffocating. You can't easily manipulate data arrays, error handling is rudimentary, and complex branching logic turns your screen into a spaghetti monster.

My Choice: n8n (Self-Hosted)

I run n8n on a Hetzner VPS using Docker. Here is why it wins:

• The Code Node: n8n allows you to drop into JavaScript or Python at any step. I’m not limited by the integration's pre-built actions. I can fetch data, transform it with regex, and map it exactly how I want.
• Execution Data: I can see exactly what data entered and exited a node. Debugging is transparent.
• Cost: I pay for the server ($6/mo). Whether I run 10 workflows or 10,000, the price is the same.

Verdict: If you are a developer, n8n is the only serious choice.

The Database Layer: Airtable vs. Supabase

The "Visual" Choice: Airtable

Airtable is essentially a pretty database. Clients love it because it looks like a spreadsheet. I still use Airtable as a "CMS" for simple internal tools or client-facing dashboards because the UI is unbeatable.

The "Scalable" Choice: Supabase

When I’m building a micro-SaaS or a heavy agentic workflow, Airtable falls apart. Rate limits are low, and relational data management gets clunky. Supabase is an open-source Firebase alternative (Postgres under the hood).

Why I use Supabase:

• Vector Storage: pgvector is built-in. I can store embeddings for RAG (Retrieval Augmented Generation) right next to my user data. No need for a separate Pinecone subscription.
• Auth: Handles user login out of the box.
• Row Level Security (RLS): Enterprise-grade security.

Verdict: Airtable for prototyping/internal ops. Supabase for production apps.

The Compute/Hosting Layer: Vercel vs. Coolify

This is the secret weapon of my stack.

We all love Vercel. It makes deploying Next.js apps magical. But again, once you scale or need backend workers, costs creep up. AWS is too complex for a solo dev to manage efficiently without Terraform scripts.

Enter Coolify

Coolify is an open-source, self-hostable Heroku/Vercel alternative. I install it on a VPS, and it gives me a dashboard to deploy my applications, databases, and services (like n8n, Supabase, Redis).

It connects to my GitHub. When I push code, Coolify builds the Docker image and deploys it. It handles SSL certificates automatically. It is the single highest ROI tool in my stack. It turns a raw Linux server into a PaaS.

The Intelligence Layer: LLM APIs vs. Local Models

Here is where the "Pay vs. Build" debate gets interesting.

Proprietary Models (OpenAI / Anthropic)

For complex reasoning, code generation, and final output formatting, Claude 3.5 Sonnet and GPT-4o are unbeatable. I pay for these APIs because the "smartness" per dollar is worth it. You cannot self-host a model this smart on consumer hardware yet.

Open Source Models (Llama 3 / Mistral via Ollama)

However, for tasks like classification, summarization, or PII extraction, GPT-4 is overkill. It’s too expensive and too slow.

I use Ollama to run Llama 3 on my local machine (or a GPU instance) for high-volume, low-complexity tasks. It protects data privacy and costs nothing per token.

My Current Stack: The "Avnish" List

If you hired me today to build a scalable AI system, this is exactly what I would spin up:

Conclusion: Start Paying, Then Optimize

If you are just starting, do not spend a week setting up a Kubernetes cluster. Pay the $20 for ChatGPT Plus and the $30 for Zapier. Validate your idea. Get a client.

But once you identify a repeatable process, ruthlessly optimize. Move the heavy lifting to self-hosted infrastructure. Own your data. Control your costs.

Automation isn't just about saving time; it's about building assets that work for you while you sleep, without draining your bank account. That is the difference between a user and an engineer.