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Posted on • Originally published at stakpak.gitbook.io

Set Up a Local AWS Environment with MiniStack

#aws #cloud #devops #infrastructure

Overview

Running cloud infrastructure locally is now easier than ever with tools like MiniStack.

This shift became even more important recently, as LocalStack changed its model requiring accounts, authentication tokens, and introducing paid plans for full usage.

As a result, many developers are looking for simpler, fully local, and free alternatives.

MiniStack lets you run AWS like services locally using real containers (Postgres, Redis, S3), making development faster, cheaper, and fully offline.

In this guide, we will use MiniStack to spin up a local AWS like environment and then use Stakpak to interact with it, configure it, and operate it.

LocalStack moved core services behind a paid plan. If you relied on LocalStack Community for local dev and CI/CD, MiniStack is your free, MIT-licensed drop-in replacement. No sign up, no API key, no telemetry.

Problem

Setting up and working with local cloud environments manually can still be painful:

  • You need to configure services (databases, storage, networking)
  • You have to remember CLI commands or SDK usage
  • You need to debug issues across multiple containers
  • You manually test if services are actually working
  • You document setup steps for future use

Even with tools like MiniStack replacing LocalStack for many use cases, operating local infrastructure is still manual work.

Small mistakes like misconfigured services, missing environment variables, or broken connections can slow down development.

Stakpak is open source, vendor neutral, and works with any model you choose.

Step-by-Step Guide

Prerequisites

  1. Install Stakpak
  2. MiniStack installed (or you can ask Stakpak to install it)
  3. Docker Installed (or you can ask Stakpak to install it)

Architecture

Application

What the app does

A user uploads a CSV or JSON file.

  • It lands in S3.
  • An event sends a job to SQS.
  • A Lambda reads the message.
  • The Lambda parses the file and stores results in Postgres.
  • It writes job state to Redis.

You can check the code source here

Now we can start that we understand the app and the architecture, we can start deploying it

Deployment

  1. Open Stakpak and ask it to deploy your app locally. That's it!
  2. It read the codebase and understood the architecture
  3. Spun up MiniStack, Postgres, and Redis via Docker Compose
  4. Bootstrapped AWS resources: S3 bucket, SQS queue, and Lambda
  5. Connected SQS to Lambda so uploads trigger processing automatically

Not lets test it..

Testing

It's working 🥳

Here is what happened:

  • We uploaded sample.csv -> got back a job_id
  • Lambda fired within 5 seconds (SQS polling)
  • Redis shows status: done, rows_inserted: 5
  • Postgres has all 5 rows parsed and stored

Extra Resources:

Related Use Cases

and more...

References

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