Business Compass LLC

Designing a Production-Ready E-Commerce Platform on AWS Building an e-commerce platform that actually holds up under real traffic is harder than most tutorials make it look. This guide is for backend engineers, cloud architects, and technical founders who need more than a “getting started” walkthrough — you need a system that handles flash sales, protects customer data, and stays online when it matters most. Here’s what we’ll dig into: Core architecture and database design — how to structure your AWS infrastructure for scalability from day one, and how to build a database layer that doesn’t crack under load Frontend delivery and security — speeding up page load times to drive conversions, and locking down customer data and transactions end to end CI/CD, monitoring, and cost management — shipping updates without breaking production, catching issues before your customers do, and keeping your AWS bill from quietly spiraling out of control By the en...

Stop Running Out of IP Addresses Mid-Project If you’ve ever painted yourself into a corner with a /24 CIDR block and nowhere left to grow, you already know how painful poor IP address planning feels at 2 AM during a production incident. This guide is for cloud architects, DevOps engineers, and senior developers who are building on AWS and want to get VPC IP address planning right the first time — not after three rounds of subnet reconfiguration. Here’s what we’ll walk through together: How to choose the right CIDR block size for your VPC so you have room to scale without wasting address space Subnet design strategies that keep your workloads organized, secure, and easy to reason about Multi-VPC and hybrid cloud network architecture planning , including how to avoid the CIDR overlap nightmares that break VPC peering and Transit Gateway connections AWS VPC CIDR best practices aren’t just a checklist — they’re decisions that quietly shape everythin...

AWS Data Lake Architecture: From Raw Data to Production-Ready Analytics Building a data lake on AWS sounds straightforward until you’re knee-deep in unstructured files, broken pipelines, and a storage bill that makes no sense. Most teams hit the same wall: they get data in , but struggle to make it usable, secure, and affordable at the same time. This guide is for data engineers, cloud architects, and analytics teams who are moving beyond proof-of-concept and want a production-ready AWS data lake architecture that actually holds up under real workloads. Here’s what we’ll walk through together: How to design a layered data lake architecture using AWS S3 as your foundation, so raw data, curated data, and analytics-ready assets each live in the right place How to build an AWS ingestion pipeline that pulls from multiple sources without turning into a maintenance nightmare How to use AWS Glue ETL and AWS Lake Formation to transform raw data and lock down security...

Stop DNS Threats Before They Reach Your AWS Workloads If you’re running workloads in AWS, DNS security probably isn’t the first thing keeping you up at night — but it should be on your radar. DNS is one of the most abused attack vectors in cloud environments, and most teams don’t realize they have a gap until something goes wrong. This guide is for cloud architects, DevOps engineers, and security teams who want a practical handle on AWS Route 53 DNS Firewall — not a theoretical overview, but a real look at how it works and how to get it running in your environment. Here’s what we’ll walk through: The DNS security risks that make cloud environments a target — including DNS data exfiltration and malicious domain abuse How Route 53 Resolver DNS Firewall works and what it actually does to protect your AWS network at the resolver level How to set it up, block threats, and monitor it in real time so you’re not flying blind after deployment By ...

Deploy Machine Learning APIs on AWS with FastAPI and Docker You’ve trained your ML model. Now what? Getting it off your laptop and into production is where most tutorials leave you hanging. This guide walks you through the full machine learning API deployment process — from wrapping your model in FastAPI to containerizing it with Docker and shipping it to AWS. This is written for data scientists and backend developers who know Python and have a basic grasp of REST APIs but haven’t tackled cloud deployment yet. If you’ve been Googling “deploy ML model AWS” and keep landing on outdated walkthroughs, you’re in the right place. Here’s what you’ll get out of this: How to build a production-ready FastAPI application around your ML model — not a toy demo, but something that handles real traffic cleanly How to containerize your machine learning API with Docker so it runs the same way everywhere, no “works on my machine” surpr...

Stop Breaking Production: Build a Reusable Terraform Sandbox That Actually Works If you’ve ever pushed an infrastructure change and held your breath waiting to see what breaks, this guide is for you. Terraform infrastructure testing doesn’t have to mean “deploy it and hope for the best.” DevOps engineers, platform teams, and cloud architects who manage infrastructure as code need a safe place to validate changes before they hit real environments — and that place is a well-designed sandbox. This guide walks you through three things: How to design a reusable sandbox environment that your whole team can spin up, test against, and tear down without stepping on each other How to write Terraform tests that actually catch problems before they reach production How to wire your sandbox into a Terraform CI/CD pipeline so testing happens automatically, not as an afterthought No hand-wavy theory here. By the end, you’ll have a clear picture of what a scala...