DIY Guide: Build a Manufacturing eCommerce Growth Stack on AWS

TL;DR

This guide will show you how to create a fast, secure, and scalable eCommerce stack on AWS for your manufacturing business. You’ll learn to build a robust foundation that includes a storefront, a secure data lake, dealer self-service tools, and clear analytics. The key is to start simple and add new features in small, manageable steps. This approach lets you deliver value every week and see tangible results quickly.

Who this is for

• Manufacturers selling B2B and B2C.
• Teams that want to reduce manual quoting, improve inventory accuracy, and speed up their website.
• Companies that need real-time analytics instead of manual spreadsheets.

What you will build

• A scalable storefront with CDN and caching.
• A unified data lake on Amazon S3 to combine data from your ERP, PIM, CRM, and store.
• A secure dealer portal for quotes, custom pricing, and contract terms.
• AI features for product recommendations and demand forecasting.
• Supply chain visibility with simple IoT signals.
• A robust security baseline and cost controls.
• Clear dashboards for data-driven decisions.

Week 1: Foundation and Networking

The first step in building a scalable, secure eCommerce stack on AWS is to establish a solid foundation. This begins with creating a dedicated AWS account, or an account within an AWS Organization, to separate your production environment from other workloads. Within this account, you will set up a Virtual Private Cloud (VPC) with both public and private subnets, which provides a logically isolated network where you can launch your resources. This structure allows you to place sensitive resources like databases and internal applications in a private subnet, shielding them from the public internet.

Beyond the core networking, you must implement a robust security and auditing baseline from the beginning. By enabling AWS CloudTrail and AWS Config, you create a complete audit log of all API activity and track resource configurations, which is essential for compliance and troubleshooting. Additionally, setting up a secure S3 bucket with default encryption for backups ensures that your critical data is protected from unauthorized access, laying the groundwork for a resilient and compliant operation.

First, create a secure and organized foundation in AWS.

1. Create a dedicated AWS account or an AWS Organization account for your production environment.
2. Set up a VPC (Virtual Private Cloud) with public and private subnets.
3. Add an Internet Gateway and NAT (Network Address Translation) as needed.
4. Turn on AWS CloudTrail and AWS Config for auditing.
5. Create an S3 bucket called company-prod-backups with default encryption enabled.

Result: A secure base that supports anything you add later.

Week 2: A Fast and Reliable Storefront

Once your foundation is in place, the next step is to build a storefront that is both fast and highly available. You have a choice between two main options: deploying your application on Amazon EC2 or Amazon Lightsail for a more traditional setup, or containerizing it with Amazon ECS Fargate for a modern, scalable approach. By placing your application behind an Application Load Balancer and using an Auto Scaling group, you ensure that it can automatically handle increases in traffic during promotions or peak seasons, preventing frustrating timeouts for your customers.

To make your storefront even faster and more resilient, you will integrate a Content Delivery Network (CDN) using Amazon CloudFront. CloudFront caches your content, including static assets and images stored on Amazon S3, at edge locations around the globe, delivering it to your users with minimal latency. For your dynamic content and transactions, a managed database like Amazon RDS or Aurora provides enterprise-grade performance and reliability. By enabling Multi-AZ deployments and automated backups, you ensure that your data is protected and always available, even in the event of a system failure.

Make your site fast and resilient, even during peak traffic.

• Option A: Use Amazon EC2 or Amazon Lightsail for a managed host if you’re using platforms like WooCommerce or Magento.
• Option B: Containerize your application with Amazon ECS Fargate if you expect traffic bursts.

Steps:

1. Launch the application in a private subnet behind an Application Load Balancer.
2. Place Amazon CloudFront in front of the load balancer for a global CDN.
3. Store static assets and images on Amazon S3 and serve them through CloudFront.
4. Use Auto Scaling to ensure your application can handle traffic spikes.
5. Add a managed database like Amazon RDS or Amazon Aurora. Enable backups and Multi-AZ for high availability.

Result: Faster page load times and fewer timeouts during peak periods.

Week 3: Create a Unified Data Lake

A unified data lake is the single most valuable asset you can build for your business, as it breaks down data silos and provides a single source of truth. The process starts by creating an S3 bucket with a clear folder structure to organize your data from various sources, such as your ERP, PIM, CRM, and eCommerce store. By regularly exporting and landing this raw data in the /raw folder, you create a central repository for all your critical business information, from sales and inventory to customer interactions.

Once the data is in your S3 data lake, you use AWS Glue Crawlers to automatically discover the schema of your data and catalog it. From there, AWS Glue jobs or Lambda functions transform this raw data into a clean, structured format in the /clean folder. This transformation process is where you standardize data types, remove duplicates, and prepare the data for analysis. The result is a clean, query-ready data set that can be used for reporting, business intelligence, and powering downstream applications and AI services.

Unify your data to get a single source of truth for reporting and automation.

1. Create an S3 bucket named s3://company-prod-datalake with folders like /raw, /clean, and /analytics.
2. Export data from your ERP, PIM, CRM, and eCommerce store and land it in the /raw folder. Use formats like CSV, Parquet, or JSON.
3. Use AWS Glue Crawlers to automatically catalog the data.
4. Use AWS Glue jobs or AWS Lambda to transform the raw data into a clean, query-ready format in the /clean folder.
5. Query the data with Amazon Athena to validate joins and create tables for key metrics.

Result: A single, reliable source for all your reporting needs.

Week 4: Analytics and Dashboards

With a unified data lake in place, you can finally move beyond spreadsheets and create powerful, real-time analytics dashboards. The process is simple: you connect Amazon QuickSight directly to the tables you defined in your data lake. QuickSight acts as your business intelligence tool, allowing you to build rich, interactive dashboards without the need for complex data engineering. These dashboards can be customized for different audiences, providing executives with a high-level view of revenue and margin, while giving operations teams granular insights into pick-pack times and open quotes.

The true value of these dashboards is in providing actionable visibility for daily decisions. By scheduling data refreshes and email summaries, you ensure that every team has access to the most up-to-date information, eliminating the need for manual reconciliation and data requests. This creates a culture of data-driven decision-making, where everyone from the factory floor to the C-suite can see clear metrics and act on them instantly, leading to greater efficiency and fewer surprises.

Turn your data into actionable insights for daily decision-making.

1. Spin up Amazon QuickSight.
2. Connect QuickSight to the Athena tables you created in the data lake.
3. Publish dashboards for executives and operations.
   • Executive View: Revenue, margin by product group, forecast vs. actual, and backorders.
   • Operations View: Pick-pack time, open quotes, late shipments, and aging inventory.
4. Schedule data refreshes and email summaries.

Result: You’ll have clear daily visibility without the hassle of spreadsheets.

Week 5: Dealer and Distributor Self-Service

Empowering your dealers with a self-service portal can dramatically reduce the manual workload on your sales and support teams. The best approach is to start with a “thin slice” that solves a single, painful step, like a self-service quoting API. Using a serverless architecture with Amazon API Gateway and AWS Lambda, you can build a lightweight, scalable service that looks up customer details, retrieves contract prices, and creates a clean quote, all without human intervention.

For the front end, you can build a simple web interface for your dealers, securing it with Amazon Cognito for authentication. To ensure a smooth user experience, it’s crucial to decouple the portal from your backend ERP. Using Amazon SQS (Simple Queue Service) as a buffer allows your portal to submit an order request instantly, while the ERP processes the order at its own pace. This prevents dealers from waiting on slow systems and protects the user interface, resulting in fewer frustrated calls and emails for your team.

Empower your dealers and reduce the burden on your sales team.

1. Build a simple serverless API using Amazon API Gateway and AWS Lambda to handle customer lookups, contract pricing, and quote creation.
2. Store temporary state in Amazon DynamoDB for speed and low cost.
3. Create a simple front-end portal for dealers using Amazon Cognito for secure authentication.
4. Integrate the API with your ERP for real-time pricing and order creation. Use Amazon SQS (Simple Queue Service) to decouple the user interface from slow ERP calls.

Result: Dealers can create their own quotes and orders, freeing up your team to focus on relationships.

Week 6: AI for Growth and Planning

Integrating AI can give your business a significant competitive edge, and it’s easier than you might think when you start with a single use case. For example, if you want to improve conversion rates, you can use Amazon Personalize to automatically generate “related items” or “frequently bought together” recommendations on your product pages. This service is trained on your existing order data and product interactions, so it learns what customers are likely to buy next and provides highly relevant suggestions.

Alternatively, you could focus on a different problem, like reducing inventory guesswork. By using Amazon Forecast with your historical sales and promotion data, you can build a model that predicts future demand for your top-selling products. This provides clear, data-backed insights for your inventory team, allowing them to make more accurate purchasing decisions and reduce costly stockouts or overstocking. The key is to pick one problem, solve it with a single AI service, and ship a pilot in just a few weeks.

Start with one high-impact AI use case and ship it quickly.

• Product Recommendations: Use Amazon Personalize to train a model based on customer orders. Start with “related items” and “frequently bought together.”
• Guided Selling: Use Amazon Bedrock or Amazon SageMaker to build a chat widget that can answer product questions and suggest SKUs.
• Demand Forecasting: Use Amazon Forecast with historical sales data. Feed the results to your inventory dashboard to reduce stockouts.

Result: Improved conversion rates and more accurate inventory planning.

Week 7: Supply Chain Signals

You don’t need to instrument your entire factory floor to gain valuable supply chain visibility. A simple and effective approach is to start small by sending a single status event from a critical workstation or storage area. Using a service like AWS IoT Core, a device can send a message whenever a job starts or finishes. This real-time signal provides a simple but powerful data point on the status of your production process.

This data is then streamed to your data lake, where it can be transformed and made available for analysis. By adding a simple widget to your QuickSight dashboard, you can display real-time metrics like work-in-progress (WIP) and cycle time. This immediate visibility helps your team identify bottlenecks, make faster decisions about production schedules, and guide shipping, all with a minimal initial investment in hardware and software.

Get a glimpse into your supply chain without a huge investment.

1. For a critical area, send a simple status event to AWS IoT Core when a job starts or finishes.
2. Stream these events to Amazon Kinesis or directly to a Lambda function.
3. Land the events in your S3 data lake and transform them.
4. Add a QuickSight widget to track work-in-progress (WIP) and cycle time.

Result: Real-time signals that provide insights for production and shipping.

Week 8: Security and Cost Controls

A robust security posture is non-negotiable for any modern eCommerce business. You should start by protecting your public-facing storefront with AWS WAF (Web Application Firewall) and AWS Shield Standard, which defend against common web exploits and DDoS attacks. For internal and dealer portals, use Amazon Cognito to handle user authentication, providing a secure and scalable way to manage user identities without building a system from scratch.

Beyond the user-facing services, a comprehensive security baseline requires continuous monitoring and data encryption. Ensure all your data, from S3 to RDS, is encrypted at rest and in transit using AWS KMS keys. Services like Amazon GuardDuty and AWS Security Hub provide continuous threat detection and a unified view of security findings across your entire AWS environment. By implementing these measures and replicating critical data to a second region with S3 Cross-Region Replication, you build a resilient, compliant operation that protects your brand and customer trust.

Protect your brand and manage your budget from day one.

• Security: Turn on AWS Shield Standard and AWS WAF for your site. Use KMS keys to encrypt everything at rest and in transit. Enable GuardDuty and Security Hub for continuous monitoring.
• Cost Control: Tag resources by owner and application. Use Cost Explorer to track spending and set budgets. Use S3 lifecycle rules to move old data to cheaper storage tiers. Right-size databases and consider Graviton instances for savings.

Result: A resilient, compliant, and cost-effective operation.

Go-Live Checklist

A successful launch requires meticulous preparation and thorough testing. Before you go live, you must perform load testing to ensure your application can handle at least twice your expected peak traffic, guaranteeing a smooth experience for customers during a major promotion. You also need to test your failover scenarios for the database and application tiers to confirm that your system remains available even if a component fails, proving the resilience of your architecture.

The final phase of your go-live checklist involves verifying that all your new systems are communicating correctly. Confirm that the dealer portal can successfully authenticate and create a clean order in the ERP. Ensure your dashboards are showing real data and refreshing on schedule, providing your team with immediate visibility into the business. Finally, verify that all alerts for errors and budget thresholds are configured correctly, so you are notified of any issues immediately. By checking every box, you can launch with confidence and avoid costly post-launch surprises.

Example Thin-Slice Roadmap

Here’s an example of how you can incrementally build your stack:

• Week 1: CloudFront in front of your current site and image offload to S3.
• Week 2: S3 data lake with Glue and one Athena report for sales by SKU.
• Week 3: Dealer quote API with API Gateway, Lambda, DynamoDB.
• Week 4: QuickSight dashboards for executives and operations.
• Week 5: Amazon Personalize for “related items” on PDP.
• Week 6: Forecast pilot for top 20 SKUs.
• Week 7: WAF rules and GuardDuty alerts.
• Week 8: IoT signal for one workstation and a WIP widget.

Ship a slice each week and review the results every Friday. This iterative approach allows you to demonstrate value continuously and adapt based on feedback.

Common Pitfalls and How to Avoid Them

• Too many tools at once: Start with one thin slice, focus on quick wins.
• No data ownership: Assign a data steward and document schemas to maintain data integrity.
• Direct ERP calls in the UI: Use queues to decouple your UI from the ERP, protecting user experience.
• Dashboards without action: Tie every chart to an owner and a clear decision, ensuring insights lead to action.

What Success Looks Like

• Faster pages and higher conversion rates.
• Dealers self-serve, allowing sales teams to focus on building relationships.
• Clear forecasts and fewer emergency builds.
• Fewer spreadsheets, fewer reconciliations, and fewer surprises.

By following this DIY guide, manufacturing leaders and technical teams can leverage AWS to build a powerful eCommerce growth stack that delivers real outcomes quickly and positions your business for sustained success.

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