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ApparelMagic cuts design time by 99.9%

DoiT engineers built a serverless AWS Lambda image-generation microservice, saving two months of in-house development.

Meet ApparelMagic

ApparelMagic is an enterprise resource planning (ERP) system built for fashion brands. Its robust platform powers clothing companies with a cloud-based suite of tools to streamline operations and foster growth. From design to delivery, ApparelMagic is the choice for industry leaders who desire innovation, quality, and scalability.

The Challenge

ApparelMagic wanted to develop an image-generation microservice to help fashion brands automatically create clothing design images and shorten design cycles. Building this tool in-house would have diverted the team from enhancing other AI offerings for two months, taking focus away from their highest priority initiatives.

The Solution

DoiT's cloud engineers built a serverless image-generation tool using AWS Lambda with three separate queues for different image styles. The solution includes policy-based pre-processing for security, comprehensive monitoring with AWS CloudWatch, and dead-letter queues for error handling. DoiT delivered the complete infrastructure-as-code with thorough documentation and handover support.

Results

Saved two months of development work, allowing ApparelMagic's team to focus on core platform priorities
Delivered 99.9% faster product designs for customers, reducing weeks of work to seconds
Built scalable serverless architecture that automatically handles usage spikes while maintaining performance

DoiT helped us to go quickly from zero to one. In little more than two months, we went from having an idea for an image-generation tool to having a fully working system ready for our customers to use.
Davin Harding, Senior Software Engineer at ApparelMagic

Building a foundation for collaboration with generative AI training

Following an introduction from AWS, ApparelMagic and DoiT began working together to develop the image-generation tool. ApparelMagic explained its needs during an initial discovery call, including its preference to build the tool as a decoupled, API-first microservice. DoiT's expert cloud architects then ran a series of generative AI workshops and training sessions with the ApparelMagic team to give them a clear understanding of the technology that would be used to build the tool.

Architecting a reliable image-generation tool with DoiT cloud engineers

DoiT's cloud engineers built the image-generation tool using AWS Lambda's serverless architecture to automatically scale while preserving performance and governance. They implemented policy-based pre-processing of user prompts to ensure security and appropriate usage. The workflow was divided into three separate queues for each image style, with each queue linked to a dedicated AWS Lambda function to prevent resource competition and reduce bottlenecks.

Comprehensive observability and monitoring

DoiT enhanced the tool's maintainability with robust monitoring capabilities throughout the pipeline. Using separate queues for each image type simplified monitoring within the AWS console, giving ApparelMagic clear visibility of incoming, successful, and failed requests. DoiT integrated AWS CloudWatch for observability and used dead-letter queues to capture problematic requests, ensuring no requests were lost and enabling detailed error monitoring.

Smooth handover and rapid deployment

DoiT delivered the infrastructure-as-code for ApparelMagic to deploy in its platform. DoiT's cloud engineers worked closely with the ApparelMagic team to ensure a smooth handover, walking them through the full architecture and working together to test the tool and resolve any bugs. The image-generation tool is now being rolled out to customers, allowing them to use natural language prompts to instantly create three distinct images of their clothing designs.

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