This page is also available in Deutsch, Español, Français, Italiano, 日本語, and Português.

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.

See how DoiT helps cloud teams control spend

Explore how Cloud Intelligence™ helps teams improve visibility, governance, and unit economics across cloud environments.

Visit DoiT Talk to our team

What they say

DoiT gave us the confidence to move from experimentation to production. They helped us understand the right way to build AI for the real world.

Milad Rezazadeh, CTO

Attribute™'s cost grouping technology took our cost visibility and allocation to a whole new level. Now, our teams are fully accountable for their budgets, significantly improving our cloud efficiency and helping us minimize unnecessary costs.

Eli Zilbershtein, Head of DevOps, Hippo

You can't tag a customer in a multi-tenant environment. Attribute™ finally shows us what each customer costs and what's driving those costs.

Omri Cohen, Director of Engineering, Platform

Attribute™'s data is truly unmatched. No other solution on the market could deliver the precise customer cost and usage profiles we needed in such a complex infrastructure. Within weeks, the data from Attribute™ transformed our understanding of cost structures, influencing key strategic decisions in pricing, renegotiations, and market positioning.

Jonathan Langer, COO, Claroty

Attribute™ simplified tracking customer costs in our multi-tenant environments. Customer cost measurement is now clear and standardized, and finance gets the business context they need. Integration was quick and required no changes.

Kfir Lippmann, CFO, Salt Security

Attribute™ translates complex cloud bills into actionable, business-centric insights that empower our engineering teams to take true ownership of their costs.

Balamurugan Mohandossgandhi, Head of IT and Infrastructure, PropertyGuru

This has let us get a better idea of what our cost of goods sold really is. It's not every day you come across something that delivers value as quickly as yours did for us. I was seeing useful insights inside the POC, and we had only deployed it to a couple of real clusters.

Jason Moore, Principal DevOps Engineer, Accrete AI

Eliminating the need to tag thousands of resources has freed up my team and we've invested our efforts in enhancing our platform significantly.

Ziv Sivan, VP of Engineering

PerfectScale by DoiT has become an important part of how we optimize Kubernetes at scale at OneFootball. It gives our platform team the visibility, automation, resiliency insights, and confidence we need to balance cost efficiency with production readiness, especially as we prepare for major global football moments like the 2026 FIFA World Cup.

Andrea Benfatto, Platform/Cloud Runtime Engineering Manager

Cloudflow's new RDS End of Life alerts have allowed us to be more proactive on keeping our database instances up-to-date. The new solution gives us internal visibility ahead of time so that we can prepare for upgrades, instead of having to upgrade under pressure while incurring extended support costs.

Jon Fairbanks, Site Reliability Engineering Manager

PerfectScale cut 40% off our total EKS spend, and the automations handle what used to take our team 20 hours a month. Now we spend that time on reliability and performance instead of chasing cost metrics.

Caio Cristo, Director of Infrastructure/SRE

What I really like about DoiT's approach is that you're very hands-on and proactive. Satyam would ping me a few times a sprint, letting me know about the most current features, checking in on how things are going. When we are going through a peak time, that proactiveness makes a real difference. Satyam always comes through whenever we need support and helps us leverage the right experts to get us where we need to be.

Chiamaka Ibeme, Engineering Manager, Platform

SELECT has made important cost data readily accessible. I will often pull it up during engineering design reviews so we can quickly evaluate cost impact and projections and factor that into our design decisions.

Douglas Zickuhr, Senior Data Platform Engineer at Personio

Your cloud bill shouldn't be a mystery

Let us show you what ships this week.

Book a demo