Customer Story

How Magic Patterns migrated 200k monthly jobs to Trigger.dev in one day

Alex Danilowicz

Alex Danilowicz

Co-founder, Magic Patterns

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Alex Danilowicz, co-founder of Magic Patterns, shares why they migrated their critical background jobs to Trigger.dev from their unreliable self-hosted solution. As a small team serving enterprise clients like PwC and Lendi Group, they needed reliable infrastructure that wouldn't consume their limited engineering resources.

What we're building at Magic Patterns

Unlike other AI coding assistants, we've built a platform that generates UI components that match your existing design system. Thousands of product teams use Magic Patterns to go from idea to interactive prototype in minutes, all while maintaining brand consistency.

Magic Patterns dashboard

We process hundreds of thousands of background jobs per month across two critical systems: screenshot generation for design iterations and automated credit resets for our usage-based billing platform.

The problem with our self-hosted solution

Our original self-hosted screenshot service was creating bottlenecks. The service was memory-intensive, expensive and experiencing frequent failures that impacted our core design iteration workflows. The unreliability was affecting the user experience for a critical part of our platform.

With millions of design generations happening, we needed a reliable solution that could handle this volume without the operational overhead of managing our own infrastructure.

Implementing Trigger.dev for reliable processing

Moving to Trigger for our background jobs was more reliable, cheaper, and easier.

We discovered the Puppeteer guide in Trigger’s docs and managed to deploy a reliable screenshotting background task which replaced our existing service, all in the same day. On top of that, it actually ended up saving us money.

We also migrated our credit reset processing to Trigger.dev which works perfectly.

The platform now handles our 200,000+ monthly background jobs reliably while eliminating the memory management issues and failures we experienced with our self-hosted solution.

This transition allowed us to redirect our engineering focus from infrastructure maintenance back to product development.

Results and business impact

Since implementing Trigger.dev, we've achieved better reliability at a lower cost. The move eliminated our infrastructure maintenance overhead while improving job processing consistency.

This change has enabled us to scale our background job processing without expanding our operations capacity. We can now grow our platform without proportionally increasing infrastructure management complexity, which is a big win for us.

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