Evolve Edits · case study

A decade-old, revenue-critical platform was modernized while the business kept operating: 90% fewer downtime incidents and 80% lower infrastructure cost.

A photo post-production company’s decade-old client portal funneled terabytes a month through a single on-premise machine. We rebuilt it as a cloud platform and released it by canary rollout, no big-bang cutover.

downtime · per quarter
12 incidents
down from 125, a 90% drop
Incidents collapsed once the revenue-critical upload flow stopped depending on a single on-premise machine.
Same quarter, a year apart, and the baseline quarter is the one the new platform shipped in; figures as recorded at the time.
upload throughput
~30 MB/s uncapped
Uploads ran through one machine, capped and shared across every client. Direct-to-object-storage uploads let each client upload in parallel at their own bandwidth, concurrently.
Shared on-premise throughput → direct-to-object-storage (DigitalOcean Spaces); figures as recorded at the time.
infrastructure cost · per month
$1,700 $300 −80%
Provisioned storage priced for peak was replaced with object storage; costs fell while the platform stored more data for longer.
AWS provisioned storage → DigitalOcean object storage (Spaces); monthly figures as recorded at the time.

Evolve Edits’ decade-old WordPress client portal moved terabytes of photos a month through a single Mac Mini at company HQ. We rebuilt it as a cloud platform on a fixed price and released it by canary rollout while the business kept operating. Downtime incidents fell 90%; infrastructure cost fell 80%.

The Situation

Evolve Edits is a post-production company for photography: photographers worldwide send their photos in for editing, with software sold as part of the service. Their client portal had grown for over a decade inside a WordPress marketing site fueled by outdated plugins. Files uploaded by clients went directly to a Mac Mini at company HQ, which suffered frequent downtime and kept running out of storage while the business moved terabytes per month. Uploads were throttled by one machine’s network throughput and disk write speed; file transfers ran over FTP with no alerts, synchronization, or automation, though international clients needed 24-hour self-service. And the AWS storage that backed it was provisioned for peak and paid for always.

What We Did

Consulting first: we assessed the existing solution, identified the improvement areas, and presented the project plan. Then a fixed-price rebuild, delivered over roughly nine months. We built a React + Material UI client portal, a Django backend, and a FastAPI file-transfer microservice. The decision that mattered most was architectural: direct-to-object-storage uploads, which removed the single-instance bottleneck entirely instead of buying a bigger instance. We migrated from AWS to DigitalOcean, replacing provisioned storage with object storage, integrated two-way with Podio via webhooks on task changes, exposed data to Looker Studio and automation platforms, and wired Authorize.net payments. Release was a canary rollout, gradual exposure to a small subset of users, because the portal is a revenue-critical flow and a big-bang cutover would have bet the entire client base on day one. That made the release slower than it could have been, deliberately.

What Moved

Downtime incidents fell from 125 to 12 per quarter, a −90% change, after the on-premise dependency was removed. The comparison is the same quarter a year apart, the baseline being the quarter the new platform shipped in, and both figures are as recorded at the time, not products of the standardized definitions our current proof loop uses. Infrastructure cost fell from $1,700 to $300 per month, −80%, while the platform stored more data for longer. Clients now upload in parallel at their own bandwidth and reported the difference unprompted; we record that as a qualitative observation, not a number. The human element left the transfer pipeline: Podio integration and automated workflows replaced manual FTP handling.

Where It Went

After launch the engagement transitioned to ongoing maintenance and monitoring, with our PM and tech lead working directly with their production manager and in-house technical role.

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