Client stories

Evidence from assessments and retainers — specific about the work, not polished into marketplace scores.

“They spent the first morning on our rollback runbooks before touching any charts. The frequency numbers finally matched what the night shift actually felt.”

— Min-jae Park, platform lead, Busan retail stack · Deployment Reliability Assessment

“The assessment found we were counting hotfixes as ‘successful deploys.’ Fixing that definition was uncomfortable — and overdue.”

— Hye-rin Cho, SRE manager, Seoul fintech · Deployment Reliability Assessment

“I wanted a faster cadence; they showed our rollback rate climbed every time we compressed review windows. We slowed two weeks, then sped up with smaller batches. That reservation in their report kept us honest.”

— Dae-won Shin, engineering director, logistics platform · Release Cadence Advisory

“The pattern review made our on-call rotation change who can call a reverse. Communication still gets messy on Friday evenings, but at least the criteria sit in one place.”

— Yuna Baek, operations lead, media streaming · Rollback Pattern Review

Extended story: retail release path, Busan

A retail platform team shipped several times a week yet could not explain a string of evening rollbacks. During the Deployment Reliability Assessment we sampled twelve releases and found schema migrations bundled with storefront experiments. Frequency looked healthy; reliability after those combined ships did not.

The team split migration windows from experiment ships and rehearsed a reverse path that no longer depended on a single database specialist. Rollback rates fell over the following six weeks. They still ship often — they simply stopped treating every green pipeline as proof that users were steady.

Talk about your release path