A small practice for noisy streams

Origin

The practice grew out of repeated late-night lag incidents in event-driven systems serving Korean retail and logistics teams. The same questions kept returning: is this catch-up or a stall, which failure signature are we seeing, and what should we fix first?

We formed Automated Data Feed in Busan to answer those questions with observation windows, written findings, and remediation lists that name owners—not with another monitoring product.

How we work

We start from the streams that hurt customers when they stall. We read metrics beside incident notes, talk with the people who were paged, and refuse to rank a fix we cannot explain in plain language.

Engagements stay finite. When the assessment or review ends, you keep the report and the next actions. Ongoing checkups are optional and scheduled only when they still earn their place.

Values

• Specific evidence over ambient dashboards
• Failure names that on-call staff can reuse at 2 a.m.
• Remediation sequences sized for the team you actually have
• Honest limits about what an external review cannot change