Real work. Real outcomes.

Two of the client's flagship products — Build 3D and Plans — were running on Kubernetes clusters with inconsistent, manually maintained Datadog tags. As traffic scaled, the monitoring layer couldn't reliably correlate alerts to services, environments, or deployment versions. Engineers were spending the first 20 minutes of every incident just figuring out which environment was on fire and which version was running — before any actual debugging could begin. Meanwhile, a weekly “tag cleanup” task was quietly consuming ~3 hours of senior SRE time that should have been spent on reliability work.

• Audited the full Datadog tag taxonomy across both products — identified 14 conflicting tag conventions inherited from separate teams.
• Defined a unified tagging standard (env, service, version, team, product) aligned to existing Kubernetes labels — zero new concepts for the engineering team to learn.
• Built an automated tag-injection pipeline using Kubernetes admission webhooks — new deployments tagged correctly at the pod level, no manual step required.
• Updated all Datadog monitors, dashboards, and SLOs to the new taxonomy in a single migration window.
• Wired Datadog deployment tracking to the CI/CD pipeline — every production push creates a traceable deployment event automatically.