“During the workload assessment they insisted on a quiet baseline week before our sale. That felt slow. The report later proved our evening concurrency pattern was the real limiter—not the midday CPU charts we had been watching.”
Client stories
What teams said afterward
Evidence from application analytics work—specific engagements, constraints, and outcomes rather than star ratings.
“The scaling readiness review before our spring campaign was blunt: two policies would thrash under the traffic mix we expected. We fixed one, accepted risk on the other, and the campaign held. I wish the write-up had been shorter, but the go/caution list was usable the same day.”
“Coverage audit found our traces stopped at the edge service while the queue consumers ran blind. Not glamorous work. It stopped a class of overnight pages we had been blaming on ‘random cloud weather.’”
“After the November outage, the incident debrief reconstructed when autoscaling finally caught up—twelve minutes after customers already left. We still debate ownership of the follow-ups, but the timeline itself is no longer contested.”
Project note: pre-launch readiness
A Seoul product company booked a Scaling Readiness Review three weeks before opening a new region. CloudAuto Link compared autoscaling thresholds against a rehearsal load that mixed reads with write bursts. Two alert routes were shortened; one capacity buffer was raised. Launch day remained busy, but the team spent it watching the signals we had agreed—not inventing new graphs mid-event.
Project note: post-peak assessment
After a festival traffic spike, a retail client commissioned a Workload Behavior Assessment. Observation covered the spike week plus a normal week. Findings showed cache miss storms on a catalog service that CPU-based scaling never saw. The walkthrough handed developers a short instrumentation list and a revised question for the next festival: measure catalog latency by cache state, not only host utilization.