Xray · see through your fleet
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updated 3m ago

Services 13

Per-service rollup over the last 6h. Click a service for its endpoint-level X-ray.

Neo4j fan-out per request
Calls (log) × queries/request — up-and-right is an N+1 suspect (amber ≥3, red ≥10 q/req)
22100calls (log)q/reqdocsvc · calls 12 · q/req 1.5docsvc
Service API calls Err % Avg latency Neo4j queries Background Neo4j / req Write % Avg Neo4j
notifsvc 23 0.0% 0 0 0.0
docsvc 12 0.0% 681 ms 18 0 0.0% 1.5 0.0% 117 ms
onboardingsvc 9 0.0% <1 ms 0 0 0.0
advpsvc 0 658 658 100.0% 0.0% 2 ms
dashrsvc 0 15 15 100.0% 100.0% 10 ms
docproc 0 797 797 100.0% 0.0% 121 ms
execsvc 0 1 1 100.0% 0.0% 134 ms
finsvc 0 59 59 100.0% 0.0% <1 ms
regsvc 0 60 60 100.0% 0.0% 285 ms
schedsvc 0 8 8 100.0% 0.0% 21 ms
tusker 0 257 257 100.0% 12.1% 13.07 s
virtual-assistant 0 117,595 117,231 99.7% 0.0% <1 ms
workplansvc 0 4,439 4,439 100.0% 5.0% 1 ms

Neo4j queries = total in-window. Background = those with no matching HTTP request (pubsub / cron / worker paths) — e.g. a service with 8 API calls but thousands of queries is doing background work. Neo4j / req = foreground queries (total − background) ÷ API calls — the true per-request fan-out (high = possible N+1), no longer skewed by background load.