Xray · see through your fleet
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updated 1m 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 34 0.0% 0 0 0.0
onboardingsvc 13 0.0% <1 ms 0 0 0.0
docsvc 12 0.0% 681 ms 18 0 0.0% 1.5 0.0% 117 ms
advpsvc 0 1,128 1,128 100.0% 0.0% 2 ms
dashrsvc 0 15 15 100.0% 100.0% 10 ms
docproc 0 1,376 1,376 100.0% 0.0% 124 ms
execsvc 0 1 1 100.0% 0.0% 134 ms
finsvc 0 104 104 100.0% 0.0% <1 ms
regsvc 0 104 104 100.0% 0.0% 293 ms
schedsvc 0 13 13 100.0% 0.0% 19 ms
tusker 0 442 442 100.0% 12.7% 13.10 s
virtual-assistant 0 204,864 204,500 99.8% 0.0% <1 ms
workplansvc 0 7,546 7,546 100.0% 5.1% 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.