Observe · ServiceIQ APM
Every service, every call, every slow span.
ServiceIQ is OpenTelemetry-native application performance monitoring: golden signals and Apdex for every service, a live map of who calls whom, and distributed traces that point straight at the slow span. Synthetic checks test what your users actually do.
Services
Golden signals, judged against your own normal.
Every service shows latency, throughput and error rate, with Apdex against the threshold you set. Baselines are learned per service, so an alert compares against what is normal for this hour of the week — not a fixed line.
- Latency percentiles computed at read time from histograms
- Apdex against your own threshold
- Baselines per service, per hour of the week
- Health and Hosts views, APM Dashboards and Logs
Distributed tracing
Spot the slow span instantly.
Open a trace and see it as a Waterfall timeline, a Flame graph, a list of Spans or a Services view. Drill down from a service to its transactions through a latency heatmap, then into the individual traces behind each one.
- Waterfall, Flame graph, Spans and Services views
- Transactions: latency heatmap → per-transaction KPIs and traces
- Dependencies as a list and a map, DB Operations, Errors and Alerts
Synthetic Monitoring
Test what users actually do — before they do.
Schedule HTTP and API checks, or script multi-step browser journeys that navigate, click, type and select the way a customer would. Every run lands in a success and failure history.
- Scheduled HTTP and API checks
- Scripted browser journeys: navigate, click, type, select
- Success and failure history
Capabilities
Everything in Application performance
The complete list, as it exists in the product today.
ServiceIQ — Application Performance Monitoring
Services
- Services list with health, golden signals (latency, throughput, error rate) and Apdex against your own threshold
- Latency percentiles computed at read time from histograms
- Topology map of service-to-service calls
- Health and Hosts views; APM Dashboards and Logs
Service drill-down
- Overview: latency, throughput, errors, response codes, running hosts, top transactions, dependencies, top DB queries, callers and callees
- Metrics: baseline charts and resource metrics
- Transactions: a latency heatmap leading to per-transaction detail with its own KPIs and traces
- Dependencies as a list and a map
- DB Operations, Traces, Errors and Alerts
Distributed tracing
- Trace detail with Waterfall timeline, Flame graph, Spans and Services views
- Spot the slow span instantly
Baselines
- Baselines learned per service, so alerts compare against “normal for this hour of the week”
Synthetic Monitoring
Checks
- Scheduled HTTP and API checks
- Scripted multi-step browser journeys — navigate, click, type, select
- Success and failure history for every check
Works with AI Core
Application signals feed AI Core.
Saturated services are one of the signals AI Core correlates with what the network and infrastructure are doing, so a slow checkout and the congested link behind it surface as one situation.
How AI Core worksFrom Application performance
- Saturated services
- Golden-signal deviations from the learned baseline
Get started
See every signal in one place.
Start with one site and one probe. Add modules as you go — the AI Core gets more useful with every source you connect.
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