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Once you can debug individual transactions, Level 4 lets you add custom business insights.
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| Course | Description | Status |
|---|---|---|
| Distributed tracing | Span analysis, trace-to-logs, bottleneck detection | Future |
| Traces drilldown | Explore traces without writing TraceQL | Future |
| Continuous profiling | Flame graphs, CPU/memory optimization | Future |
| Frontend observability | Core Web Vitals, session replay, RUM | Future |
| AI/LLM observability | Token tracking, prompt analysis, GPU monitoring | Future |
| Course | Description | Status |
|---|---|---|
| Transaction alerting | Latency alerts, trace-based investigation | Future |
| Transaction SLOs | End-to-end latency targets | Future |
| Trace dashboards | Span breakdowns, latency distributions | Future |
| Incident response | OnCall, Incident, Sift AI | Future |
Once you can debug individual transactions, Level 4 lets you add custom business insights.
Level 3 has a lot of surface area, so there are several deep dive courses to choose from.
For the core capabilities, we’re building courses on Distributed Tracing, Traces Drilldown (which lets you explore traces without writing query language), Continuous Profiling, Frontend Observability, and AI/LLM Observability.
On the operational side, there’s Transaction Alerting, Transaction SLOs, and Trace Dashboards.
Check the documentation links on this slide if you want to start exploring these features now. The docs are comprehensive.
Once you can confidently debug individual transactions and understand exactly where time is being spent, you’re ready for the final level: adding custom insights through manual instrumentation.