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Signed-off-by: Pratik Mankawde <3397372+pratikmankawde@users.noreply.github.com>
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@@ -498,3 +498,74 @@
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| 9 | Document results and next steps | 1 | 0 | 8 |
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**Parallel work**: Tasks 0 and 1 can run in parallel. Tasks 2 and 5 have no dependency on each other. Tasks 6 and 7 can be done in parallel once Tasks 4 and 5 are complete.
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---
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## Next Steps (Post-POC)
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### Metrics Pipeline for Grafana Dashboards
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The current POC exports **traces only**. Grafana's Explore view can query Jaeger for individual traces, but time-series charts (latency histograms, request throughput, error rates) require a **metrics pipeline**. To enable this:
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1. **Add a `spanmetrics` connector** to the OTel Collector config that derives RED metrics (Rate, Errors, Duration) from trace spans automatically:
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```yaml
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connectors:
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spanmetrics:
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histogram:
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explicit:
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buckets: [1ms, 5ms, 10ms, 25ms, 50ms, 100ms, 250ms, 500ms, 1s, 5s]
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dimensions:
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- name: xrpl.rpc.command
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- name: xrpl.rpc.status
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exporters:
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prometheus:
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endpoint: 0.0.0.0:8889
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service:
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pipelines:
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traces:
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receivers: [otlp]
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processors: [batch]
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exporters: [debug, otlp/jaeger, spanmetrics]
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metrics:
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receivers: [spanmetrics]
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exporters: [prometheus]
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```
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2. **Add Prometheus** to the Docker Compose stack to scrape the collector's metrics endpoint.
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3. **Add Prometheus as a Grafana datasource** and build dashboards for:
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- RPC request latency (p50/p95/p99) by command
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- RPC throughput (requests/sec) by command
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- Error rate by command
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- Span duration distribution
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### Additional Instrumentation
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- **W3C `traceparent` header extraction** in `ServerHandler` to support cross-service context propagation from external callers
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- **WebSocket RPC tracing** in `ServerHandler::onWSMessage()`
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- **Transaction relay tracing** across nodes using protobuf `TraceContext` messages
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- **Consensus round and phase tracing** for validator coordination visibility
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- **Ledger close tracing** to measure close-to-validated latency
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### Production Hardening
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- **Tail-based sampling** in the OTel Collector to reduce volume while retaining error/slow traces
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- **TLS configuration** for the OTLP exporter in production deployments
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- **Resource limits** on the batch processor queue to prevent unbounded memory growth
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- **Health monitoring** for the telemetry pipeline itself (collector lag, export failures)
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### POC Lessons Learned
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Issues encountered during POC implementation that inform future work:
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| Issue | Resolution | Impact on Future Work |
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|-------|-----------|----------------------|
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| Conan lockfile rejected `opentelemetry-cpp/1.18.0` | Used `--lockfile=""` to bypass | Lockfile must be regenerated when adding new dependencies |
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| Conan package only builds OTLP HTTP exporter, not gRPC | Switched from gRPC to HTTP exporter (`localhost:4318/v1/traces`) | HTTP exporter is the default; gRPC requires custom Conan profile |
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| CMake target `opentelemetry-cpp::api` etc. don't exist in Conan package | Use umbrella target `opentelemetry-cpp::opentelemetry-cpp` | Conan targets differ from upstream CMake targets |
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| OTel Collector `logging` exporter deprecated | Renamed to `debug` exporter | Use `debug` in all collector configs going forward |
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| Macro parameter `telemetry` collided with `::xrpl::telemetry::` namespace | Renamed macro params to `_tel_obj_`, `_span_name_` | Avoid common words as macro parameter names |
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| `opentelemetry::trace::Scope` creates new context on move | Store scope as member, create once in constructor | SpanGuard move semantics need care with Scope lifecycle |
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| `TracerProviderFactory::Create` returns `unique_ptr<sdk::TracerProvider>`, not `nostd::shared_ptr` | Use `std::shared_ptr` member, wrap in `nostd::shared_ptr` for global provider | OTel SDK factory return types don't match API provider types |
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