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Diagnostics & health checks

Visibility is critical when you run RPC Dart in production. The library ships with health reporting, active ping support, and a configurable logging system to help you troubleshoot issues without redeploying instrumentation.

Endpoint health snapshots

RpcCallerEndpoint.health() and RpcResponderEndpoint.health() return RpcEndpointHealth, a composite structure that includes:

  • endpointStatus – overall status of the endpoint lifecycle (active, degraded, closed, etc.).
  • dependencies – map of component names (usually transports) to their RpcHealthStatus.
  • transportStatus – convenience getter exposing the primary transport.
  • timestamp – when the snapshot was generated.
final report = await callerEndpoint.health();
if (!report.isHealthy) {
  final transport = report.transportStatus;
  logger.warning('Caller degraded: ${transport?.message}', data: transport?.details);
}

Call reconnect() to delegate recovery to the transport. Transports that support automatic reconnection return RpcHealthStatus.reconnecting until the link is stable again.

Active ping between endpoints

RpcCallerEndpoint.ping() performs a round-trip check using the built-in system service _rpc.System/Ping.

final result = await callerEndpoint.ping(timeout: const Duration(seconds: 1));
print('RTT: ${result.roundTrip.inMilliseconds} ms');
print('Responder: ${result.responderDebugLabel}');

The result includes:

  • roundTrip – measured latency.
  • responderTimestamp – when the responder processed the ping.
  • responderDebugLabel and responderTransportType – diagnostic headers supplied by the responder endpoint.
  • responseHeaders – raw metadata for custom analysis.

Ping uses the same transport pipeline as regular calls, so you can detect routing issues, TLS problems, or degraded links in real time.

Logging with RpcLogger

RpcLogger is a pluggable logging facade with structured metadata support. Each endpoint exposes a logger and you can create child loggers for subcomponents.

final logger = RpcLogger('BillingService');
logger.info('Responder started', data: responder.collectEndpointMetrics());

Customise logging globally:

RpcLogger.setDefaultMinLogLevel(RpcLoggerLevel.debug);
RpcLogger.setLoggerFactory((name, {colors, label, context}) {
  return MyJsonLogger(name, label: label, context: context);
});

Per-message calls accept contextual data, trace IDs, and request IDs so you can ship logs to observability pipelines without losing correlation.

Colour-coding and formatting

Use RpcLoggerColors to differentiate client and server logs in the terminal:

final callerLogger = RpcLogger(
  'CheckoutCaller',
  colors: const RpcLoggerColors.bright(),
);
callerLogger.debug('Prepared context', data: context.headers);

Formatters and filters let you integrate with any logging backend. Implement IRpcLoggerFormatter to change the output structure or IRpcLoggerFilter to suppress noisy categories.

Transport diagnostics

Every IRpcTransport implements health() and reconnect(), so you can gather per-transport metrics even when multiple transports are routed together via RpcTransportRouter. Health details expose flags such as supportsZeroCopy, activeStreams, and isClosed—perfect for exporting to Prometheus or custom metrics collectors.

Combine these tools to build dashboards, trigger alerts, and keep latency under control as your system grows.