cliffracer-metrics

Dispatch timing and counting for cliffracer services, plus batching and connection-pooling helpers.

from cliffracer import CliffracerService, ServiceConfig
from cliffracer_metrics import MetricsExtension

class OrderService(CliffracerService):
    metrics = MetricsExtension()

MetricsExtension records a count, an error count and a latency window per dispatch kind, and contributes them to /health under the attribute name you declared it as. Declared as metrics above, its numbers appear under "metrics".

A refusal is counted separately from a handler error, so a service refusing unauthenticated callers reports that as policy rather than as a thousand crashes.

A pool of connections

from cliffracer import CliffracerService, rpc
from cliffracer_metrics import PoolExtension

class Ingest(CliffracerService):
    pool = PoolExtension(max_connections=8)

    @rpc
    async def bulk(self, subject: str) -> dict[str, bool]:
        reply = await self.pool.request(subject, b"{}")
        return {"ok": True}

PoolExtension builds an OptimizedNATSConnection from the service's own config, credentials included, connects it when the service starts, closes it when the service stops, and reports its connection count under /health.

The pool is a second set of connections the handler reaches for. The service's own connection carries call_rpc, publish_event and every subscription, so what goes through the pool is what a handler sends through it.

You construct BatchProcessor and PerformanceMetrics yourself. Each has a package test that builds and exercises it, which is the working example of how to use it.

Installed from PyPI, versioned in lockstep with cliffracer.