FabricFabricHarness
Operating

Operational SLOs

Stable runtime metrics, SLO evaluation, alerts, dashboards, and cross-target conformance.

Fabric Harness defines low-cardinality metrics for the operational signals that matter across Node, Temporal, Cloudflare, and Databricks Apps:

MetricMeaning
fabric_harness_request_latency_msEnd-to-end HTTP or application request latency
fabric_harness_submission_duration_msAdmission-to-settlement duration
fabric_harness_queue_age_msAdmission-to-worker-start delay
fabric_harness_errors_totalFailed requests, submissions, events, and recovery attempts
fabric_harness_approval_wait_msApproval request-to-terminal-decision delay
fabric_harness_recovery_duration_msWorker or persistence recovery duration
fabric_harness_cost_usd_totalAttributed model and serving cost

Collect and export

import { createOperationalMetricsCollector } from '@fabric-harness/sdk';

const metrics = createOperationalMetricsCollector();

const config = {
  onEvent: (event) => metrics.recordEvent(event),
  submissionTelemetry: metrics.submissionSink,
};

application.get('/metrics', () => new Response(metrics.openMetrics(), {
  headers: { 'content-type': 'application/openmetrics-text; version=1.0.0' },
}));

Call recordRequest(durationMs, outcome) at the HTTP or application boundary and recordRecovery(durationMs, recovered) around recovery drills. The collector keeps bounded samples and exports count, sum, p50, p95, and p99.

Evaluate a service objective

import { evaluateOperationalSlos } from '@fabric-harness/sdk';

const evaluation = evaluateOperationalSlos(metrics.snapshot(), {
  requestLatencyP95Ms: 2_000,
  queueAgeP95Ms: 5_000,
  errorRateMax: 0.01,
  approvalWaitP95Ms: 4 * 60 * 60_000,
  recoveryP95Ms: 60_000,
  costUsdMax: 1_000,
});

The runnable examples/operational-slos workspace includes an importable Grafana dashboard and Prometheus alert rules for every metric above. Adjust the reference thresholds to the user journey and recovery tier of each deployment.

Deployment conformance

runDeploymentConformance() is the same black-box client suite for every deployment target. It checks health, dependency readiness, asynchronous finite job settlement and event offsets, plus persistent-agent submission settlement and conversation offsets.

import { assertDeploymentConformance } from '@fabric-harness/client';

await assertDeploymentConformance({
  target: 'databricks-app',
  baseUrl: process.env.DATABRICKS_APP_URL!,
  headers: { authorization: `Bearer ${process.env.APP_TOKEN}` },
  job: { name: 'analyst', input: { question: 'SELECT 1' } },
});

The live workflow runs this contract against a local Node host, a real Temporal cluster behind the Node HTTP API, local and deployed Cloudflare Workers, and the reference Databricks App. Each run writes a redacted JSON evidence artifact.