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생산성 및 협업 · SKILL.md

perplexity-observability

perplexity-observability

Set up comprehensive observability for Perplexity integrations with metrics, traces, and alerts. Use when implementing monitoring for Perplexity operations, setting up dashboards, or configuring alerting for Perplexity integration health. Trigger with phrases like "perplexity monitoring", "perplexity metrics", "perplexity observability", "monitor perplexity…

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Skill 문서

GitHub

name: perplexity-observability description: | Set up comprehensive observability for Perplexity integrations with metrics, traces, and alerts. Use when implementing monitoring for Perplexity operations, setting up dashboards, or configuring alerting for Perplexity integration health. Trigger with phrases like "perplexity monitoring", "perplexity metrics", "perplexity observability", "monitor perplexity", "perplexity alerts", "perplexity tracing". allowed-tools: Read, Write, Edit version: 1.0.0 license: MIT author: Jeremy Longshore jeremy@intentsolutions.io

Perplexity Observability

Overview

Set up comprehensive observability for Perplexity integrations.

Prerequisites

  • Prometheus or compatible metrics backend
  • OpenTelemetry SDK installed
  • Grafana or similar dashboarding tool
  • AlertManager configured

Metrics Collection

Key Metrics

MetricTypeDescription
perplexity_requests_totalCounterTotal API requests
perplexity_request_duration_secondsHistogramRequest latency
perplexity_errors_totalCounterError count by type
perplexity_rate_limit_remainingGaugeRate limit headroom

Prometheus Metrics

import { Registry, Counter, Histogram, Gauge } from 'prom-client';

const registry = new Registry();

const requestCounter = new Counter({
  name: 'perplexity_requests_total',
  help: 'Total Perplexity API requests',
  labelNames: ['method', 'status'],
  registers: [registry],
});

const requestDuration = new Histogram({
  name: 'perplexity_request_duration_seconds',
  help: 'Perplexity request duration',
  labelNames: ['method'],
  buckets: [0.05, 0.1, 0.25, 0.5, 1, 2.5, 5],
  registers: [registry],
});

const errorCounter = new Counter({
  name: 'perplexity_errors_total',
  help: 'Perplexity errors by type',
  labelNames: ['error_type'],
  registers: [registry],
});

Instrumented Client

async function instrumentedRequest<T>(
  method: string,
  operation: () => Promise<T>
): Promise<T> {
  const timer = requestDuration.startTimer({ method });

  try {
    const result = await operation();
    requestCounter.inc({ method, status: 'success' });
    return result;
  } catch (error: any) {
    requestCounter.inc({ method, status: 'error' });
    errorCounter.inc({ error_type: error.code || 'unknown' });
    throw error;
  } finally {
    timer();
  }
}

Distributed Tracing

OpenTelemetry Setup

import { trace, SpanStatusCode } from '@opentelemetry/api';

const tracer = trace.getTracer('perplexity-client');

async function tracedPerplexityCall<T>(
  operationName: string,
  operation: () => Promise<T>
): Promise<T> {
  return tracer.startActiveSpan(`perplexity.${operationName}`, async (span) => {
    try {
      const result = await operation();
      span.setStatus({ code: SpanStatusCode.OK });
      return result;
    } catch (error: any) {
      span.setStatus({ code: SpanStatusCode.ERROR, message: error.message });
      span.recordException(error);
      throw error;
    } finally {
      span.end();
    }
  });
}

Logging Strategy

Structured Logging

import pino from 'pino';

const logger = pino({
  name: 'perplexity',
  level: process.env.LOG_LEVEL || 'info',
});

function logPerplexityOperation(
  operation: string,
  data: Record<string, any>,
  duration: number
) {
  logger.info({
    service: 'perplexity',
    operation,
    duration_ms: duration,
    ...data,
  });
}

Alert Configuration

Prometheus AlertManager Rules

# perplexity_alerts.yaml
groups:
  - name: perplexity_alerts
    rules:
      - alert: PerplexityHighErrorRate
        expr: |
          rate(perplexity_errors_total[5m]) /
          rate(perplexity_requests_total[5m]) > 0.05
        for: 5m
        labels:
          severity: warning
        annotations:
          summary: "Perplexity error rate > 5%"

      - alert: PerplexityHighLatency
        expr: |
          histogram_quantile(0.95,
            rate(perplexity_request_duration_seconds_bucket[5m])
          ) > 2
        for: 5m
        labels:
          severity: warning
        annotations:
          summary: "Perplexity P95 latency > 2s"

      - alert: PerplexityDown
        expr: up{job="perplexity"} == 0
        for: 1m
        labels:
          severity: critical
        annotations:
          summary: "Perplexity integration is down"

Dashboard

Grafana Panel Queries

{
  "panels": [
    {
      "title": "Perplexity Request Rate",
      "targets": [{
        "expr": "rate(perplexity_requests_total[5m])"
      }]
    },
    {
      "title": "Perplexity Latency P50/P95/P99",
      "targets": [{
        "expr": "histogram_quantile(0.5, rate(perplexity_request_duration_seconds_bucket[5m]))"
      }]
    }
  ]
}

Instructions

Step 1: Set Up Metrics Collection

Implement Prometheus counters, histograms, and gauges for key operations.

Step 2: Add Distributed Tracing

Integrate OpenTelemetry for end-to-end request tracing.

Step 3: Configure Structured Logging

Set up JSON logging with consistent field names.

Step 4: Create Alert Rules

Define Prometheus alerting rules for error rates and latency.

Output

  • Metrics collection enabled
  • Distributed tracing configured
  • Structured logging implemented
  • Alert rules deployed

Error Handling

IssueCauseSolution
Missing metricsNo instrumentationWrap client calls
Trace gapsMissing propagationCheck context headers
Alert stormsWrong thresholdsTune alert rules
High cardinalityToo many labelsReduce label values

Examples

Quick Metrics Endpoint

app.get('/metrics', async (req, res) => {
  res.set('Content-Type', registry.contentType);
  res.send(await registry.metrics());
});

Resources

Next Steps

For incident response, see perplexity-incident-runbook.

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