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AGENT SKILL

replit-observability

replit-observability 是面向效率工具、开发运维的 Agent Skill,来自 jeremylongshore/claude-code-plugins-plus-skills。查看技能说明、操作步骤与使用约定,并通过原项目了解详细用法。

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

SKILL.md

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namereplit-observability
descriptionSet up comprehensive observability for Replit integrations with metrics, traces, and alerts. Use when implementing monitoring for Replit operations, setting up dashboards, or configuring alerting for Replit integration health. Trigger with phrases like "replit monitoring", "replit metrics", "replit observability", "monitor replit", "replit alerts", "replit tracing".
allowed-toolsRead, Write, Edit
version1.0.0
licenseMIT
authorJeremy Longshore <[email protected]>

Replit Observability

Overview

Set up comprehensive observability for Replit integrations.

Prerequisites

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

Metrics Collection

Key Metrics

Metric Type Description
replit_requests_total Counter Total API requests
replit_request_duration_seconds Histogram Request latency
replit_errors_total Counter Error count by type
replit_rate_limit_remaining Gauge Rate limit headroom

Prometheus Metrics

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

const registry = new Registry();

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

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

const errorCounter = new Counter({
  name: 'replit_errors_total',
  help: 'Replit 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('replit-client');

async function tracedReplitCall<T>(
  operationName: string,
  operation: () => Promise<T>
): Promise<T> {
  return tracer.startActiveSpan(`replit.${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: 'replit',
  level: process.env.LOG_LEVEL || 'info',
});

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

Alert Configuration

Prometheus AlertManager Rules

# replit_alerts.yaml
groups:
  - name: replit_alerts
    rules:
      - alert: ReplitHighErrorRate
        expr: |
          rate(replit_errors_total[5m]) /
          rate(replit_requests_total[5m]) > 0.05
        for: 5m
        labels:
          severity: warning
        annotations:
          summary: "Replit error rate > 5%"

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

      - alert: ReplitDown
        expr: up{job="replit"} == 0
        for: 1m
        labels:
          severity: critical
        annotations:
          summary: "Replit integration is down"

Dashboard

Grafana Panel Queries

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

Issue Cause Solution
Missing metrics No instrumentation Wrap client calls
Trace gaps Missing propagation Check context headers
Alert storms Wrong thresholds Tune alert rules
High cardinality Too many labels Reduce 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 replit-incident-runbook.

来源:jeremylongshore/claude-code-plugins-plus-skills · MIT 许可 · 许可原文 · MD 为来源页保存的历史版本