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jeremylongshore

instantly-observability

by jeremylongshore

Hundreds of Claude Code plugins with embedded AI skills. Learn via interactive Jupyter tutorials.

1,042🍴 135📅 Jan 23, 2026

SKILL.md


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

Instantly Observability

Overview

Set up comprehensive observability for Instantly integrations.

Prerequisites

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

Metrics Collection

Key Metrics

MetricTypeDescription
instantly_requests_totalCounterTotal API requests
instantly_request_duration_secondsHistogramRequest latency
instantly_errors_totalCounterError count by type
instantly_rate_limit_remainingGaugeRate limit headroom

Prometheus Metrics

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

const registry = new Registry();

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

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

const errorCounter = new Counter({
  name: 'instantly_errors_total',
  help: 'Instantly 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('instantly-client');

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

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

Alert Configuration

Prometheus AlertManager Rules

# instantly_alerts.yaml
groups:
  - name: instantly_alerts
    rules:
      - alert: InstantlyHighErrorRate
        expr: |
          rate(instantly_errors_total[5m]) /
          rate(instantly_requests_total[5m]) > 0.05
        for: 5m
        labels:
          severity: warning
        annotations:
          summary: "Instantly error rate > 5%"

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

      - alert: InstantlyDown
        expr: up{job="instantly"} == 0
        for: 1m
        labels:
          severity: critical
        annotations:
          summary: "Instantly integration is down"

Dashboard

Grafana Panel Queries

{
  "panels": [
    {
      "title": "Instantly Request Rate",
      "targets": [{
        "expr": "rate(instantly_requests_total[5m])"
      }]
    },
    {
      "title": "Instantly Latency P50/P95/P99",
      "targets": [{
        "expr": "histogram_quantile(0.5, rate(instantly_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 instantly-incident-runbook.

Score

Total Score

85/100

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