ramp-observability

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

claude-code
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ramp-pack Plugin
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ramp-pack

Claude Code skill pack for Ramp (24 skills)

saas packs v1.0.0
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Installation

This skill is included in the ramp-pack plugin:

/plugin install ramp-pack@claude-code-plugins-plus

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Instructions

Ramp Observability

Overview

Set up comprehensive observability for Ramp integrations.

Prerequisites

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

Metrics Collection

Key Metrics

Metric Type Description
ramprequeststotal Counter Total API requests
ramprequestduration_seconds Histogram Request latency
ramperrorstotal Counter Error count by type
rampratelimit_remaining Gauge Rate limit headroom

Prometheus Metrics


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

const registry = new Registry();

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

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

const errorCounter = new Counter({
  name: 'ramp_errors_total',
  help: 'Ramp 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('ramp-client');

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

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

Alert Configuration

Prometheus AlertManager Rules


# ramp_alerts.yaml
groups:
  - name: ramp_alerts
    rules:
      - alert: RampHighErrorRate
        expr: |
          rate(ramp_errors_total[5m]) /
          rate(ramp_requests_total[5m]) > 0.05
        for: 5m
        labels:
          severity: warning
        annotations:
          summary: "Ramp error rate > 5%"

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

      - alert: RampDown
        expr: up{job="ramp"} == 0
        for: 1m
        labels:
          severity: critical
        annotations:
          summary: "Ramp integration is down"

Dashboard

Grafana Panel Queries


{
  "panels": [
    {
      "title": "Ramp Request Rate",
      "targets": [{
        "expr": "rate(ramp_requests_total[5m])"
      }]
    },
    {
      "title": "Ramp Latency P50/P95/P99",
      "targets": [{
        "expr": "histogram_quantile(0.5, rate(ramp_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 ramp-incident-runbook.

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