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".
Allowed Tools
Provided by Plugin
ramp-pack
Claude Code skill pack for Ramp (24 skills)
Installation
This skill is included in the ramp-pack plugin:
/plugin install ramp-pack@claude-code-plugins-plus
Click to copy
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.