oraclecloud-observability
Set up comprehensive observability for Oracle Cloud integrations with metrics, traces, and alerts. Use when implementing monitoring for Oracle Cloud operations, setting up dashboards, or configuring alerting for Oracle Cloud integration health. Trigger with phrases like "oraclecloud monitoring", "oraclecloud metrics", "oraclecloud observability", "monitor oraclecloud", "oraclecloud alerts", "oraclecloud tracing".
Allowed Tools
Provided by Plugin
oraclecloud-pack
Claude Code skill pack for Oracle Cloud (24 skills)
Installation
This skill is included in the oraclecloud-pack plugin:
/plugin install oraclecloud-pack@claude-code-plugins-plus
Click to copy
Instructions
Oracle Cloud Observability
Overview
Set up comprehensive observability for Oracle Cloud integrations.
Prerequisites
- Prometheus or compatible metrics backend
- OpenTelemetry SDK installed
- Grafana or similar dashboarding tool
- AlertManager configured
Metrics Collection
Key Metrics
| Metric | Type | Description |
|---|---|---|
oraclecloudrequeststotal |
Counter | Total API requests |
oraclecloudrequestduration_seconds |
Histogram | Request latency |
oracleclouderrorstotal |
Counter | Error count by type |
oraclecloudratelimit_remaining |
Gauge | Rate limit headroom |
Prometheus Metrics
import { Registry, Counter, Histogram, Gauge } from 'prom-client';
const registry = new Registry();
const requestCounter = new Counter({
name: 'oraclecloud_requests_total',
help: 'Total Oracle Cloud API requests',
labelNames: ['method', 'status'],
registers: [registry],
});
const requestDuration = new Histogram({
name: 'oraclecloud_request_duration_seconds',
help: 'Oracle Cloud request duration',
labelNames: ['method'],
buckets: [0.05, 0.1, 0.25, 0.5, 1, 2.5, 5],
registers: [registry],
});
const errorCounter = new Counter({
name: 'oraclecloud_errors_total',
help: 'Oracle Cloud 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('oraclecloud-client');
async function tracedOracle CloudCall<T>(
operationName: string,
operation: () => Promise<T>
): Promise<T> {
return tracer.startActiveSpan(`oraclecloud.${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: 'oraclecloud',
level: process.env.LOG_LEVEL || 'info',
});
function logOracle CloudOperation(
operation: string,
data: Record<string, any>,
duration: number
) {
logger.info({
service: 'oraclecloud',
operation,
duration_ms: duration,
...data,
});
}
Alert Configuration
Prometheus AlertManager Rules
# oraclecloud_alerts.yaml
groups:
- name: oraclecloud_alerts
rules:
- alert: Oracle CloudHighErrorRate
expr: |
rate(oraclecloud_errors_total[5m]) /
rate(oraclecloud_requests_total[5m]) > 0.05
for: 5m
labels:
severity: warning
annotations:
summary: "Oracle Cloud error rate > 5%"
- alert: Oracle CloudHighLatency
expr: |
histogram_quantile(0.95,
rate(oraclecloud_request_duration_seconds_bucket[5m])
) > 2
for: 5m
labels:
severity: warning
annotations:
summary: "Oracle Cloud P95 latency > 2s"
- alert: Oracle CloudDown
expr: up{job="oraclecloud"} == 0
for: 1m
labels:
severity: critical
annotations:
summary: "Oracle Cloud integration is down"
Dashboard
Grafana Panel Queries
{
"panels": [
{
"title": "Oracle Cloud Request Rate",
"targets": [{
"expr": "rate(oraclecloud_requests_total[5m])"
}]
},
{
"title": "Oracle Cloud Latency P50/P95/P99",
"targets": [{
"expr": "histogram_quantile(0.5, rate(oraclecloud_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 oraclecloud-incident-runbook.