Use when working with Gcp Cloud Run Deep — deep Google Cloud Run analysis covering service inventory, revision management, traffic splitting, autoscaling configuration, request latency metrics, container resource limits, domain mappings, and VPC connector usage. Use for comprehensive Cloud Run optimization and health assessment.
Scanned 9/8/2026
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---
name: managing-gcp-cloud-run-deep
description: |
Use when working with Gcp Cloud Run Deep — deep Google Cloud Run analysis
covering service inventory, revision management, traffic splitting,
autoscaling configuration, request latency metrics, container resource limits,
domain mappings, and VPC connector usage. Use for comprehensive Cloud Run
optimization and health assessment.
connection_type: gcp
preload: false
---
# GCP Cloud Run Deep Management
Comprehensive analysis of Cloud Run services, revisions, traffic routing, and performance.
## Phase 1: Discovery
```bash
#!/bin/bash
PROJECT="${GOOGLE_CLOUD_PROJECT}"
echo "=== Cloud Run Services ==="
gcloud run services list --project="$PROJECT" \
--format="table(name, region, status.url, status.conditions[0].status:label=READY, metadata.annotations.'run.googleapis.com/launch-stage':label=STAGE)" \
2>/dev/null | head -20
echo ""
echo "=== Service Details ==="
for SVC in $(gcloud run services list --project="$PROJECT" --format="value(name)" 2>/dev/null); do
REGION=$(gcloud run services list --project="$PROJECT" --format="value(region)" --filter="name=${SVC}" 2>/dev/null)
gcloud run services describe "$SVC" --project="$PROJECT" --region="$REGION" --format="json" \
| jq '{name: .metadata.name, image: .spec.template.spec.containers[0].image, cpu: .spec.template.spec.containers[0].resources.limits.cpu, memory: .spec.template.spec.containers[0].resources.limits.memory, concurrency: .spec.template.spec.containerConcurrency, timeout: .spec.template.metadata.annotations["run.googleapis.com/execution-environment"], minInstances: .spec.template.metadata.annotations["autoscaling.knative.dev/minScale"], maxInstances: .spec.template.metadata.annotations["autoscaling.knative.dev/maxScale"]}' 2>/dev/null
done | head -30
echo ""
echo "=== Traffic Splitting ==="
for SVC in $(gcloud run services list --project="$PROJECT" --format="value(name)" 2>/dev/null); do
REGION=$(gcloud run services list --project="$PROJECT" --format="value(region)" --filter="name=${SVC}" 2>/dev/null)
gcloud run services describe "$SVC" --project="$PROJECT" --region="$REGION" \
--format="json" | jq ".status.traffic[] | {revision: .revisionName, percent: .percent, tag: .tag}" 2>/dev/null
done
echo ""
echo "=== Domain Mappings ==="
gcloud run domain-mappings list --project="$PROJECT" \
--format="table(name, routeName, status.conditions[0].status:label=READY)" 2>/dev/null
echo ""
echo "=== Revisions ==="
for SVC in $(gcloud run services list --project="$PROJECT" --format="value(name)" 2>/dev/null); do
REGION=$(gcloud run services list --project="$PROJECT" --format="value(region)" --filter="name=${SVC}" 2>/dev/null)
gcloud run revisions list --service="$SVC" --project="$PROJECT" --region="$REGION" \
--format="table(name, active, status.conditions[0].status:label=READY, metadata.creationTimestamp)" \
2>/dev/null | head -5
done
```
## Phase 2: Analysis
```bash
#!/bin/bash
PROJECT="${GOOGLE_CLOUD_PROJECT}"
END=$(date -u +"%Y-%m-%dT%H:%M:%SZ")
START=$(date -u -d "7 days ago" +"%Y-%m-%dT%H:%M:%SZ" 2>/dev/null || date -u -v-7d +"%Y-%m-%dT%H:%M:%SZ")
echo "=== Request Count & Latency ==="
gcloud monitoring time-series list \
--project="$PROJECT" \
--filter='metric.type="run.googleapis.com/request_count"' \
--interval-start-time="$START" --interval-end-time="$END" \
--format="table(resource.labels.service_name, metric.labels.response_code_class, points[0].value.int64Value:label=REQUESTS)" \
2>/dev/null | head -20
echo ""
echo "=== Request Latencies ==="
gcloud monitoring time-series list \
--project="$PROJECT" \
--filter='metric.type="run.googleapis.com/request_latencies"' \
--interval-start-time="$START" --interval-end-time="$END" \
--format="table(resource.labels.service_name, points[0].value.distributionValue.mean:label=AVG_MS)" \
2>/dev/null | head -20
echo ""
echo "=== Instance Count ==="
gcloud monitoring time-series list \
--project="$PROJECT" \
--filter='metric.type="run.googleapis.com/container/instance_count"' \
--interval-start-time="$START" --interval-end-time="$END" \
--format="table(resource.labels.service_name, metric.labels.state, points[0].value.int64Value:label=COUNT)" \
2>/dev/null | head -20
echo ""
echo "=== CPU & Memory Utilization ==="
gcloud monitoring time-series list \
--project="$PROJECT" \
--filter='metric.type="run.googleapis.com/container/cpu/utilizations"' \
--interval-start-time="$START" --interval-end-time="$END" \
--format="table(resource.labels.service_name, points[0].value.distributionValue.mean:label=CPU_UTIL)" \
2>/dev/null | head -20
echo ""
echo "=== VPC Connectors ==="
for SVC in $(gcloud run services list --project="$PROJECT" --format="value(name)" 2>/dev/null); do
REGION=$(gcloud run services list --project="$PROJECT" --format="value(region)" --filter="name=${SVC}" 2>/dev/null)
VPC=$(gcloud run services describe "$SVC" --project="$PROJECT" --region="$REGION" --format="json" \
| jq -r '.spec.template.metadata.annotations["run.googleapis.com/vpc-access-connector"] // "none"' 2>/dev/null)
echo "${SVC}: ${VPC}"
done
```
## Output Format
```
GCP CLOUD RUN DEEP ANALYSIS
==============================
Service Region CPU Memory Min/Max Requests P50-ms P99-ms
──────────────────────────────────────────────────────────────────────────────────
order-api us-central1 1 512Mi 1/10 125000 45 230
auth-service us-central1 2 1Gi 2/50 890000 12 85
batch-worker us-east1 1 2Gi 0/5 8900 2400 5000
Traffic: 3 services with 100% on latest | 1 canary at 10%
VPC Connectors: 2/3 services connected | Domain Mappings: 2
```
## Safety Rules
- **Read-only**: Only use `gcloud run services list`, `describe`, `revisions list`, and monitoring queries
- **Never deploy, update traffic**, or delete services without confirmation
- **Secrets**: Never output secret environment variable values
- **Quota**: Cloud Monitoring API quota is 6000 read requests per minute
## Anti-Hallucination Rules
1. **NEVER assume resource names** — always discover via CLI/API in Phase 1 before referencing in Phase 2.
2. **NEVER fabricate metric names or dimensions** — verify against the service documentation or `--help` output.
3. **NEVER mix CLI commands between service versions** — confirm which version/API you are targeting.
4. **ALWAYS use the discovery → verify → analyze chain** — every resource referenced must have been discovered first.
5. **ALWAYS handle empty results gracefully** — an empty response is valid data, not an error to retry.
## Counter-Rationalizations
| Shortcut | Counter | Why |
|----------|---------|-----|
| "I'll skip discovery and check known resources" | Always run Phase 1 discovery first | Resource names change, new resources appear — assumed names cause errors |
| "The user only asked for a quick check" | Follow the full discovery → analysis flow | Quick checks miss critical issues; structured analysis catches silent failures |
| "Default configuration is probably fine" | Audit configuration explicitly | Defaults often leave logging, security, and optimization features disabled |
| "Metrics aren't needed for this" | Always check relevant metrics when available | API/CLI responses show current state; metrics reveal trends and intermittent issues |
| "I don't have access to that" | Try the command and report the actual error | Assumed permission failures prevent useful investigation; actual errors are informative |
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