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gcp-cloud-run

Use when working with Gcp Cloud Run — google Cloud Run service management, revision traffic splitting, scaling configuration, concurrency tuning, and container diagnostics via gcloud CLI.

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연동 도구Google Cloud
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Cloud Run Skill

Manage and analyze Google Cloud Run services using gcloud run commands.

Discovery-First Rule

ALWAYS discover before acting. Never assume service names, regions, or revision names.

# Discover services
gcloud run services list --format=json \
  | jq '[.[] | {name: .metadata.name, region: .metadata.labels."cloud.googleapis.com/location", url: .status.url, ready: .status.conditions[] | select(.type=="Ready") | .status}]'

Parallel Execution Requirement

ALL independent operations MUST run in parallel using background jobs (&) and wait.

for svc in $(gcloud run services list --format="value(metadata.name,metadata.labels.cloud\\.googleapis\\.com/location)" | tr '\t' ','); do
  {
    name=$(echo "$svc" | cut -d',' -f1)
    region=$(echo "$svc" | cut -d',' -f2)
    gcloud run services describe "$name" --region="$region" --format=json
  } &
done
wait

Helper Functions

# Get service details
get_service_details() {
  local name="$1" region="$2"
  gcloud run services describe "$name" --region="$region" --format=json \
    | jq '{name: .metadata.name, url: .status.url, latestRevision: .status.latestReadyRevisionName, traffic: .status.traffic, template: {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.spec.timeoutSeconds, scaling: {minScale: .spec.template.metadata.annotations."autoscaling.knative.dev/minScale", maxScale: .spec.template.metadata.annotations."autoscaling.knative.dev/maxScale"}}}'
}

# List revisions
list_revisions() {
  local name="$1" region="$2"
  gcloud run revisions list --service="$name" --region="$region" --format=json \
    | jq '[.[] | {name: .metadata.name, ready: (.status.conditions[] | select(.type=="Ready") | .status), created: .metadata.creationTimestamp, image: .spec.containers[0].image}]'
}

# Get service logs
get_service_logs() {
  local name="$1" region="$2" limit="${3:-50}"
  gcloud logging read "resource.type=\"cloud_run_revision\" AND resource.labels.service_name=\"$name\" AND resource.labels.location=\"$region\"" --limit="$limit" --format=json
}

# Get traffic split
get_traffic() {
  local name="$1" region="$2"
  gcloud run services describe "$name" --region="$region" --format=json \
    | jq '.status.traffic[] | {revision: .revisionName, percent: .percent, latest: .latestRevision}'
}

Common Operations

1. Service Health Overview

services=$(gcloud run services list --format="value(metadata.name,metadata.labels.cloud\\.googleapis\\.com/location)" | tr '\t' ',')
for svc in $services; do
  {
    name=$(echo "$svc" | cut -d',' -f1)
    region=$(echo "$svc" | cut -d',' -f2)
    get_service_details "$name" "$region"
  } &
done
wait

2. Revision and Traffic Management

# Current traffic distribution
get_traffic "$SERVICE" "$REGION"

# List recent revisions
list_revisions "$SERVICE" "$REGION"

# Check revision health
gcloud run revisions list --service="$SERVICE" --region="$REGION" --format=json \
  | jq '[.[] | {name: .metadata.name, ready: (.status.conditions[] | select(.type=="Ready") | .status), reason: (.status.conditions[] | select(.type=="Ready" and .status!="True") | .reason)}]'

3. Scaling Configuration

gcloud run services describe "$SERVICE" --region="$REGION" --format=json \
  | jq '{minInstances: .spec.template.metadata.annotations."autoscaling.knative.dev/minScale", maxInstances: .spec.template.metadata.annotations."autoscaling.knative.dev/maxScale", concurrency: .spec.template.spec.containerConcurrency, cpu: .spec.template.spec.containers[0].resources.limits.cpu, memory: .spec.template.spec.containers[0].resources.limits.memory, cpuThrottling: .spec.template.metadata.annotations."run.googleapis.com/cpu-throttling", startupCpuBoost: .spec.template.metadata.annotations."run.googleapis.com/startup-cpu-boost"}'

4. Concurrency and Performance

# Check request metrics
gcloud monitoring time-series list \
  --filter="metric.type=\"run.googleapis.com/request_count\" AND resource.labels.service_name=\"$SERVICE\"" \
  --interval-start-time="$(date -u -v-1H +%Y-%m-%dT%H:%M:%SZ 2>/dev/null || date -u -d '1 hour ago' +%Y-%m-%dT%H:%M:%SZ)" \
  --format=json

# Check instance count
gcloud monitoring time-series list \
  --filter="metric.type=\"run.googleapis.com/container/instance_count\" AND resource.labels.service_name=\"$SERVICE\"" \
  --interval-start-time="$(date -u -v-1H +%Y-%m-%dT%H:%M:%SZ 2>/dev/null || date -u -d '1 hour ago' +%Y-%m-%dT%H:%M:%SZ)" \
  --format=json

# Request latency
gcloud monitoring time-series list \
  --filter="metric.type=\"run.googleapis.com/request_latencies\" AND resource.labels.service_name=\"$SERVICE\"" \
  --interval-start-time="$(date -u -v-1H +%Y-%m-%dT%H:%M:%SZ 2>/dev/null || date -u -d '1 hour ago' +%Y-%m-%dT%H:%M:%SZ)" \
  --format=json

5. IAM and Ingress Configuration

# Check IAM policy (who can invoke)
gcloud run services get-iam-policy "$SERVICE" --region="$REGION" --format=json

# Check ingress settings
gcloud run services describe "$SERVICE" --region="$REGION" --format=json \
  | jq '{ingress: .metadata.annotations."run.googleapis.com/ingress", vpcAccess: .spec.template.metadata.annotations."run.googleapis.com/vpc-access-connector", vpcEgress: .spec.template.metadata.annotations."run.googleapis.com/vpc-access-egress"}'

Output Format

Present results as a structured report:

Gcp Cloud Run Report
════════════════════
Resources discovered: [count]

Resource       Status    Key Metric    Issues
──────────────────────────────────────────────
[name]         [ok/warn] [value]       [findings]

Summary: [total] resources | [ok] healthy | [warn] warnings | [crit] critical
Action Items: [list of prioritized findings]

Target ≤50 lines of output. Use tables for multi-resource comparisons.

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

ShortcutCounterWhy
"I'll skip discovery and check known resources"Always run Phase 1 discovery firstResource names change, new resources appear — assumed names cause errors
"The user only asked for a quick check"Follow the full discovery → analysis flowQuick checks miss critical issues; structured analysis catches silent failures
"Default configuration is probably fine"Audit configuration explicitlyDefaults often leave logging, security, and optimization features disabled
"Metrics aren't needed for this"Always check relevant metrics when availableAPI/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 errorAssumed permission failures prevent useful investigation; actual errors are informative

Common Pitfalls

  1. Scale to zero: Min instances of 0 (default) means cold starts. Set autoscaling.knative.dev/minScale annotation for latency-sensitive services.
  2. CPU throttling: By default, CPU is only allocated during request processing. Set cpu-throttling=false for background tasks, but this increases cost.
  3. Concurrency vs instances: Low concurrency with high traffic spawns many instances. Default concurrency is 80. Tune based on actual workload.
  4. Ingress restrictions: internal ingress blocks all public traffic. internal-and-cloud-load-balancing allows GLB but not direct access.
  5. Container contract: Cloud Run expects the container to listen on the PORT environment variable (default 8080), not a hardcoded port.

리뷰

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