Is GCP Down? Complete Google Cloud Status Check Guide + Quick Fixes

Compute Engine instances not responding?
Cloud Run deployments failing?
BigQuery queries timing out?

Before panicking, verify if GCP is actually down—or if it's a configuration, quota, or authentication issue on your end. Here's your complete guide to checking Google Cloud status and fixing common issues fast.

Quick Check: Is GCP Actually Down?

Don't assume it's GCP. 80% of "GCP down" reports are actually quota limits, IAM permission issues, misconfigured services, or regional problems—not global outages.

1. Check Official Sources

Google Cloud Status Dashboard:
🔗 status.cloud.google.com

What to look for:

  • ✅ All green checkmarks = GCP is operational
  • 🟡 Yellow icon = Service disruption in progress
  • 🔴 Red icon = Service outage
  • 🔵 Blue icon = Scheduled maintenance

Real-time updates:

  • Compute Engine status
  • Cloud Run availability
  • Cloud Functions health
  • BigQuery service status
  • Cloud Storage operations
  • GKE (Kubernetes Engine) health
  • Cloud SQL databases
  • Pub/Sub messaging
  • Regional and global services

Pro tip: Click on any service to see incident history and affected regions.

Google Cloud Support Twitter/X:
🔗 Search "GCP down" or @googlecloud

Why it works:

  • Developers report outages instantly
  • See if others in your region are affected
  • Google Cloud team posts official updates here

Pro tip: If 200+ tweets in the last hour mention "GCP down" in your region, it's likely a real outage.

Google Workspace Status Dashboard:
🔗 google.com/appsstatus

Note: This is for Gmail, Drive, Calendar, etc.—NOT Google Cloud Platform. Common confusion point.

2. Check Service-Specific Status

GCP has 100+ services that can fail independently:

Service What It Does Check Status
Compute Engine Virtual machines (VMs) Compute Engine Status
Cloud Run Serverless containers Cloud Run Status
Cloud Functions Serverless functions Cloud Functions Status
BigQuery Data warehouse BigQuery Status
Cloud Storage Object storage (GCS) Cloud Storage Status
GKE Kubernetes clusters GKE Status
Cloud SQL Managed databases Cloud SQL Status
Pub/Sub Message queue Pub/Sub Status

Your service might be down while GCP globally is up.

How to check which service is affected:

  1. Visit status.cloud.google.com
  2. Filter by service or region
  3. Check "Incident History" for recent issues
  4. Subscribe to status updates (email notifications)
  5. Use RSS feed for automated monitoring

3. Check Regional vs Global Issues

GCP operates in 40+ regions worldwide. An outage in us-central1 doesn't affect europe-west1.

How to identify regional issues:

Option 1: Status Dashboard Filtering

  1. Visit status.cloud.google.com
  2. Click affected service
  3. Look for "Affected locations" in incident details
  4. Check if your region is listed

Option 2: Test from Different Region

# Test API from different region
gcloud compute instances list --zones=us-central1-a
gcloud compute instances list --zones=europe-west1-b

If one works and other fails: Regional outage confirmed.

Common regional patterns:

  • us-central1 (Iowa) — Most common, highest traffic
  • us-east1 (South Carolina) — Second most common
  • europe-west1 (Belgium) — European workloads
  • asia-southeast1 (Singapore) — Asia-Pacific

Pro tip: Multi-region deployments protect against regional outages. Consider failover strategies for critical services.

Common GCP Error Messages (And What They Mean)

Error 403: "The caller does not have permission"

What it means: IAM permissions issue—your account/service account lacks required roles.

Common causes:

  • Service account missing roles
  • Project-level permissions not granted
  • Organization policy blocking access
  • API not enabled for project

Quick fixes:

1. Check IAM roles:

# Check your permissions
gcloud projects get-iam-policy PROJECT_ID \
  --flatten="bindings[].members" \
  --filter="bindings.members:YOUR_EMAIL"

# Grant necessary role (example: Compute Admin)
gcloud projects add-iam-policy-binding PROJECT_ID \
  --member="user:YOUR_EMAIL" \
  --role="roles/compute.admin"

2. Enable required API:

# Check enabled APIs
gcloud services list --enabled

# Enable API (example: Compute Engine)
gcloud services enable compute.googleapis.com

3. Check service account:

# View service account roles
gcloud projects get-iam-policy PROJECT_ID \
  --flatten="bindings[].members" \
  --filter="bindings.members:serviceAccount:SA_EMAIL"

Error 429: "Quota exceeded"

What it means: You've hit API quota limits or resource quotas.

Common causes:

  • API request rate limit exceeded
  • CPU/memory quota exhausted
  • Disk quota reached
  • IP address quota limit hit

Quick fixes:

1. Check quota usage:

# View quotas
gcloud compute project-info describe --project=PROJECT_ID

# Or visit Cloud Console:
# IAM & Admin → Quotas

2. Request quota increase:

  1. Console → IAM & Admin → Quotas
  2. Filter by service (e.g., "Compute Engine API")
  3. Select quota (e.g., "CPUs")
  4. Click "EDIT QUOTAS"
  5. Request increase (justify business need)
  6. Wait for approval (usually 24-48 hours)

3. Implement exponential backoff:

# Retry with exponential backoff
import time
from google.api_core import retry

@retry.Retry(predicate=retry.if_exception_type(Exception))
def call_api():
    # Your API call here
    pass

4. Temporary workaround:

  • Delete unused resources
  • Use different region (separate quotas)
  • Upgrade to paid tier (higher limits)

Error 500: "Internal Server Error"

What it means: Something wrong on Google's side—server error, not your code.

Common causes:

  • Temporary service glitch
  • Backend service degraded
  • Database connection issue
  • Deployment in progress

Quick fixes:

1. Retry the request:

  • Most 500 errors are transient
  • Wait 30-60 seconds and retry
  • Implement automatic retry logic

2. Check status dashboard:

3. Try different region:

# If us-central1 fails, try us-east1
gcloud config set compute/region us-east1

4. Contact support:

  • If persistent, file support ticket
  • Include request ID from error message
  • Provide timestamp and affected service

Error 503: "Service Unavailable"

What it means: Service temporarily unavailable—could be maintenance or overload.

Common causes:

  • Scheduled maintenance window
  • Service overloaded
  • Regional capacity issue
  • Cold start timeout (Cloud Functions/Cloud Run)

Quick fixes:

1. Check maintenance schedule:

  • Console → Compute Engine → VM instances → Maintenance events
  • status.cloud.google.com shows planned maintenance

2. Increase Cloud Run/Functions resources:

# Cloud Run: Increase CPU/memory
apiVersion: serving.knative.dev/v1
kind: Service
spec:
  template:
    spec:
      containers:
      - resources:
          limits:
            cpu: "2"
            memory: "1Gi"

3. Set minimum instances (avoid cold starts):

# Cloud Run: Set minimum instances
gcloud run services update SERVICE_NAME \
  --min-instances=1 \
  --region=REGION

4. Implement retry logic:

  • Wait and retry (exponential backoff)
  • Use Cloud Tasks for async processing
  • Implement circuit breaker pattern

Error 404: "Not Found"

What it means: Resource doesn't exist—wrong name, region, or project.

Common causes:

  • Wrong resource name/ID
  • Resource in different project
  • Resource in different region
  • Resource was deleted

Quick fixes:

1. Verify resource exists:

# List all instances
gcloud compute instances list --project=PROJECT_ID

# List Cloud Run services
gcloud run services list --platform=managed

# List Cloud Storage buckets
gcloud storage buckets list

2. Check correct project:

# View current project
gcloud config get-value project

# Switch project
gcloud config set project PROJECT_ID

# List all your projects
gcloud projects list

3. Check correct region:

# Specify region explicitly
gcloud compute instances describe INSTANCE_NAME \
  --zone=us-central1-a

Error 401: "Unauthorized"

What it means: Authentication failed—expired token, wrong credentials, or revoked access.

Common causes:

  • Application Default Credentials (ADC) not configured
  • Service account key expired/revoked
  • gcloud auth not set up
  • OAuth token expired

Quick fixes:

1. Authenticate gcloud:

# Login with your account
gcloud auth login

# Set application default credentials
gcloud auth application-default login

2. Check service account key:

# Verify service account
gcloud auth list

# Activate service account
gcloud auth activate-service-account SA_EMAIL \
  --key-file=PATH_TO_KEY.json

3. Refresh credentials:

# Revoke and re-authenticate
gcloud auth revoke
gcloud auth login

4. Check environment variables:

# Verify GOOGLE_APPLICATION_CREDENTIALS
echo $GOOGLE_APPLICATION_CREDENTIALS

# Set it if missing
export GOOGLE_APPLICATION_CREDENTIALS="/path/to/key.json"

Quick Fixes: GCP Not Working?

Fix #1: Check gcloud CLI Authentication

Why it works: 90% of GCP issues are authentication or project misconfiguration.

Verify setup:

# Check current auth account
gcloud auth list

# Check current project
gcloud config get-value project

# Check current region/zone
gcloud config get-value compute/region
gcloud config get-value compute/zone

Expected output:

ACTIVE  ACCOUNT
*       your-email@example.com

PROJECT_ID: your-project-123
REGION: us-central1
ZONE: us-central1-a

If missing or wrong:

# Set correct project
gcloud config set project YOUR_PROJECT_ID

# Set default region
gcloud config set compute/region us-central1
gcloud config set compute/zone us-central1-a

# Re-authenticate
gcloud auth login
gcloud auth application-default login

Fix #2: Enable Required APIs

GCP APIs are disabled by default. Enabling them is the #1 forgotten step.

Check enabled APIs:

# List enabled APIs
gcloud services list --enabled

# List available APIs
gcloud services list --available

Enable common APIs:

# Compute Engine
gcloud services enable compute.googleapis.com

# Cloud Run
gcloud services enable run.googleapis.com

# Cloud Functions
gcloud services enable cloudfunctions.googleapis.com

# BigQuery
gcloud services enable bigquery.googleapis.com

# Cloud Storage
gcloud services enable storage.googleapis.com

# GKE
gcloud services enable container.googleapis.com

# Cloud SQL
gcloud services enable sqladmin.googleapis.com

Enable via Console:

  1. APIs & Services → Library
  2. Search for service (e.g., "Cloud Run")
  3. Click service → "ENABLE"

Pro tip: Enabling APIs can take 30-60 seconds. Don't retry immediately.

Fix #3: Check Billing Account

GCP requires active billing for most services (even with free tier credits).

Verify billing:

# Check billing account
gcloud beta billing projects describe PROJECT_ID

Expected output:

billingAccountName: billingAccounts/XXXXXX-XXXXXX-XXXXXX
billingEnabled: true

If billing not enabled:

  1. Console → Billing
  2. Link project to billing account
  3. Enable billing for project

Common billing issues:

  • Credit card expired
  • Free tier credits exhausted
  • Billing account suspended
  • Project not linked to billing account

Check billing status:

  • Console → Billing → Account Management
  • Look for "ACTIVE" status
  • Check spending limits/budgets

Fix #4: Verify IAM Permissions

"Permission denied" is the most common error—even for project owners.

Check your roles:

# View your permissions
gcloud projects get-iam-policy PROJECT_ID \
  --flatten="bindings[].members" \
  --filter="bindings.members:$(gcloud config get-value account)"

Common required roles:

  • Compute Admin → Create/manage VMs
  • Cloud Run Admin → Deploy Cloud Run services
  • Storage Admin → Manage Cloud Storage
  • BigQuery Admin → Query and manage datasets
  • Editor → General development access
  • Owner → Full project access

Grant yourself missing roles:

# Example: Grant Compute Admin
gcloud projects add-iam-policy-binding PROJECT_ID \
  --member="user:YOUR_EMAIL" \
  --role="roles/compute.admin"

For service accounts:

# Grant service account Cloud Run Admin
gcloud projects add-iam-policy-binding PROJECT_ID \
  --member="serviceAccount:SA_EMAIL" \
  --role="roles/run.admin"

Fix #5: Check Resource Quotas

Quotas prevent runaway costs—but also block legitimate usage.

View quota usage:

  1. Console → IAM & Admin → Quotas
  2. Filter by service
  3. Look for quotas near 100% usage

Common quota issues:

  • CPUs: Default 24 CPUs per region
  • In-use IP addresses: Default 23 per region
  • Persistent disk SSD: Default 500 GB per region
  • Cloud Run requests: Default 1000/second

Increase quota:

  1. IAM & Admin → Quotas
  2. Select quota to increase
  3. Click "EDIT QUOTAS"
  4. Enter higher limit + justification
  5. Submit request

Temporary workaround:

# Deploy to different region (separate quotas)
gcloud run deploy SERVICE_NAME \
  --region=europe-west1 \
  --image=gcr.io/PROJECT_ID/IMAGE

# Or delete unused resources
gcloud compute instances delete OLD_INSTANCE --zone=us-central1-a

Fix #6: Update gcloud CLI

Outdated CLI = bugs, missing features, and weird errors.

Check version:

gcloud version

Current version (as of Feb 2026): 460.0.0+

Update gcloud:

# Standard installation
gcloud components update

# Snap installation (Linux)
snap refresh google-cloud-sdk

# Homebrew (Mac)
brew upgrade google-cloud-sdk

If update fails:

# Reinstall from scratch
curl https://sdk.cloud.google.com | bash
exec -l $SHELL
gcloud init

Fix #7: Check Network Connectivity

Firewall rules block most traffic by default.

Test connectivity:

# SSH into Compute Engine instance
gcloud compute ssh INSTANCE_NAME --zone=ZONE

# If SSH fails, check firewall rules
gcloud compute firewall-rules list

Common firewall fixes:

Allow SSH (port 22):

gcloud compute firewall-rules create allow-ssh \
  --allow=tcp:22 \
  --source-ranges=0.0.0.0/0 \
  --target-tags=ssh-enabled

Allow HTTP/HTTPS:

gcloud compute firewall-rules create allow-http \
  --allow=tcp:80,tcp:443 \
  --source-ranges=0.0.0.0/0 \
  --target-tags=http-server

Check Cloud Run ingress settings:

# Allow public access
gcloud run services update SERVICE_NAME \
  --ingress=all \
  --region=REGION

Check VPC routes:

# List routes
gcloud compute routes list

# Check VPC peering
gcloud compute networks peerings list

Fix #8: Restart/Redeploy Service

Simple restart fixes transient issues.

Compute Engine:

# Restart instance
gcloud compute instances stop INSTANCE_NAME --zone=ZONE
gcloud compute instances start INSTANCE_NAME --zone=ZONE

# Or reset (hard restart)
gcloud compute instances reset INSTANCE_NAME --zone=ZONE

Cloud Run:

# Redeploy (triggers new revision)
gcloud run deploy SERVICE_NAME \
  --image=gcr.io/PROJECT_ID/IMAGE \
  --region=REGION

# Or force new revision with no changes
gcloud run services update SERVICE_NAME \
  --region=REGION \
  --update-env-vars=UPDATED=$(date +%s)

Cloud Functions:

# Redeploy function
gcloud functions deploy FUNCTION_NAME \
  --runtime=python311 \
  --trigger-http \
  --allow-unauthenticated

GKE:

# Restart deployment
kubectl rollout restart deployment DEPLOYMENT_NAME

# Check pod status
kubectl get pods
kubectl describe pod POD_NAME

Compute Engine Not Working?

Issue: Can't SSH Into Instance

Troubleshoot:

1. Check instance is running:

gcloud compute instances list
# Status should be "RUNNING"

2. Check firewall allows SSH:

# List firewall rules
gcloud compute firewall-rules list | grep ssh

# Create SSH rule if missing
gcloud compute firewall-rules create allow-ssh \
  --allow=tcp:22 \
  --source-ranges=0.0.0.0/0

3. Check instance has external IP:

gcloud compute instances describe INSTANCE_NAME \
  --zone=ZONE \
  --format="get(networkInterfaces[0].accessConfigs[0].natIP)"

4. Use IAP tunnel (if no external IP):

gcloud compute ssh INSTANCE_NAME \
  --zone=ZONE \
  --tunnel-through-iap

5. Check OS Login settings:

# Enable OS Login
gcloud compute instances add-metadata INSTANCE_NAME \
  --zone=ZONE \
  --metadata=enable-oslogin=TRUE

Issue: Instance Stuck in "PROVISIONING" or "STAGING"

Causes:

  • Resource quota exceeded
  • Zone capacity issue
  • Image/snapshot problem

Fixes:

1. Check quota:

  • Console → IAM & Admin → Quotas
  • Look for CPU or disk quota exhausted

2. Try different zone:

# Delete stuck instance
gcloud compute instances delete INSTANCE_NAME --zone=us-central1-a

# Create in different zone
gcloud compute instances create INSTANCE_NAME \
  --zone=us-central1-b \
  --machine-type=e2-medium

3. Use different machine type:

# If n2-standard-4 unavailable, try e2-standard-4
gcloud compute instances create INSTANCE_NAME \
  --zone=ZONE \
  --machine-type=e2-standard-4

Cloud Run Not Working?

Issue: Deployment Fails

Troubleshoot:

1. Check container image exists:

# List images in Container Registry
gcloud container images list --repository=gcr.io/PROJECT_ID

# Or Artifact Registry
gcloud artifacts docker images list REGION-docker.pkg.dev/PROJECT_ID/REPOSITORY

2. Check service account permissions:

# Grant Cloud Run Admin role
gcloud projects add-iam-policy-binding PROJECT_ID \
  --member="user:YOUR_EMAIL" \
  --role="roles/run.admin"

3. Check deployment logs:

# View deployment errors
gcloud run services describe SERVICE_NAME \
  --region=REGION \
  --format="value(status.conditions)"

4. Test container locally:

# Run container locally first
docker run -p 8080:8080 gcr.io/PROJECT_ID/IMAGE
curl localhost:8080

Issue: "Container failed to start"

Causes:

  • Application crashes on startup
  • Port not exposed correctly
  • Missing environment variables
  • Cold start timeout

Fixes:

1. Check logs:

# View Cloud Run logs
gcloud run services logs read SERVICE_NAME \
  --region=REGION \
  --limit=50

2. Verify PORT environment variable:

# Cloud Run expects app to listen on $PORT (usually 8080)
# In your app:
port = os.environ.get("PORT", 8080)
app.run(host="0.0.0.0", port=port)

3. Increase timeout and resources:

gcloud run services update SERVICE_NAME \
  --region=REGION \
  --timeout=300 \
  --cpu=2 \
  --memory=2Gi

4. Set required environment variables:

gcloud run services update SERVICE_NAME \
  --region=REGION \
  --set-env-vars="KEY1=value1,KEY2=value2"

BigQuery Not Working?

Issue: Queries Timing Out

Causes:

  • Query too complex/expensive
  • Large dataset scan
  • Quota exceeded
  • Concurrent query limit hit

Fixes:

1. Optimize query:

-- Use partitioned tables
SELECT *
FROM `project.dataset.table`
WHERE DATE(timestamp) = "2026-02-10"  -- Uses partition pruning

-- Avoid SELECT *
SELECT specific_column1, specific_column2
FROM `project.dataset.table`
LIMIT 1000

2. Check query cost before running:

# Estimate query cost
bq query --dry_run 'SELECT * FROM `project.dataset.table`'

3. Increase timeout:

# Set longer timeout (milliseconds)
bq query --max_rows=1000 --timeout=300000 'SELECT ...'

4. Check quota usage:

  • Console → BigQuery → Quotas
  • Look for "Query usage" and "Concurrent queries"

Cloud Storage Not Working?

Issue: "Access Denied" When Reading Object

Causes:

  • IAM permissions missing
  • Bucket-level access not configured
  • Object ACL restrictions
  • Requester Pays bucket

Fixes:

1. Grant Storage permissions:

# Grant yourself Storage Admin
gcloud projects add-iam-policy-binding PROJECT_ID \
  --member="user:YOUR_EMAIL" \
  --role="roles/storage.admin"

# Or grant on specific bucket
gcloud storage buckets add-iam-policy-binding gs://BUCKET_NAME \
  --member="user:YOUR_EMAIL" \
  --role="roles/storage.objectViewer"

2. Make bucket public (if appropriate):

# Make all objects public
gcloud storage buckets add-iam-policy-binding gs://BUCKET_NAME \
  --member="allUsers" \
  --role="roles/storage.objectViewer"

3. Check if Requester Pays:

# Specify billing project for Requester Pays buckets
gcloud storage cp gs://BUCKET_NAME/file.txt . \
  --billing-project=PROJECT_ID

GKE (Kubernetes) Not Working?

Issue: Cluster Creation Fails

Causes:

  • Quota exceeded
  • Zone capacity
  • API not enabled
  • Network configuration issue

Fixes:

1. Enable GKE API:

gcloud services enable container.googleapis.com

2. Check quota:

  • Console → IAM & Admin → Quotas
  • Filter: "Kubernetes Engine API"
  • Look for "In-use IP addresses" and "CPUs"

3. Use Autopilot mode (simpler):

# Create Autopilot cluster (managed for you)
gcloud container clusters create-auto CLUSTER_NAME \
  --region=REGION

4. Try different zone/region:

# If us-central1 full, try us-east1
gcloud container clusters create CLUSTER_NAME \
  --zone=us-east1-b

Issue: Can't Connect to Cluster

Troubleshoot:

1. Get cluster credentials:

# Configure kubectl
gcloud container clusters get-credentials CLUSTER_NAME \
  --region=REGION

2. Verify kubectl context:

# Check current context
kubectl config current-context

# List all contexts
kubectl config get-contexts

3. Test cluster access:

# List nodes
kubectl get nodes

# List pods
kubectl get pods --all-namespaces

4. Check firewall:

  • Master authorized networks might be blocking you
  • Console → GKE → Cluster → Networking
  • Add your IP to authorized networks

When GCP Actually Goes Down

What Happens

Recent major outages:

  • November 2025: 4-hour Cloud Run outage in us-central1 (deployment issue)
  • August 2025: 2-hour Compute Engine disruption (network configuration)
  • May 2025: 3-hour Cloud Storage degradation in europe-west1 (hardware failure)
  • February 2025: 1-hour BigQuery slowdown (internal service issue)

Typical causes:

  1. Regional infrastructure failures
  2. Network configuration errors
  3. Software deployment bugs
  4. Power/cooling issues in data centers
  5. Rare: Multi-region backbone failures

How Google Responds

Communication channels:

Timeline:

  1. 0-15 min: Developers report issues on Twitter/Reddit
  2. 15-30 min: Google acknowledges on status dashboard
  3. 30-90 min: Regular updates posted
  4. Resolution: Usually 1-4 hours for major outages

Post-incident:

  • Detailed incident report published (7-14 days later)
  • Root cause analysis
  • Remediation steps taken
  • SLA credits issued (if applicable)

What to Do During Outages

1. Check if multi-region helps:

# Switch to backup region
gcloud config set compute/region europe-west1
gcloud run deploy SERVICE_NAME --region=europe-west1

2. Use cached/backup data:

  • Serve from Cloud CDN cache
  • Use read replicas in different regions
  • Activate disaster recovery plan

3. Monitor status dashboard:

4. File support ticket:

  • Console → Support → Create Case
  • Reference status dashboard incident number
  • Request SLA credit if applicable

GCP Down Checklist

Follow these steps in order:

Step 1: Verify it's actually down

Step 2: Quick authentication fixes

  • Run gcloud auth list (verify logged in)
  • Run gcloud config get-value project (verify correct project)
  • Re-authenticate: gcloud auth login
  • Set application default credentials: gcloud auth application-default login

Step 3: Enable APIs and check billing

  • Verify required APIs enabled: gcloud services list --enabled
  • Enable missing APIs: gcloud services enable SERVICE.googleapis.com
  • Check billing enabled: gcloud beta billing projects describe PROJECT_ID
  • Link project to billing account if needed

Step 4: Check IAM permissions

  • Verify your roles: gcloud projects get-iam-policy PROJECT_ID
  • Grant missing roles (Editor, Compute Admin, etc.)
  • Check service account permissions
  • Enable Domain Delegation if needed (for workspace)

Step 5: Check quotas and limits

  • Console → IAM & Admin → Quotas
  • Look for quotas at 100% usage
  • Request quota increase if needed
  • Try different region (separate quotas)

Step 6: Network troubleshooting

  • Check firewall rules: gcloud compute firewall-rules list
  • Verify instance has external IP (if needed)
  • Test connectivity with gcloud compute ssh
  • Check VPC routes and peering

Step 7: Service-specific fixes

  • Compute Engine: Restart instance, check zone capacity
  • Cloud Run: Check logs, redeploy service
  • BigQuery: Optimize query, check quota
  • Cloud Storage: Verify bucket permissions
  • GKE: Get credentials, check cluster status

Step 8: Nuclear option

  • Update gcloud CLI: gcloud components update
  • Recreate resource in different region
  • Contact Google Cloud Support
  • Check Google Cloud Community

Prevent Future Issues

1. Set Up Multi-Region Redundancy

Don't put all your eggs in one region.

Best practices:

Compute Engine:

# Create instance group spanning multiple zones
gcloud compute instance-groups managed create IG_NAME \
  --template=TEMPLATE_NAME \
  --size=3 \
  --zones=us-central1-a,us-central1-b,us-central1-c

Cloud Run:

# Deploy to multiple regions
gcloud run deploy SERVICE_NAME --region=us-central1 --image=IMAGE
gcloud run deploy SERVICE_NAME --region=europe-west1 --image=IMAGE

# Use Cloud Load Balancing for global distribution

Cloud Storage:

# Use multi-region bucket
gcloud storage buckets create gs://BUCKET_NAME \
  --location=US  # Multi-region (not single region)

BigQuery:

  • Use dataset in multi-region location (US, EU)
  • Replicate critical datasets across regions
  • Use BigQuery Omni for cross-cloud queries

2. Monitor Proactively

Don't wait for users to report issues.

Set up monitoring:

1. Cloud Monitoring (native):

# Create uptime check
gcloud monitoring uptime-checks create HTTP_CHECK_NAME \
  --display-name="My Service Health Check" \
  --resource-type="gce-instance" \
  --http-check-path="/"

2. Cloud Alerting:

  • Console → Monitoring → Alerting
  • Create alert policies for:
    • Instance CPU > 80%
    • Cloud Run error rate > 5%
    • BigQuery job failures
    • Cloud Storage 4xx/5xx errors

3. External monitoring:

  • Use API Status Check for independent monitoring
  • Set up alerts to Slack, Discord, email, webhooks
  • Monitor from multiple global locations

4. Subscribe to status updates:

3. Implement Proper Error Handling

Your code should gracefully handle GCP failures.

Best practices:

Exponential backoff:

from google.api_core import retry

# Automatic retry with exponential backoff
@retry.Retry(
    predicate=retry.if_exception_type(Exception),
    initial=1.0,
    maximum=60.0,
    multiplier=2.0,
    deadline=300.0
)
def call_gcp_api():
    # Your API call
    pass

Circuit breaker:

# Stop hammering failed service
from pybreaker import CircuitBreaker

gcp_breaker = CircuitBreaker(fail_max=5, timeout_duration=60)

@gcp_breaker
def call_gcp_service():
    # API call
    pass

Fallback strategies:

def get_data():
    try:
        return fetch_from_bigquery()
    except Exception:
        # Fallback to cached data
        return get_from_memcache()

4. Use Infrastructure as Code

Recreate infrastructure quickly if needed.

Terraform example:

# terraform/main.tf
resource "google_compute_instance" "app_server" {
  name         = "app-server"
  machine_type = "e2-medium"
  zone         = var.primary_zone

  # Automatic failover to secondary zone
  lifecycle {
    create_before_destroy = true
  }
}

# Easy to deploy to backup region
# terraform apply -var="region=europe-west1"

gcloud scripts:

#!/bin/bash
# deploy.sh - Reproducible deployment

PROJECT_ID="my-project"
REGION="us-central1"

gcloud config set project $PROJECT_ID

# Enable APIs
gcloud services enable compute.googleapis.com
gcloud services enable run.googleapis.com

# Deploy Cloud Run
gcloud run deploy app \
  --image=gcr.io/$PROJECT_ID/app \
  --region=$REGION \
  --allow-unauthenticated

5. Test Disaster Recovery

Hope for the best, prepare for the worst.

DR testing checklist:

1. Region failover test:

  • Simulate primary region outage
  • Switch traffic to secondary region
  • Measure RTO (Recovery Time Objective)
  • Verify data consistency

2. Data backup/restore test:

# Test Cloud SQL backup restore
gcloud sql backups create \
  --instance=INSTANCE_NAME

gcloud sql backups restore BACKUP_ID \
  --backup-instance=SOURCE_INSTANCE \
  --backup-instance-project=PROJECT_ID \
  --restore-instance=TARGET_INSTANCE

3. Service degradation scenarios:

  • What if BigQuery is down? Can you serve cached results?
  • What if Cloud Storage is down? Can you serve from CDN?
  • What if Cloud Run is down? Can you failover to Compute Engine?

4. Document runbooks:

  • Step-by-step recovery procedures
  • Who to contact (Google Support, on-call engineer)
  • Communication templates for users
  • SLA credit request process

Key Takeaways

Before assuming GCP is down:

  1. ✅ Check Google Cloud Status Dashboard
  2. ✅ Verify authentication: gcloud auth list
  3. ✅ Check correct project: gcloud config get-value project
  4. ✅ Search Twitter for "GCP down" in your region

Common fixes:

  • Re-authenticate (gcloud auth login)
  • Enable required APIs (gcloud services enable)
  • Check/grant IAM permissions
  • Verify billing account linked
  • Check resource quotas (IAM & Admin → Quotas)
  • Try different region

Service-specific issues:

  • Compute Engine: Check firewall, instance status, zone capacity
  • Cloud Run: Check logs, container image, environment variables
  • BigQuery: Optimize query, check quota, increase timeout
  • Cloud Storage: Verify IAM, check Requester Pays
  • GKE: Get credentials, check cluster health, verify quota

If GCP is actually down:

  • Monitor status.cloud.google.com
  • Switch to backup region if configured
  • Activate disaster recovery plan
  • File support ticket for SLA credits

Prevent future issues:

  • Deploy to multiple regions
  • Set up Cloud Monitoring + alerting
  • Use API Status Check for external monitoring
  • Implement retry logic and error handling
  • Test disaster recovery procedures regularly

Remember: Most "GCP down" issues are authentication, permissions, or quota problems—not actual outages. Work through the checklist systematically.

Need real-time GCP status monitoring? Track Google Cloud uptime with API Status Check - Get instant alerts when GCP services go down.

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