Google Cloud Run Integration
Monitor serverless container deployments with request metrics and instance scaling data. Track cold starts, error rates, and latency SLOs across all your Cloud Run services.
How It Works
Create a GCP Service Account
Create a service account in your GCP project with the Monitoring Viewer and Cloud Run Viewer roles. Download the JSON key to authenticate TigerOps.
Enable Cloud Monitoring API
Enable the Cloud Monitoring API and Cloud Run Admin API in your project. TigerOps uses these to collect request counts, latency distributions, and instance metrics.
Connect TigerOps to Cloud Run
Enter your project ID and credentials in TigerOps. Select the Cloud Run services and regions to monitor. TigerOps begins collecting metrics within seconds.
Configure Alerts and SLOs
Define latency SLOs, error budget burn rate alerts, and cold start frequency thresholds. TigerOps fires predictive alerts before your error budget is exhausted.
What You Get Out of the Box
Request Latency Distributions
P50, P95, and P99 request latency for every Cloud Run service and revision. TigerOps tracks latency regressions across deployments and correlates them with config changes.
Instance Scaling Visibility
Monitor active instance counts, minimum and maximum instance configuration, and scale-to-zero events. Understand the relationship between traffic patterns and instance scaling behavior.
Cold Start Tracking
Measure cold start frequency and duration per service revision. TigerOps identifies which deployments trigger excessive cold starts and recommends minimum instance adjustments.
Error Rate Monitoring
Track HTTP 4xx and 5xx error rates per service. TigerOps correlates error spikes with new revisions, traffic surges, and downstream dependency failures automatically.
Concurrency & Throttling
Monitor container concurrency utilization, request queue depth, and throttled request counts. Optimize your max-concurrency settings with data-driven recommendations.
Multi-Region Aggregation
Aggregate Cloud Run metrics across all GCP regions in a single view. Compare service behavior across regions and detect region-specific latency anomalies with AI correlation.
Cloud Run Integration Config
Set up your GCP credentials and configure Cloud Run services for TigerOps monitoring.
# TigerOps Cloud Run Integration
# gcloud auth application-default login
# or use a service account key
integrations:
gcp_cloud_run:
project_id: "your-gcp-project-id"
credentials_file: "./tigerops-sa-key.json"
regions:
- us-central1
- us-east1
- europe-west1
# Specific services to monitor (empty = all services)
services:
- api-gateway
- payment-processor
- image-resizer
scrape_interval: 60s
metrics:
- run.googleapis.com/request_count
- run.googleapis.com/request_latencies
- run.googleapis.com/container/instance_count
- run.googleapis.com/container/cpu/utilizations
- run.googleapis.com/container/memory/utilizations
alerts:
latency_p99_ms: 2000
error_rate_percent: 1.0
instance_count_max: 100
cold_start_threshold_ms: 3000Common Questions
Can TigerOps monitor Cloud Run for Anthos as well as fully managed Cloud Run?
Yes. TigerOps supports both fully managed Cloud Run (regional) and Cloud Run for Anthos. For Anthos, metrics are collected through the Cloud Monitoring API after enabling the Anthos integration in your cluster.
How does TigerOps measure cold starts for Cloud Run?
TigerOps uses the run.googleapis.com/request_latencies metric combined with instance count change events to infer cold starts. When instance count increases coincide with latency spikes, TigerOps flags the event as a cold start and tracks its duration.
Can I set alerts when Cloud Run scales to zero unexpectedly?
Yes. TigerOps monitors instance count transitions and can alert you when a service scales to zero outside expected maintenance windows. You can also configure alerts for scale-up latency that exceeds your SLO threshold.
Does TigerOps support Cloud Run Jobs in addition to services?
Yes. TigerOps monitors Cloud Run Jobs with metrics including job execution count, execution duration, failed executions, and task retry rates. Job metrics appear alongside service metrics in your GCP dashboard.
How are Cloud Run deployments tracked in TigerOps?
TigerOps captures revision deployment events from the Cloud Run Admin API and overlays them on your metrics charts. When a new revision is deployed, TigerOps automatically compares its performance against the previous revision for regression detection.
Get Ahead of Cloud Run Cold Starts and Errors
Request latency SLOs, cold start tracking, and AI-powered error correlation. Connect your Cloud Run services in minutes.