GKE Tip Series how do i choose between gke standard, autopilot and cloud run
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This document compares Google Kubernetes Engine (GKE) Standard, GKE Autopilot, and Cloud Run, discussing features like control over cluster management, autoscaling, and pricing. GKE Standard offers more configuration flexibility, while Autopilot provides a hands-off experience with auto-provisioning of resources. Cloud Run allows quick application deployment with a focus on serverless execution, ideal for applications without stateful requirements.
GKE Tip Series how do i choose between gke standard, autopilot and cloud run
- 1. AppMod Tip of the week series How do I choose between GKE Standard, Autopilot and Cloud Run? Sreenivas Makam
- 2. Control plane provisioning & management Availability & reliability Patching & upgrades Security & Networking configuration Application platform Monitoring & management Scaling up & down DIY Kubernetes Service Worker nodes provisioning & management Standard mode: Managed Kubernetes with configuration flexibility Autopilot mode: Optimized Managed Kubernetes with hands-off experience Security & Networking configuration Worker nodes provisioning & management Google Kubernetes Engine (GKE) Modern application platform Modern application platform One GKE - two modes of operation Mode of operation = level of control over a GKE cluster
- 3. Cloud Run Deploy in seconds Automatic HTTPS, Custom domains Any language, any library Portability Pay-per-use Run containers on a fully managed environment
- 4. Comparison Feature GKE Autopilot Cloud Run Use Kubernetes manifest to deploy application Yes Yes No Worker nodes responsibility Customer Google Google Networking and security Managed by the customer Auto-provisioned Auto-provisioned Autoscaling Managed by the customer Node autoscaling managed by Google. HPA and VPA for pods managed by customer Managed by Google Stateful apps Supported Supported Not supported SLA Control plane SLA Control plane and pod SLA Service SLA Resource request Flexible cpu, memory sizes Pod requests are rounded off to 250mcpu multiples and vcpu to memory ratio allowed is 1:6.5. Limits set same as requests. Limited granularity(vcpu-1,2,4 memory starting at 128m) Pricing Based on worker node count and sizes. Cluster fee applicable. Based on Cpu and memory usage of user scheduled pods. Don’t need to pay for system pods and OS usage in nodes. Cluster fee applicable. Based on Cpu, memory of pods and number of requests/second. No cluster fee
- 5. Deploy application gcloud run deploy hello-app --region us-central1 --image gcr.io/google-samples/hello-app:1.0 --platform managed --cpu=1 --memory=128Mi gcloud beta container --project <project> clusters create-auto "autopilot-cluster-1" --region "us-central1" kubectl run hello-server --image=gcr.io/google-samples/hello-a pp:1.0 --port=8080 --replicas=2 gcloud beta container --project <project> clusters create <name> --region "us-central1" --no-enable-basic-auth --machine-type "e2-medium" --num-nodes "3" --enable-autoscaling --min-nodes "0" --max-nodes "3" kubectl run hello-server --image=gcr.io/google-samples/hello-a pp:1.0 --port=8080 --replicas=2 Google Kubernetes Engine Google Kubernetes Engine with AP Cloud Run
- 6. How do I select?