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🔒 Confidential Computing and P April 5, 2026 12 min read

Google Confidential GKE: sensitive Kubernetes workloads

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Google Confidential GKE (Google Kubernetes Engine) enables enterprises to run containerised workloads where the node VMs are hardware-encrypted using AMD SEV-SNP or Intel TDX, protecting running workloads from the cloud infrastructure operator. For enterprises running sensitive workloads on GKE — healthcare data processing, financial model inference, PII handling — Confidential GKE provides data-in-use protection with minimal operational overhead beyond standard GKE management. This guide covers configuration, performance characteristics, and enterprise deployment patterns.

What Is Confidential GKE?

Confidential GKE — Definition
Google Kubernetes Engine nodes running on Confidential VM instances (C3 series with Intel TDX or N2D series with AMD SEV-SNP) where the node's memory is hardware-encrypted. Kubernetes pods running on these nodes benefit from the same hardware memory isolation as Confidential VMs — even a compromised GKE node host cannot read the memory of containers running in confidential mode. Requires minimal configuration changes vs standard GKE: add --enable-confidential-nodes to the node pool.

Confidential GKE Options: C3 (TDX) vs N2D (SEV-SNP)

OptionHardwareTEEvCPU RangePerformance OverheadBest For
C3 ConfidentialIntel Sapphire RapidsIntel TDX4–192 vCPU5–10%Compute-intensive, newest hardware, AI inference
N2D ConfidentialAMD EPYC Milan/GenoaAMD SEV-SNP2–224 vCPU3–8%Memory-intensive workloads, existing AMD workflows

Enabling Confidential GKE

01
Step 1
Create Confidential Node Pool

Enable confidential nodes via gcloud: gcloud container node-pools create confidential-pool --cluster=CLUSTER --machine-type=c3-standard-8 --enable-confidential-nodes --zone=us-central1-a. Node pool must use a machine type that supports Confidential VMs. Compatible OS: Container-Optimised OS (COS) or Ubuntu. Verify confidential status: gcloud compute instances describe NODE_NAME | grep -i confidential. Integrate into your Terraform infrastructure-as-code.

gcloud node-pool--enable-confidential-nodesTerraform integration
02
Step 2
Schedule Sensitive Workloads to Confidential Nodes

Use Kubernetes node selectors and taints to schedule sensitive workloads exclusively to confidential nodes. Add label to node pool: confidential-compute: "true". Add toleration and nodeSelector to pod spec: nodeSelector: {confidential-compute: "true"} and matching toleration. This ensures sensitive containers never run on non-confidential nodes by mistake. Document which workloads require confidential scheduling in your security architecture.

Node selectorPod tolerationWorkload scheduling policy
03
Step 3
Attestation and Key Management with Cloud KMS

Combine Confidential GKE with Google Cloud KMS key policies that require confidential compute attestation. Use Workload Identity + KMS Key Access Conditions: compute.googleapis.com/confidentialComputing: "true". This ensures encryption keys are only accessible to workloads running in verified confidential nodes. Connect to your secrets management and DevOps security infrastructure.

Cloud KMS attestationWorkload IdentityKey access conditions
2 flags
Configuration required to enable Confidential GKE on an existing node pool — --enable-confidential-nodes and a compatible machine type. The lowest-friction entry point to confidential computing at enterprise Kubernetes scale
0
Application code changes required for most Kubernetes workloads migrating to Confidential GKE — the hardware encryption is transparent to containerised applications
5–10%
Performance overhead for most workloads on Confidential GKE — acceptable for the vast majority of enterprise containerised applications processing regulated or sensitive data
Deploying Confidential GKE?

Our DevOps and software development teams design and deploy Confidential GKE architectures for regulated enterprise workloads. Book a free advisory session to scope your confidential Kubernetes deployment.

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