> ## Documentation Index
> Fetch the complete documentation index at: https://notes.kodekloud.com/llms.txt
> Use this file to discover all available pages before exploring further.
# Section Introduction
> This article covers key security layers and best practices for securing Google Kubernetes Engine clusters.
This module assumes you are already familiar with [Kubernetes basics](https://kubernetes.io/docs/concepts/overview/what-is-kubernetes/) and have access to a Google Cloud project with billing enabled.
Google Kubernetes Engine (GKE) is a powerful platform for running containerized workloads at scale. As adoption grows, it’s critical to build a robust security posture around your clusters. In this lesson, we’ll cover the key security layers in GKE and best practices for each.
## What You’ll Learn
| Security Domain | Key Concepts |
| ------------------------------ | --------------------------------------------------------------------------------- |
| Shared Responsibility Model | Division of security duties between Google and customers |
| Authentication & Authorization | Kubernetes RBAC, Google Cloud IAM integration, service account mapping |
| Control Plane & Node Hardening | Securing the Kubernetes API server, node configuration, and credential management |
| Network Security | VPC-native clusters, network policies, audit logging for visibility |
| Data Protection | Encryption at rest, in transit, and in use via Google Cloud encryption services |
## 1. Shared Responsibility Model
Understanding who manages which layer of the stack is fundamental to securing GKE workloads.
* Google Cloud is responsible for the underlying infrastructure, control plane, and host OS patching.
* You, the customer, manage your container images, Kubernetes configurations, network policies, and workload permissions.
Misconfiguring your side of the shared responsibility model can expose your applications to threats. Always verify IAM roles and network policies.
## 2. Authentication and Authorization
Securing access to your cluster begins with strong identity controls:
* **Kubernetes RBAC**\
Define Roles and RoleBindings to grant fine-grained permissions within your cluster.
* **Google Cloud IAM**\
Assign IAM roles at the project, folder, or organization level to control who can create and manage clusters.
* **Service Account Mapping**\
Link Kubernetes ServiceAccounts to Google Service Accounts for workload identity and least-privilege access.
## 3. Control Plane and Node Hardening
Locking down your control plane and nodes ensures that only trusted workloads and administrators can interact with your cluster:
* Enable private clusters and restrict public endpoint access.
* Use Binary Authorization to enforce image attestation.
* Rotate and securely store cluster credentials.
## 4. Network Security
Effective network controls help prevent lateral movement and data exfiltration:
* Leverage VPC-native clusters to use [VPC Service Controls](https://cloud.google.com/vpc-service-controls) and private IPs.
* Define Kubernetes NetworkPolicies to restrict pod-to-pod communication.
* Enable VPC Flow Logs and Cloud Audit Logs for full visibility.
## 5. Data Protection
Protect sensitive information throughout its lifecycle:
* **At Rest**: Use Google-managed encryption keys or bring your own keys (BYOK) with Cloud Key Management Service.
* **In Transit**: Enforce TLS for all service-to-service and client-to-cluster communications.
* **In Use**: Explore Confidential GKE nodes to keep data encrypted even during processing.
***
By the end of this lesson, you’ll have a clear roadmap for implementing GKE security best practices across all layers of your cluster architecture. Proceed to the next section to dive into the Shared Responsibility Model in detail.