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Pod Sandboxing in Kubernetes

Required knowledge for the CKS certification.

What is Pod Sandboxing?​

Pod sandboxing is a security technique that enhances isolation between workloads running in Kubernetes. It reduces the risk of container breakout attacks, ensures stronger multi-tenancy, and limits the impact of compromised pods.

In a standard Kubernetes environment, pods share the underlying kernel of the host system. Pod sandboxing introduces additional layers of isolation, preventing malicious workloads from impacting the host or other workloads.

Why Use Pod Sandboxing?​

Pod sandboxing is particularly useful in the following scenarios:

  • Multi-Tenancy: Running workloads from different users or teams on shared clusters.
  • High-Security Workloads: Protecting sensitive applications from compromise.
  • Zero Trust Architectures: Restricting access between workloads and enforcing strict security policies.

By using pod sandboxing, organizations can prevent privilege escalation, reduce attack surfaces, and improve workload security.

Approaches to Pod Sandboxing​

1. Kata Containers​

Required knowledge for the CKS certification.

Kata Containers provide hardware-virtualized isolation by running each pod inside a lightweight virtual machine (VM). This creates an extra security boundary between the workload and the host.

Example: Deploying a Pod with Kata Containers​

apiVersion: v1
kind: Pod
metadata:
  name: kata-pod
  annotations:
    io.kubernetes.cri.untrusted-workload: "true"
spec:
  runtimeClassName: kata-containers
  containers:
    - name: app-container
      image: nginx

Benefits:

  • Provides VM-level isolation while maintaining Kubernetes compatibility.
  • Ideal for running untrusted workloads in multi-tenant environments.

2. gVisor​

Required knowledge for the CKS certification.

gVisor is a user-space kernel designed to sandbox workloads by intercepting and handling syscalls in a controlled environment.

Example: Deploying a Pod with gVisor​

apiVersion: v1
kind: Pod
metadata:
  name: gvisor-pod
spec:
  runtimeClassName: gvisor
  containers:
    - name: app-container
      image: nginx

Benefits:

  • Runs applications in a highly restricted user-space kernel.
  • Limits the attack surface by preventing direct host kernel access.
  • Ideal for lightweight sandboxing with minimal performance impact.

3. Firecracker​

Firecracker is a lightweight microVM technology designed for serverless computing and secure container execution.

Key Features:

  • Provides strong isolation using KVM-based microVMs.
  • Used by services like AWS Lambda and Fargate.
  • Optimized for fast startup times and low resource overhead.

Firecracker-based runtimes, such as AWS Firecracker-containerd, can be integrated into Kubernetes for secure multi-tenant workloads.

4. Using RuntimeClass for Sandboxing​

Required knowledge for the CKS certification.

Kubernetes allows selecting different runtimes for workloads using RuntimeClass.

apiVersion: node.k8s.io/v1
kind: RuntimeClass
metadata:
  name: sandboxed
handler: kata-containers

By associating pods with a specific RuntimeClass, Kubernetes can enforce sandboxed execution environments.

apiVersion: v1
kind: Pod
metadata:
  name: sandboxed-pod
spec:
  runtimeClassName: sandboxed
  containers:
    - name: secure-container
      image: alpine

This method ensures that workloads requiring extra isolation can run securely without affecting the host.

Best Practices for Pod Sandboxing​

  • Use Kata Containers or Firecracker for workloads requiring strong hardware isolation.
  • Deploy gVisor for lightweight syscall filtering and restricted execution.
  • Limit pod privileges using Pod Security Standards (PSS).
  • Combine pod sandboxing with seccomp and AppArmor for defense-in-depth security.
  • Use RuntimeClass to enforce sandboxed execution where necessary.

Conclusion​

Pod sandboxing is an essential technique for securing multi-tenant Kubernetes clusters and high-security workloads. By leveraging technologies like Kata Containers, gVisor, and Firecracker, organizations can reduce the risk of container breakouts, **limit exposure to host reso

Last updated on by Itai Ganot