1. Code
At the heart of cloud native security lies the code itself—the foundation of any application. Secure coding practices must be a top priority from day one. Developers need to follow principles such as input validation, proper error handling, least privilege access, and rigorous authentication and authorization checks. This also includes avoiding common vulnerabilities like SQL injection, cross-site scripting (XSS), and command injection. Tools like static application security testing (SAST) and dynamic application security testing (DAST) help identify vulnerabilities early in the development cycle. Incorporating security into CI/CD pipelines through automated code scanning and dependency checks is crucial to "shift left" and catch issues before they reach production.A good example of secure code practices in action is a developer using a CI pipeline that automatically scans each pull request for vulnerabilities using tools like SonarQube or Snyk. Suppose a developer introduces a third-party library for logging—before merging, the pipeline identifies a critical vulnerability in that library version. By failing the build and alerting the team, the pipeline prevents that risk from entering production. Additionally, developers can use tools like GitGuardian to detect hardcoded secrets in repositories, ensuring sensitive data like API keys never leaks.
2. Container
Once secure code is written, it is packaged into containers, which are lightweight, portable environments for application deployment. The security of containers is vital because a compromised container can impact the underlying system or other services running in the same environment. Best practices include using minimal base images (e.g., Alpine Linux) to reduce the attack surface, scanning container images for vulnerabilities using tools like Trivy or Clair, and ensuring that containers run as non-root users whenever possible. Containers should also be signed and verified to guarantee their integrity and origin.For instance, imagine a team deploying a Node.js microservice inside a container. Instead of using a general-purpose Ubuntu base image, they choose a stripped-down Node.js Alpine image to reduce vulnerabilities. They also configure Dockerfiles to drop root privileges and enforce strict runtime permissions. During the build process, they integrate Trivy to scan the image for known CVEs (Common Vulnerabilities and Exposures). If a vulnerability is detected in the image's OpenSSL dependency, the build fails, prompting the team to update the base image or patch the dependency before proceeding.
3. Cluster
The cluster layer refers to the orchestration environment, commonly Kubernetes, where containers are scheduled and managed. Securing the cluster involves hardening its configuration, enforcing least-privilege access via Kubernetes RBAC (Role-Based Access Control), applying network policies to control traffic between pods, and using Pod Security Admission (PSA) to prevent insecure pod configurations. Secrets should be stored using secure backends such as HashiCorp Vault or cloud-native secrets managers, not in plain-text ConfigMaps or environment variables.Consider a Kubernetes cluster hosting multiple microservices for an e-commerce platform. To prevent lateral movement, the security team defines network policies that restrict communication between pods to only what is necessary. They also use Open Policy Agent (OPA) with Gatekeeper to enforce compliance rules—such as denying deployments that mount host volumes or run as root. To ensure secure authentication, access to the Kubernetes API server is managed through federated identity providers, and actions are audited via Kubernetes audit logs. All of this ensures that the cluster acts as a secure boundary for container workloads.
4. Cloud (Infrastructure)
The outermost layer is the cloud or infrastructure level, which encompasses the underlying compute, storage, and networking resources provided by cloud service providers like AWS, Azure, or Google Cloud. At this layer, security practices include configuring Identity and Access Management (IAM) roles with least privilege, securing APIs and endpoints, encrypting data at rest and in transit, and implementing firewalls or security groups to control network access. Infrastructure-as-Code (IaC) tools like Terraform and CloudFormation should be scanned for misconfigurations that could lead to data leaks or privilege escalation.For example, an organization running workloads in AWS might use IAM roles to restrict S3 access to only the services that need it, avoiding wide-open permissions like
s3:*. They might also use AWS Config or Azure Policy to continuously monitor for drift from security baselines, such as ensuring that public S3 buckets or unencrypted EBS volumes trigger alerts. CloudTrail or equivalent logging services are enabled to provide audit trails of all infrastructure activity. This visibility allows security teams to detect suspicious behaviors—such as repeated access attempts from unknown IPs—and take proactive measures to contain threats.Together, the 4 Cs—Code, Container, Cluster, and Cloud—form a comprehensive framework for securing cloud native applications. Each layer reinforces the next, and overlooking any one of them can expose the entire system to risk. A holistic security strategy must therefore integrate policies, tools, and practices across all four dimensions.