Secure cloud-native applications by protecting every stage of their lifecycle: design and development, software distribution, deployment, and runtime. For Kubernetes workloads, that means understanding trust boundaries, controlling what enters a cluster and who can change it, limiting each workload’s identity and privileges, and protecting APIs, network traffic, data, and operational records. The right controls depend on the application and cluster; no checklist is universal.
Start with the application’s risks and trust boundaries
Begin with a threat model, not a product list. Identify the application’s components, the data they handle, the people and services that can reach them, and the boundaries where trust changes—for example, between a public-facing service and an internal database. Use those risks to decide which controls matter most, and revisit the model when the design or dependencies change.
Kubernetes’ cloud-native security guidance treats secure design and development as part of the same problem as deployment and runtime protection. Its Application Security Checklist is a useful developer reference, but Kubernetes says it is not exhaustive or one-size-fits-all. Include end-user security needs as well as platform and code risks.
Secure code, dependencies, and software artifacts
Containers do not remove the risks in the software they package. Scan images and other build artifacts for known vulnerabilities, track dependencies, and respond to security announcements with updates. A scan is a point-in-time check, not proof that an artifact is safe; keep the process connected to dependency maintenance and release decisions.
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- Protect distribution: use trusted, encrypted artifact distribution and restrict registry access to authorized clients.
- Preserve the chain of trust: validate artifact provenance or certificates where appropriate, and control who can publish or replace images.
- Make deployment use the artifacts you reviewed: restrict what may be deployed and who may deploy it, rather than relying only on controls at build time.
Kubernetes discusses these measures as part of cloud-native security, while NIST SP 800-190 focuses specifically on application-container security. NIST’s publication record dates SP 800-190 to September 2017; it is a container-focused guide, not a complete treatment of every Kubernetes or API security concern. See the NIST SP 800-190 publication record.
Constrain what can be deployed and where it can run
Deployment controls should answer three questions: which workloads are permitted, which identities may submit or change them, and where those workloads may run. Use namespaces to separate applications or cluster components when that separation supports the design, and apply appropriate workload security standards. Admission controls can constrain API changes before they are accepted; Kubernetes documents mechanisms including ValidatingAdmissionPolicy in its security overview.
Choose controls according to the consequences of a deployment mistake or compromise. A policy that blocks an application’s required behavior can disrupt service, while a policy with broad exceptions may provide little protection. Test proposed restrictions against the workload and keep exceptions deliberate and reviewable.
Give each workload only the identity and privilege it needs
A Kubernetes ServiceAccount gives a workload an identity for interacting with the Kubernetes API. Avoid using the default ServiceAccount indiscriminately: create workload-specific accounts and disable automatic token mounting when the application does not need API access. The application checklist also recommends non-root execution, disabling privilege escalation, using a read-only root filesystem where compatible, avoiding privileged containers, and dropping capabilities the workload does not require.
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For example, the following Pod-level settings illustrate several of those controls. They are not a complete manifest: define the referenced ServiceAccount and container image, and adapt the settings to the application and cluster.
apiVersion: v1
kind: Pod
metadata:
name: example
spec:
serviceAccountName: example
automountServiceAccountToken: false
containers:
- name: app
image: registry.example/app:version
securityContext:
runAsNonRoot: true
runAsUser: 10001
allowPrivilegeEscalation: false
readOnlyRootFilesystem: true
capabilities:
drop:
- ALLUse a non-root UID and GID appropriate to the image and workload. A read-only root filesystem can require changes if the application writes temporary files or state; provide only the writable locations it needs rather than abandoning the control without review. If a workload needs Kubernetes API access, grant only the necessary permissions to its dedicated identity instead of disabling access controls or reusing a broadly privileged account. These recommendations follow the Kubernetes Application Security Checklist.
Protect Kubernetes APIs and application network paths
Kubernetes identifies API protection as central to cluster security. Protect API access with authentication and authorization, and use TLS for API traffic within the control plane and between the control plane and clients. For cloud-native applications that expose APIs, assess risks during both development and runtime: the NIST SP 800-228 March 2026 update, published March 13, 2026, focuses on API protection for cloud-native systems and describes an incremental, risk-based approach.
Use NetworkPolicy to express which traffic should be allowed between workloads, but verify that the cluster’s network implementation enforces those policies. A policy object alone does not establish that traffic is being filtered. Start from the application’s expected flows, then permit only those paths that are needed; account for legitimate dependencies such as service-to-service calls and operational access.
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Runtime protection reduces the impact of a compromise and helps responders understand what happened. Select a container runtime that meets the workload’s information-security needs; Kubernetes does not prescribe one. On Linux, consider mechanisms such as seccomp or AppArmor, and separate workloads by trust context where isolation requirements justify it.
- Protect stored data: consider storage encryption and encryption at rest for Kubernetes API objects, based on the data’s sensitivity and assurance requirements.
- Prove recovery works: maintain backups and verify restoration through exercises, rather than assuming that a successful backup job guarantees recoverability.
- Protect evidence: preserve the integrity and confidentiality of logs and monitoring data when incident response or assurance requirements depend on them.
These measures complement, rather than replace, controls on identity, deployment, and network access. Kubernetes’ cloud-native security overview covers lifecycle-wide concerns, and its application checklist was last modified November 6, 2024, according to the page.
Choose controls by risk, compatibility, and operating cost
There is no single security control or vendor tool that addresses every cloud-native threat. When comparing implementation options, consider:
- Threat and lifecycle stage: does the control address a design, artifact, deployment, API, network, or runtime risk?
- Workload compatibility: what application changes or exceptions are needed, and can they be kept narrow?
- Operational effort: who will enforce, monitor, update, and troubleshoot the control?
- Trust and data sensitivity: is the control proportionate to the workload’s exposure and the consequences of compromise?
Use guidance with a scope that matches the question: Kubernetes documentation for Kubernetes mechanisms, NIST SP 800-190 for application-container concerns, and NIST SP 800-228’s March 2026 update for cloud-native API protection. They complement one another rather than providing interchangeable checklists.
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