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NEW QUESTION # 317
What is the order of 4C's in Cloud Native Security, starting with the layer that a user has the most control over?
Answer: A
Explanation:
The Cloud Native Security "4C's" model is commonly presented as Code, Container, Cluster, Cloud, ordered from the layer you control most directly to the one you control least-therefore D is correct. The idea is defense-in-depth across layers, recognizing that responsibilities are shared between developers, platform teams, and cloud providers.
Code is where users have the most direct control: application logic, dependencies, secure coding practices, secrets handling patterns, and testing. This includes validating inputs, avoiding vulnerabilities, and scanning dependencies. Next is the Container layer: building secure images, minimizing image size/attack surface, using non-root users, setting file permissions, and scanning images for known CVEs. Container security is about ensuring the artifact you run is trustworthy and hardened.
Then comes the Cluster layer: Kubernetes configuration and runtime controls, including RBAC, admission policies (OPA/Gatekeeper), Pod Security standards, network policies, runtime security, audit logging, and node hardening practices. Cluster controls determine what can run and how workloads interact. Finally, the Cloud layer includes the infrastructure and provider controls-IAM, VPC/networking, KMS, managed control plane protections, and physical security-which users influence through configuration but do not fully own.
The model's value is prioritization: start with what you control most (code), then harden the container artifact, then enforce cluster policy and runtime protections, and finally ensure cloud controls are configured properly.
This layered approach aligns well with Kubernetes security guidance and modern shared-responsibility models.
NEW QUESTION # 318
In Kubernetes, what is the primary purpose of using annotations?
Answer: C
Explanation:
Annotations in Kubernetes are a flexible mechanism for attaching non-identifying metadata to Kubernetes objects. Their primary purpose is to store additional information that is not used for object selection or grouping, which makes Option B the correct answer.
Unlike labels, which are designed to be used for selection, filtering, and grouping of resources (for example, by Services or Deployments), annotations are intended purely for informational or auxiliary purposes. They allow users, tools, and controllers to store arbitrary key-value data on objects without affecting Kubernetes' core behavior. This makes annotations ideal for storing data such as build information, deployment timestamps, commit hashes, configuration hints, or ownership details.
Annotations are commonly consumed by external tools and controllers rather than by the Kubernetes scheduler or control plane for decision-making. For example, ingress controllers, service meshes, monitoring agents, and CI/CD systems often read annotations to enable or customize specific behaviors. Because annotations are not used for querying or selection, Kubernetes places no strict size or structure requirements on their values beyond general object size limits.
Option A is incorrect because access permissions are managed using Role-Based Access Control (RBAC), which relies on roles, role bindings, and service accounts-not annotations. Option C is incorrect because deployment strategies (such as RollingUpdate or Recreate) are defined in the specification of workload resources like Deployments, not through annotations. Option D is also incorrect because resource limits and requests are specified explicitly in the Pod or container spec under the resources field.
In summary, annotations provide a powerful and extensible way to associate metadata with Kubernetes objects without influencing scheduling, selection, or identity. They support integration, observability, and operational tooling while keeping core Kubernetes behavior predictable and stable. This design intent is clearly documented in Kubernetes metadata concepts, making Option B the correct and verified answer.
NEW QUESTION # 319
Open Container Initiative set container standards for
Answer: D
NEW QUESTION # 320
What happens with a regular pod running in Kubernetes when a node fails?
Answer: D
Explanation:
When a node fails, Kubernetes schedules a new pod with a different UID (a new instance) on another available node to replace the failed pod.
NEW QUESTION # 321
You are using Istio to manage traffic flow in a microservices architecture. Your application consists of three services: 'service-A', 'service-B', and 'service-C', where 'service-A' depends on 'service-B' and 'service-B' depends on 'service-C'. You want to implement a canary rollout for 'service-B' to test a new version before rolling it out to all users. How would you configure Istio to achieve this?
Answer: C
Explanation:
Istio's VirtualService allows you to define routing rules that can direct a percentage of traffic to a specific version of a service- This enables you to perform canary rollouts by gradually introducing the new version of 'service-B' to a subset of users- Option A is not a valid Istio configuration option- Option C creates unnecessary complexity Option D is related to retries, not canary rollouts. Option E is closer but doesn't specify the percentage split.
NEW QUESTION # 322
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