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| Section | Objectives |
|---|---|
| Cloud Security and Governance | - Security fundamentals in cloud native systems
|
| Container Orchestration | - Container lifecycle and scheduling
|
| Cloud Native Application Delivery | - CI/CD and deployment strategies
|
| Cloud Native Architecture | - Microservices and distributed systems
|
| Cloud Native Observability | - Monitoring and logging
|
| Kubernetes Fundamentals | - Core Kubernetes concepts
|
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NEW QUESTION # 209
Which type of Service requires manual creation of Endpoints?
Answer: C
Explanation:
A Kubernetes Service without selectors requires you to manage its backend endpoints manually, so B is correct. Normally, a Service uses a selector to match a set of Pods (by labels). Kubernetes then automatically maintains the backend list (historically Endpoints, now commonly EndpointSlice) by tracking which Pods match the selector and are Ready. This automation is one of the key reasons Services provide stable connectivity to dynamic Pods.
When you create a Service without a selector, Kubernetes has no way to know which Pods (or external IPs) should receive traffic. In that pattern, you explicitly create an Endpoints object (or EndpointSlices, depending on your approach and controller support) that maps the Service name to one or more IP:port tuples. This is commonly used to represent external services (e.g., a database running outside the cluster) while still providing a stable Kubernetes Service DNS name for in-cluster clients. Another use case is advanced migration scenarios where endpoints are controlled by custom controllers rather than label selection.
Why the other options are wrong: Service types like ClusterIP, NodePort, and LoadBalancer describe how a Service is exposed, but they do not inherently require manual endpoint management. A ClusterIP Service with selectors (D) is the standard case where endpoints are automatically created and updated. NodePort and LoadBalancer Services also typically use selectors and therefore inherit automatic endpoint management; the difference is in how traffic enters the cluster, not how backends are discovered.
Operationally, when using Services without selectors, you must ensure endpoint IPs remain correct, health is accounted for (often via external tooling), and you update endpoints when backends change. The key concept is: no selector # Kubernetes can't auto-populate endpoints # you must provide them.
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NEW QUESTION # 210
You are monitoring a Kubernetes cluster using Prometheus. You notice a sudden spike in the number of requests to a specific pod, followed by a corresponding increase in pod CPU utilization. Which Prometheus query can you use to identify the specific endpoint being heavily accessed?
Answer: E
Explanation:
The correct answer is E . The query 'kube_http_server_requests_seconds_bucket{job="", method="GET", uri="/specific_endpoint"}" targets HTTP requests made to a specific endpoint within a pod (identified by the •job', •method', and 'uri' labels). This query allows you to see the number of requests made to the '/specific_endpoint• and identify spikes in traffic to that endpoint. The other options are not relevant to identifying specific endpoints being heavily accessed. Option A shows CPU resource requests for a pod, option B shows the pod's phase, option C shows the number of replicas in a deployment, and option D shows the restart count for a pod's containers. These queries do not provide information about specific endpoints and traffic patterns.
NEW QUESTION # 211
You are implementing a new security policy for your Kubernetes cluster. The policy requires that all pods running in the cluster must authenticate with a specific identity provider before they are allowed to access any resources. Which Kubernetes component is responsible for enforcing this authentication policy?
Answer: C
Explanation:
The kube-apiserver component acts as the central control plane for Kubernetes. It handles all communication and requests from other components, including authentication and authorization. It enforces security policies by verifying credentials and granting access based on configured rules.
NEW QUESTION # 212
Which of the following sentences is true about namespaces in Kubernetes?
Answer: D
Explanation:
The true statement is C: the default namespace exists when a new cluster is created. Namespaces are a Kubernetes mechanism for partitioning cluster resources into logical groups. When you set up a cluster, Kubernetes creates some initial namespaces (including default, and commonly kube-system, kube-public, and kube-node-lease). The default namespace is where resources go if you don't specify a namespace explicitly.
Option A is false because namespaces are not hierarchical; Kubernetes does not support "namespaces inside namespaces." Option B is false because within a given namespace, resource names must be unique per resource kind. You can't have two Deployments with the same name in the same namespace. You can have a Deployment named web in one namespace and another Deployment named web in a different namespace- namespaces provide that scope boundary. Option D is false because not all objects are namespaced. Many resources are cluster-scoped (for example, Nodes, PersistentVolumes, ClusterRoles, ClusterRoleBindings, and StorageClasses). Namespaces apply only to namespaced resources.
Operationally, namespaces support multi-tenancy and environment separation (dev/test/prod), RBAC scoping, resource quotas, and policy boundaries. For example, you can grant a team access only to their namespace and enforce quotas that prevent them from consuming excessive CPU/memory. Namespaces also make organization and cleanup easier: deleting a namespace removes most namespaced resources inside it (subject to finalizers).
So, the verified correct statement is C: the default namespace exists upon cluster creation.
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NEW QUESTION # 213
Which field in a Pod or Deployment manifest ensures that Pods are scheduled only on nodes with specific labels?
Answer: A
Explanation:
In Kubernetes, Pod scheduling is handled by the Kubernetes scheduler, which is responsible for assigning Pods to suitable nodes based on a set of constraints and policies. One of the simplest and most commonly used mechanisms to control where Pods are scheduled is the nodeSelector field. The nodeSelector field allows you to constrain a Pod so that it is only eligible to run on nodes that have specific labels.
Node labels are key-value pairs attached to nodes by cluster administrators or automation tools. These labels typically describe node characteristics such as hardware type, disk type, geographic zone, or environment. For example, a node might be labeled with disktype=ssd to indicate that it has SSD-backed storage. When a Pod specification includes a nodeSelector with the same key-value pair, the scheduler will only consider nodes that match this label when placing the Pod.
Option A (resources) is incorrect because resource specifications are used to define CPU and memory requests and limits for containers, not to influence node selection based on labels. Option B (labels) is also incorrect because Pod labels are metadata used for identification, grouping, and selection by other Kubernetes objects such as Services and Deployments; they do not affect scheduling decisions. Option D (annotations) is incorrect because annotations are intended for storing non-identifying metadata and are not interpreted by the scheduler for placement decisions.
The nodeSelector field is evaluated during scheduling, and if no nodes match the specified labels, the Pod will remain in a Pending state. While nodeSelector is simple and effective, it is considered a basic scheduling mechanism. For more advanced scheduling requirements-such as expressing preferences, using set-based matching, or combining multiple conditions-Kubernetes also provides node affinity and anti-affinity.
However, nodeSelector remains a foundational and widely used feature for enforcing strict node placement based on labels, making option C the correct and verified answer according to Kubernetes documentation.
NEW QUESTION # 214
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