Certified Kubernetes Administrator CKA (CKA) — Questions 226–300

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Option B is wrong because removing the taint from the control-plane node does not solve the memory shortage on the three worker nodes; it only makes the control-plane node schedulable, but that node also has a taint that the pod does not tolerate, so it would still be unavailable unless a toleration is added. Option C is wrong because adding a toleration for the control-plane taint would allow the pod to schedule on the control-plane node, but that node also has insufficient memory (as implied by '0/4 nodes are available'), so it would not fix the pending state. Option D is wrong because setting nodeSelector to control-plane nodes would force scheduling on a node that is tainted and likely has insufficient memory, and the pod does not tolerate the taint, so it would remain pending.

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Option B (Pending) is wrong because the pod has already started executing its init containers; it is not stuck waiting for scheduling or image pull. Option C (Failed) is wrong because a pod enters the Failed phase only when all its containers have terminated and the pod will not be restarted (e.g., a non-init container with restart policy Never), but here the init container will be retried. Option D (Running) is wrong because the pod's init container has not completed successfully, so the pod's status cannot be Running; the pod remains in a waiting state until all init containers succeed.

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Option A is wrong because allowedTopologies in a StorageClass is used with Immediate binding mode to restrict provisioning to specific zones, but with WaitForFirstConsumer, the PV is provisioned on the node where the Pod is scheduled, not necessarily on a node matching allowedTopologies unless the scheduler enforces it. Option C is wrong because the PV is not provisioned on 'any node with sufficient resources'; it is specifically provisioned on the node where the Pod is scheduled, and the scheduler considers topology constraints from the PVC and StorageClass. Option D is wrong because the control plane node is not involved in PV provisioning for WaitForFirstConsumer; the PV is provisioned on the worker node where the Pod runs, not on the control plane.

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Option A is wrong because it defines a ClusterRole, which is cluster-scoped and not namespace-scoped; while a ClusterRole can be used to grant permissions across namespaces, the requirement specifically asks for a Role in the 'dev' namespace. Option B is wrong because it defines a RoleBinding, which binds a Role to a user but does not define the Role itself; the question asks for the Role definition, not the binding. Option D is wrong because it defines a Role with the verb 'get' instead of 'list'; 'get' allows retrieving a specific pod by name, but the requirement is to list pods, which requires the 'list' verb.

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Option A is wrong because `kubectl logs test-pod` retrieves container logs, but the pod is in 'Pending' state and has not started any containers, so there are no logs to fetch; this command would fail with an error like 'container is waiting to start'. Option C is wrong because `kubectl exec -it test-pod -- /bin/bash` attempts to execute a command inside a running container, but since the pod is not running (Pending), there is no container to attach to, and the command will fail. Option D is wrong because `kubectl get events` shows cluster-wide events, which may include relevant information but is less targeted than `kubectl describe pod`; it requires filtering through many events and may not show pod-specific details like scheduler failure reasons or volume binding errors as clearly.

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Option A is wrong because it suggests draining all nodes before upgrading, but the control plane must be upgraded first, not simultaneously with workers. Option C is wrong because upgrading worker nodes before the control plane would break cluster coordination, as the API server version must be higher or equal to kubelet versions. Option D is wrong because upgrading all nodes simultaneously is not supported with kubeadm; it would cause version mismatches and potential cluster downtime.

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Option A is wrong because a DaemonSet ensures that a copy of a Pod runs on every node (or a subset of nodes) in the cluster, which is designed for continuous daemon processes like logging or monitoring, not a one-time initialization task. Option C is wrong because a Deployment manages a set of Pods to maintain a desired state with rolling updates and self-healing, intended for long-running stateless applications, not a single run-to-completion job. Option D is wrong because a CronJob is used for scheduling Jobs to run at specific times or intervals, which is overkill and incorrect for a task that should run only once immediately.

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Option B (kube-scheduler) is wrong because it is responsible for assigning Pods to nodes based on resource availability and scheduling policies, not for maintaining network rules. Option C (kubelet) is wrong because it is the primary node agent that manages Pod lifecycle, container health, and mounts volumes, but it does not handle network rule enforcement. Option D (kube-controller-manager) is wrong because it runs controller processes such as the Node Controller, Replication Controller, and Endpoint Controller, but it does not implement per-node network rules.

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Option A is wrong because 'Device' is not a valid volume mode in Kubernetes; the valid modes are 'Filesystem' and 'Block'. Option B is wrong because 'Raw' is not a recognized volume mode; the correct term is 'Block' for raw block device access. Option D is wrong because 'Filesystem' is the default volume mode, which mounts a filesystem (e.g., ext4) and does not expose the device as a raw block device.

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Option A is wrong because `kubectl get pods -o wide` only shows pod IPs and node assignments, not CPU or memory usage. Option C is wrong because `kubectl logs pods` fetches container logs, not resource metrics. Option D is wrong because `kubectl describe pods` provides detailed pod configuration and status but does not include live CPU or memory utilization data.

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Option B is wrong because 'kubeadm reset --force' is used to tear down a cluster or reinitialize it, not to configure kubectl; running it would destroy the cluster state. Option C is wrong because it copies the admin.conf to /root/.kube/config, which only configures kubectl for the root user, not for the current admin user; the CKA environment typically expects non-root usage. Option D is wrong because it references /etc/kubernetes/pki/admin.conf, which does not exist — the admin kubeconfig is located at /etc/kubernetes/admin.conf, not in the pki directory.

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Option A is wrong because the service does not remove all endpoints; it only removes the unhealthy pod, preserving connectivity via the healthy pods. Option C is wrong because the service endpoints do not include the unhealthy pod; the endpoint controller removes pods that fail readiness probes, so the pod is not present in the endpoint list at all. Option D is wrong because the service does not include all three pods; the CrashLoopBackOff pod is excluded from endpoints due to its failed readiness probe.

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Option B is wrong because kubelet is the agent that runs on each node and ensures containers are running in a pod, but it does not decide which node a pod should be scheduled on. Option C is wrong because kube-apiserver is the front-end for the Kubernetes control plane and handles API requests, but it does not perform scheduling decisions. Option D is wrong because kube-controller-manager runs controller processes like replication controller and node controller, but pod-to-node assignment is the scheduler's responsibility.

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Option A is wrong because `volumeBindingMode: Immediate` does not require a specific access mode; it simply means binding and provisioning happen as soon as the PVC is created, regardless of pod scheduling. Option C is wrong because the PVC can still be created and bound even if it does not specify an access mode; the access mode is a required field in the PVC spec, but its absence would cause a validation error, not a Pending state after creation. Option D is wrong because the `reclaimPolicy: Delete` does not prevent binding; it only determines what happens to the PV when the PVC is deleted, and has no effect on the initial binding process.

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Option A is wrong because a DaemonSet ensures that a copy of a Pod runs on all (or a subset of) nodes, providing continuous background services like logging or monitoring, not a one-time batch job. Option B is wrong because a CronJob is used for scheduling recurring tasks at specified times (e.g., every hour), not for a single execution. Option C is wrong because a Deployment manages a set of replica Pods intended to run indefinitely, maintaining a desired state with rolling updates, not a finite task that exits.

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Option A is wrong because `class` is not a valid field in a PVC spec; it is a legacy term from earlier versions and is not recognized by the Kubernetes API. Option B is wrong because `storageClass` (camelCase) is not the correct field name; the API uses `storageClassName` (all lowercase with 'Name' appended). Option C is wrong because `className` is not a field in the PVC spec; it might be confused with a field in other Kubernetes resources (e.g., Ingress) but does not apply to PVCs.

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Option A is wrong because using environment variables is a different mechanism that does not address the requirement to mount a ConfigMap as a volume; it also exposes all keys as environment variables unless you manually specify each key, which is not the best approach for selective file projection. Option C is wrong because mounting the entire ConfigMap and then using a startup script to remove unwanted files is an anti-pattern that wastes resources, adds complexity, and violates the principle of declarative configuration. Option D is wrong because creating a new ConfigMap with only the needed keys duplicates data and increases management overhead, whereas the `items` field achieves the same goal without creating additional objects.

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Option B is wrong because `kubectl exec -it mypod -- sh` attempts to start an interactive shell in a running container, but the pod is in `CrashLoopBackOff` and the container is not running, so exec will fail with an error like 'cannot exec into a container in a crashed state'. Option C is wrong because deleting and recreating the pod will lose the previous container's logs and crash history, making debugging harder; it is a reactive restart, not a diagnostic step. Option D is wrong because `kubectl describe pod mypod` shows pod events and status but does not provide the application-level error output from the crashed container; it is useful for infrastructure issues but not for application crash logs.

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Option B is wrong because it uses a ClusterRole and ClusterRoleBinding, which grant permissions cluster-wide (across all namespaces), not just in the 'app' namespace as required. Option C is wrong because it uses a ClusterRole with a RoleBinding; while a RoleBinding can reference a ClusterRole, the binding itself is namespaced, but the ClusterRole's scope is still cluster-wide, which is unnecessarily broad and not the minimal required RBAC for a single namespace. Option D is wrong because the Role is defined in the 'default' namespace, not in the 'app' namespace, so the RoleBinding in 'app' cannot reference a Role from a different namespace; Role and RoleBinding must be in the same namespace.

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Option A is wrong because preemption does not wait for the lower-priority pod to complete; it actively evicts it to schedule the higher-priority pod. Option B is wrong because preemption is enabled by default in Kubernetes (the 'Preemption' plugin is active in the default scheduler configuration), so Pod A will not remain pending if a lower-priority pod can be evicted. Option C is wrong because the scheduler automatically handles preemption without manual intervention from the cluster administrator.

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Option A is wrong because increasing the number of replicas does not resolve the underlying scheduling constraints—it only creates more pods that will also remain Pending. Option C is wrong because removing the control-plane taint from control plane nodes is not recommended; those nodes are typically reserved for system components and removing the taint could lead to resource contention or security issues. Option D is wrong because adding a toleration for the control-plane taint would only address the taint issue on two nodes, but the pod would still fail to schedule on the third node due to the anti-affinity conflict.

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Option B is wrong because deleting the namespace and redeploying all workloads is an extreme, disruptive action that does not fix the underlying memory limit issue and would cause unnecessary downtime for all workloads in the namespace. Option C is wrong because deleting and recreating the pod will only restart the container with the same memory limit, resulting in the same OOMKilled crash and continued CrashLoopBackOff. Option D is wrong because increasing the CPU request does not affect memory constraints; the OOMKilled error is caused by exceeding the memory limit, not CPU resources.

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Option B is wrong because if the pod lacked network access to the mysql service, the error would typically be a timeout or 'no route to host', not a specific connection refusal to 10.0.0.1:3306; the pod can reach the IP but the database isn't listening there. Option C is wrong because the mysql service is explicitly stated to run on port 3306, and the error shows the app is attempting port 3306, so the port exposure is not the issue. Option D is wrong because if the database pod were not running, the service would have no endpoints, and the connection attempt would result in a 'connection refused' or timeout, but the error specifically mentions a hardcoded IP (10.0.0.1) rather than the service DNS name, indicating a configuration problem, not a pod status issue.

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Option A is wrong because missing resource requests would cause the scheduler to fail with a different error message, such as 'Insufficient cpu' or 'Insufficient memory', not a taint-related message. Option C is wrong because a cordoned node would show 'node(s) were cordoned' or 'node(s) had taint node.kubernetes.io/unschedulable' in the describe output, not a taint about node-role.kubernetes.io/master. Option D is wrong because if the kubelet were not running, the node would show as 'NotReady' and the scheduler would report '0/1 nodes are available: 1 node(s) were not ready', not a taint-related message.

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Option B is wrong because `kubectl describe nodes` shows node-level resource capacity, requests, and limits, but does not display actual real-time resource usage of individual pods. Option C is wrong because `kubectl get pods -o wide` only lists pod metadata and IP addresses, not resource usage metrics. Option D is wrong because `kubectl top nodes` shows aggregate node-level CPU and memory usage, not per-pod resource usage.

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Option B is wrong because incorrect search domains in /etc/resolv.conf would cause name resolution failures for short names (e.g., 'kubernetes'), but the fully qualified domain name 'kubernetes.default.svc.cluster.local' would still resolve if the DNS server were reachable; the error here is a connection timeout, not a lookup failure. Option C is wrong because a network policy blocking traffic to the kube-dns service would typically result in a connection refused or timeout, but the question states the service exists and the error is a timeout; however, the most likely cause is the CoreDNS pods not running, as network policies are less common in default clusters and would not prevent the service from having endpoints. Option D is wrong because the DNS name 'kubernetes.default.svc.cluster.local' is a standard Kubernetes service name that exists by default; if it did not exist, nslookup would return 'NXDOMAIN' (non-existent domain), not a connection timeout.

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Option A is wrong because `kubectl config view` displays the entire kubeconfig file contents (clusters, users, contexts) but does not explicitly indicate which context is currently active; it requires manual inspection to find the `current-context` field. Option B is wrong because `kubectl cluster-info` shows information about the cluster the current context points to (e.g., control plane endpoints), not the name of the active context itself. Option C is wrong because `kubectl config get-contexts` lists all available contexts and marks the active one with an asterisk (*) in the output, but it does not directly output just the active context name; it requires parsing the list.

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Option A is wrong because LUKS encrypts the entire disk partition at the filesystem level, which is a valid approach for encrypting etcd data at rest, but the question asks which approach the team should use in the context of a Kubernetes cluster; the recommended and Kubernetes-native method is to use the EncryptionConfiguration resource, not an OS-level disk encryption tool. Option C is wrong because TLS certificates encrypt data in transit between etcd and the API server, not at rest; encryption at rest protects data when it is stored on disk, not during network communication. Option D is wrong because etcd does not have an --experimental-encryption-provider flag; encryption at rest is configured on the kube-apiserver side, not on etcd itself.

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Option B is wrong because `kubectl logs first-pod` only retrieves the container logs from the first pod, which does not test network connectivity to another pod. Option C is wrong because `kubectl top pod first-pod` shows resource usage (CPU/memory) of the first pod, not network connectivity. Option D is wrong because it runs `ping` from the second pod to the first pod's IP, which tests the reverse direction and does not diagnose connectivity from the first pod to the second pod as the question requires.

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Option A is wrong because `kubeadm upgrade plan --certificate-expiration` is not a valid flag; `kubeadm upgrade plan` shows upgrade options, not certificate expiration. Option B is wrong because `kubectl config view --raw | grep client-certificate` only outputs the path or base64-encoded certificate data, not the expiration date; it does not decode or parse the certificate. Option C is wrong because `openssl x509 -in /etc/kubernetes/admin.conf -text -noout` attempts to read a kubeconfig file as a certificate, but `admin.conf` is a YAML file, not a PEM-encoded certificate; the command would fail or produce garbage.

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Option A is wrong because `kubectl get endpoints` retrieves the legacy Endpoints object, not EndpointSlices, and does not use the `--selector` flag to filter by service name. Option B is wrong because `kubectl describe svc` shows the Service's details, including its selector and endpoints, but does not list the individual EndpointSlice objects. Option D is wrong because `kubectl get endpointslices` is not a valid kubectl command (the correct resource name is `endpointslice`, not `endpointslices`), and even if corrected, it would not filter by service name without the `--selector` flag.

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Option B is wrong because `--all-containers` streams logs from all containers in the pod simultaneously, but it does not retrieve logs from a previous (crashed) instance; it only shows current container logs. Option C is wrong because `-p` is the shorthand for `--previous`, so this option is actually correct and identical to A; however, the question expects the explicit `--previous` flag as the answer, and `-p` is not listed as a separate correct choice. Option D is wrong because `kubectl logs pod-name` without any flag only shows logs from the currently running container; in a `CrashLoopBackOff` state, the current container may have just started and has no useful logs, or the command may fail if no container is currently running.

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Option A is wrong because 'kubectl exec' into the etcd container runs etcdctl inside the pod, but it does not automatically provide the necessary TLS certificates or endpoint, and the command lacks the required --cacert, --cert, --key flags, so it will fail to authenticate. Option B is wrong because it runs etcdctl on the host without specifying an endpoint or TLS credentials, so it defaults to the local unix socket or insecure connection, which will not reach the etcd server running as a static pod with TLS enabled. Option D is wrong because it uses an HTTP endpoint (http://localhost:2379) instead of HTTPS, and etcd in a production cluster (including static pods) requires TLS encryption; the connection will be refused or fail authentication.

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Option A is wrong because `kubectl config set-cluster` only modifies or adds a cluster definition (e.g., server URL, certificate authority) in the kubeconfig, it does not change the active context. Option B is wrong because `kubectl config set-context` creates or modifies a context entry (associating a cluster, user, and namespace) but does not switch to it; it only defines the context. Option C is wrong because `kubectl config view` displays the contents of the kubeconfig file (or a merged view) and does not alter the current context.

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Option A is wrong because a LoadBalancer Service exposes the application directly via a cloud load balancer, but it does not terminate TLS natively; TLS termination would require additional configuration (e.g., an external load balancer with TLS support) and the IP may change if the Service is recreated. Option B is wrong because a ClusterIP Service is only accessible within the cluster and cannot expose the application to external users. Option D is wrong because a NodePort Service exposes the application on a static port on each node's IP, but it does not provide a stable IP address (node IPs can change) and does not terminate TLS; TLS termination would require additional components like an Ingress or a reverse proxy.

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Option A is wrong because a misconfigured network plugin (e.g., CNI) would cause pods to fail networking but the kubelet would still be running and the node would typically show 'Ready' with pod issues, not 'NotReady' due to a dead kubelet. Option B is wrong because cordoning a node (via 'kubectl cordon') marks it as 'SchedulingDisabled' but does not stop the kubelet; the node remains 'Ready' and the kubelet service stays active. Option D is wrong because if the container runtime (e.g., containerd or CRI-O) were not installed, the kubelet would fail to start or would crash-loop, but the service would show 'active (running)' or 'failed', not 'inactive (dead)'.

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Option A is wrong because a ClusterRole with 'get' and 'list' verbs on pods, bound via a ClusterRoleBinding, would grant these permissions cluster-wide (across all namespaces), which is excessive for a requirement limited to the 'monitoring' namespace. Option B is wrong because adding the ServiceAccount to the 'cluster-admin' group grants full cluster-wide administrative privileges, violating the principle of least privilege and far exceeding the need to only list pods. Option C is wrong because a Role created in the 'default' namespace cannot grant permissions in the 'monitoring' namespace; RoleBindings only apply within the namespace of the Role, so the binding in 'monitoring' would have no effect.

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Option B is wrong because insufficient resources would cause the pod to remain in a Pending state (not fail to be scheduled entirely), and the DaemonSet controller would still attempt to schedule it; the question states the pod is 'not running,' which could be due to scheduling failure, but resource insufficiency is a less common cause for a new node unless it's explicitly resource-starved. Option C is wrong because a nodeSelector mismatch would prevent scheduling on any node that doesn't match the labels, but the question specifies the DaemonSet is 'configured to run on all nodes,' implying no nodeSelector is set, or if it were, it would affect all nodes equally, not just the new one. Option D is wrong because the update strategy (OnDelete) controls how pods are updated when the DaemonSet template changes, not whether pods are scheduled on new nodes; scheduling is independent of the update strategy.

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Option A is wrong because the `--type=LoadBalancer` flag directly creates a Service of type LoadBalancer; it does not create a ClusterIP that is later changed — the type is set at creation. Option C is wrong because `kubectl expose deployment` derives the label selector from the deployment's pod template labels (e.g., `app=web`), not all pods in the namespace; it does not select all pods. Option D is wrong because the Service exposes port 80 (the Service port), not port 8080 on the node; port 8080 is the target port on the pods, and the NodePort (if any) is dynamically assigned, not explicitly set to 8080.

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Option B is wrong because '500m' is a CPU unit, not a memory unit; memory is expressed in bytes (e.g., Mi, Gi). Option C is wrong because 500m represents 0.5 cores, not 50% of the node's total capacity (which would be 1 core on a 2-core node). Option D is wrong because CPU limits in Kubernetes are not measured in seconds per day; they are enforced as a maximum usage rate (e.g., via CFS quota) over short intervals, not a daily cap.

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Option A is wrong because a ClusterRoleBinding grants permissions cluster-wide, not limited to the namespace of the service account or the binding. Option C is wrong because the ClusterRole 'pod-reader' includes both 'get' and 'list' verbs, so the service account can perform both operations. Option D is wrong because the binding successfully grants the permissions defined in the ClusterRole, so the service account can read pods in all namespaces.

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Option A is wrong because `docker ps` only lists running containers managed by Docker, not the kubelet service itself, and the kubelet may be running as a systemd unit or binary, not a container. Option B is wrong because `kubectl describe node` shows the node's status and conditions from the control plane's perspective, but if the kubelet is down, the API server may have stale data and cannot reveal the actual kubelet process state on the node. Option C is wrong because `kubectl logs kubelet -n kube-system` assumes the kubelet runs as a pod in the cluster, which is not the case—kubelet is a system-level daemon managed by systemd, not a Kubernetes workload, so its logs are accessed via `journalctl` or `systemctl`, not `kubectl logs`.

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Option A is wrong because `nodeAffinity` with `requiredDuringSchedulingIgnoredDuringExecution` is a valid way to select GPU nodes, but it is not sufficient on its own — the Pod must also request the `nvidia.com/gpu` resource to actually get a GPU assigned. Option B is wrong because setting `resources.limits` for `nvidia.com/gpu` alone does not guarantee the Pod lands on a GPU node; without a nodeSelector or affinity, the scheduler may place the Pod on a non-GPU node where the resource is unavailable. Option D is wrong because GPU nodes do not inherently have taints; while administrators may add taints to GPU nodes, a toleration is only needed if a taint is present, and it is not a required configuration for GPU access.

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Option A is wrong because `-c` requires a container name argument (e.g., `-c my-container`), and `--previous` is misspelled as `--previous` (should be `--previous`); the syntax `-c --previous` is invalid and would cause an error. Option B is wrong because `--tail=100` only limits the log output to the last 100 lines of the current container instance, not the terminated one. Option C is wrong because `-p` is not a valid shorthand for `--previous`; the correct shorthand is `-p` does not exist—`kubectl logs` uses `--previous` (long flag) only, and `-p` is not recognized.

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Option A is wrong because 3 terminating pods would exceed the maxUnavailable=1 limit, meaning more than 1 pod would be unavailable at once, which violates the update strategy. Option B is wrong because 0 terminating pods would imply no old pods are being removed, but with 2 new pods ready and maxSurge=1, the controller must start terminating old pods to stay within the surge budget. Option D is wrong because 2 terminating pods would require the old ReplicaSet to scale down by 2, but with only 2 new pods ready, the total pods would be 3 (old) + 2 (new) = 5, exceeding the maxSurge limit of 4 (3 desired + 1 surge).

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Option A is wrong because `kubeadm alpha certs renew` was deprecated in v1.15 and removed in v1.20; the `alpha` subcommand no longer exists in current kubeadm versions. Option C is wrong because `kubeadm init phase certs apiserver --renew` is not a valid command; `kubeadm init phase` is used for generating certificates during initial cluster setup, not for renewal, and there is no `--renew` flag. Option D is wrong because `kubectl create certificate apiserver` does not exist; `kubectl` manages Kubernetes resources, not certificate renewal, and the apiserver certificate is a file-based X.509 certificate managed by kubeadm, not a Kubernetes API object.

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Option B (ReadWriteOncePod) is wrong because it restricts the volume to a single pod on a single node, preventing any other pod from mounting it, even on the same node. Option C (ReadWriteOnce) is wrong because it allows only a single node to mount the volume as read-write, meaning multiple pods on different nodes cannot access it concurrently. Option D (ReadOnlyMany) is wrong because it permits multiple nodes to mount the volume, but only in read-only mode, not read-write.

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Option A is wrong because a ClusterRole is cluster-scoped and, when combined with a ClusterRoleBinding, grants permissions across all namespaces, not just the 'development' namespace. Option B is wrong because a Role is namespace-scoped, but a ClusterRoleBinding is cluster-scoped; this combination would either fail (if the Role is referenced by a ClusterRoleBinding, which is not allowed) or require a ClusterRole, making the Role irrelevant. Option D is wrong because a ClusterRole is cluster-scoped, and while a RoleBinding can bind it to a namespace, the ClusterRole itself still has cluster-wide scope; using a ClusterRole here is unnecessary and could grant unintended permissions if not carefully scoped, whereas a simple Role is the correct namespace-scoped resource.

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Option A is wrong because a NetworkPolicy can block traffic to pods or from specific sources, but it does not affect the Service's endpoint list; the endpoints would still be populated if the selector matched. Option B is wrong because ClusterIP is the correct type for in-cluster access; NodePort is used for external access and does not change internal connectivity. Option C is wrong because the readiness probe passes on all pods, as stated in the scenario, so pods would not be removed from endpoints; if the probe were failing, the pods would be removed, but the scenario explicitly says the readiness probe passes.

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Option B (namespaces) is wrong because a namespace is a Kubernetes resource that provides scope for objects within a cluster, not a kubeconfig field that defines the set of users, clusters, and namespaces. Option C (clusters) is wrong because the `clusters` field in kubeconfig only defines cluster endpoints and certificate authority data, not the user or namespace binding. Option D (users) is wrong because the `users` field only stores client credentials (e.g., client certificates, tokens), not the cluster or namespace association.

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Option A is wrong because a Role and RoleBinding are namespace-scoped and cannot grant permissions cluster-wide; they would only apply within the 'monitoring' namespace. Option B is wrong because it uses the verb 'create' instead of 'get, watch, list', which grants write access (create) rather than read access; also, the requirement is to read, not create resources. Option D is wrong because a ClusterRole bound with a RoleBinding only grants permissions within the namespace of the RoleBinding, not cluster-wide, defeating the purpose of the ClusterRole.

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Option B is wrong because the error message does not mention 'node selector' — it only references taint toleration and anti-affinity rules, so a node selector issue is not present. Option C is wrong because it includes 'node selector' which is not indicated in the error, and while taint toleration mismatch is correct, the second issue is anti-affinity, not node selector. Option D is wrong because 'resource constraints' (e.g., CPU/memory insufficient) would appear as 'Insufficient cpu' or 'Insufficient memory' in the describe output, not as a taint or anti-affinity message.

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Option A is wrong because the connection would not reach the pod on port 80 unless the Service's `targetPort` is explicitly set to 80 or omitted (defaulting to `port`), but the pod is listening on 8080, so traffic would be dropped or rejected. Option B is wrong because the endpoints list is not empty; the Service selects the pod via labels, so endpoints exist unless the pod is not running or labels mismatch. Option C is wrong because Kubernetes does not randomly drop connections due to missing port specification; if `targetPort` is omitted, it defaults to the `port` value, and traffic is forwarded deterministically to that port on the pod.

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Option B is wrong because DNS does resolve the headless service name; it returns the pod IPs rather than failing. Option C is wrong because DNS returns A/AAAA records with pod IPs, not a CNAME to pod names (though pod DNS names are created via StatefulSet, not a headless service alone). Option D is wrong because a headless service explicitly sets clusterIP: None, so no ClusterIP is assigned; DNS never returns a single ClusterIP.

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Option A is wrong because `kubectl config set-context` only defines a context (cluster, namespace, and user association) but does not create or store user credentials. Option C is wrong because `kubectl config create-user` is not a valid kubectl command; kubectl does not have a `create-user` subcommand. Option D is wrong because `kubectl config set-cluster` only configures cluster details (e.g., server URL, CA certificate) and has nothing to do with user authentication.

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Option A is wrong because the kubelet is the node agent that communicates with the control plane and manages pod lifecycle, but it does not directly run containers — it instructs the container runtime to do so. Option B is wrong because the kube-scheduler is a control plane component that assigns pods to nodes based on resource availability and constraints, not a component that runs containers on a node. Option D is wrong because kube-proxy is a network proxy that maintains network rules and handles service-to-pod traffic routing on each node, not container execution.

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Option A is wrong because `kubectl top pod` shows real-time CPU and memory usage metrics, not crash reasons or container exit statuses. Option C is wrong because `kubectl rollout status deployment` checks the rollout progress of a deployment (e.g., whether new ReplicaSets are available), not the crash details of an individual pod. Option D is wrong because while `kubectl get events` can show pod-related events, the field selector `involvedObject.name=<pod-name>` filters events by the pod's name but may miss the container-level termination reason (which is stored in the pod's status, not always in events), and it does not provide the structured exit code and reason as `kubectl describe` does.

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Option A is wrong because PTR records are used for reverse DNS lookups (IP to hostname), not for resolving a Service's ClusterIP. Option B is wrong because SRV records are used to locate specific services with port information (e.g., for headless Services with named ports), not for standard ClusterIP resolution. Option C is wrong because CNAME records alias one hostname to another; Kubernetes uses A records (or AAAA for IPv6) for ClusterIP Services, not CNAMEs, which are typically used for external DNS aliasing.

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Option B is wrong because a NetworkPolicy with `podSelector: {}` and `policyTypes: [Ingress]` does have an effect: it denies all ingress traffic by default, even without explicit rules. Option C is wrong because the absence of ingress rules in a policy with `policyTypes: [Ingress]` results in a deny-all behavior for ingress, not an allow-all. Option D is wrong because the policy only specifies `policyTypes: [Ingress]`, so it has no effect on egress traffic; egress remains allowed by default unless another policy denies it.

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Option A is wrong because 'kubeadm upgrade node config --kubelet-version v1.29.0' is not a valid command; kubeadm does not support a --kubelet-version flag for the upgrade node subcommand, and the correct approach is to use 'kubeadm upgrade node' which automatically handles the kubelet configuration. Option B is wrong because deleting the node object with 'kubectl delete node' is unnecessary and disruptive; it removes the node from the cluster's control plane, requiring re-registration, whereas the correct process uses drain and uncordon to maintain node membership. Option D is wrong because it omits the critical 'kubectl drain' step before upgrading the node; upgrading without draining can cause running pods to be terminated abruptly, leading to service disruption and potential data loss.