Last Updated: Aug 15, 2026
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| Section | Objectives |
|---|---|
| Topic 1: Kubernetes on Nutanix Infrastructure | - Node management and scaling - Nutanix Kubernetes Platform (NKP) concepts - Cluster deployment and lifecycle management |
| Topic 2: Networking in Kubernetes Environments | - Service networking and load balancing - Ingress controllers and traffic management |
| Topic 3: Container Orchestration and Workloads | - Deploying workloads on Kubernetes clusters - Managing deployments, services, and ingress |
| Topic 4: Operations, Monitoring, and Troubleshooting | - Cluster monitoring and logging - Troubleshooting workloads and cluster issues |
| Topic 5: Storage and Data Management | - Nutanix storage integration with Kubernetes - Persistent volumes and storage classes |
1. A company has 30 Edge devices with lightweight Kubernetes, and developers need to push the application to every edge device. An NKP administrator has the NKP Ultimate license tier configured and has access to all kubeconfig files for the 30 edge devices. What is the most efficient way that the administrator can lifecycle manage the application deployments?
A) Create a script to automate the deployment to every edge device.
B) Create a GitHub configuration, deploy it to the 30 edge devices, and configure them to use a GitHub account.
C) Create a new Workspace and attach the 30 edge devices to this workspace with Attach Cluster.
D) Ask the developers to delete the lightweight Kubernetes and deploy new Kubernetes clusters with NKP.
2. Recently, the reliability of some developer platforms has been impacted by out-of-memory errors, causing pods to crash and then remain in a pending state. A Cloud Engineer has been tasked with collecting and reviewing centralized metrics across the various platform environments to identify differences between them and better understand what is causing these performance issues. What should the engineer do to address this request?
A) Utilize Thanos to collect and present centralized metrics on NKP attached and managed clusters.Then visualize these collected and centralized metrics in Grafana.
B) Utilize Fluentd and Fluent Bit to collect and present centralized metrics on NKP attached and managed clusters. Then configure Thanos Query to monitor and send out alerts based on the metric thresholds that have been configured within it.
C) Utilize Prometheus to collect and present centralized metrics on NKP attached and managed clusters. Then configure Thanos Query to monitor and send out alerts based on the metric thresholds that have been configured within it.
D) Utilize Fluentd and Fluent Bit to collect and present centralized metrics on NKP attached and managed clusters. Then visualize these collected and centralized metrics in Grafana.
3. A Platform Engineer has deployed NKP and wants to utilize its OOB data storage feature.
What should the engineer enable to support backups within the NKP environment?
A) Volumes iSCSI
B) MinIO
C) Rook Ceph
D) Objects S3
4. A dev team needed to optimize their logging system to be more robust, because the CPU and memory limits were insufficient, which caused delays in log collection and processing during times of high demand.
After a deep performance analysis, they decided to increase the CPU limits from 1 to 4 and the memory from 1000Mi to 4Gi.
Which ConfigMap should the development team run with custom resource requests and limit values for fluentd?
A) bashCopy
[nutanix@nkp-boot ~]$ cat <<EOF > configmap.yamlapiVersion: v1kind:
ConfigMapmetadata:name:
logging-operator-logging-overridesnamespace: kommanderdata:values.yaml:
|fluentd:resources:limits:cpu: 4memory: 4Girequests:cpu: 4memory: 4GiEOF
B) bashCopy
[nutanix@nkp-boot ~]$ cat <<EOF > configmap.yamlapiVersion v1kind ConfigMapmetadataname logging-operator-logging-overridesnamespace kommanderdatavalues.yaml
|fluentdresourceslimitscpu 4EOFvalues.yaml |fluentdresourceslimitscpu 4memory 4Girequestscpu
1memory 1000MiEOF
C) bashCopy
[nutanix@nkp-boot ~]$ cat <<EOF > configmap.yamlapiVersion: v1kind:
ConfigMapmetadata:name:
logging-operator-logging-overridesnamespace: kommanderdata:values.yaml:
|fluentdresourceslimitscpu 4memory 1000Mirequestscpu 1memory 4GiEOF
D) bashCopy
[nutanix@nkp-boot ~]$ cat <<EOF > configmap.yamlapiVersion v1kind ConfigMapmetadataname logging-operator-logging-overridesnamespace kommanderdatavalues.yaml
|fluentdresourceslimitscpu 1memory 1000Mirequestscpu 4memory 4GiEOF
5. A Platform Engineer is attaching existing Kubernetes clusters to NKP, but a particular Kubernetes Amazon EKS cluster is getting errors with application deployments. These errors are related to persistent volumes. What could be the issue, and what can the engineer do?
A) There is no default StorageClass. Storage classes should be reviewed, and only one should be set as default.
B) There could be a misconfiguration in the ConfigMap. It should be adjusted to NKP requirements.
C) The storage appliance is having issues. The storage engineer should be contacted to take a look.
D) There is no compatible storage to be attached to the EKS cluster. Ask for compatible storage.
Solutions:
| Question # 1 Answer: C | Question # 2 Answer: C | Question # 3 Answer: C | Question # 4 Answer: A | Question # 5 Answer: A |
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