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Nutanix NCP-CN-6.10 Exam Syllabus Topics:

Nutanix Certified Professional - Cloud Native v6.10 Sample Questions:

1. What is a key troubleshooting step if Velero fails to complete a backup in NKP?

A) Inspect Velero pod logs and event messages
B) Check the logging stack status
C) Restart the Kommander UI
D) Recreate the cluster

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 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.
B) Utilize Thanos to collect and present centralized metrics on NKP attached and managed clusters.Then visualize these collected and centralized metrics in Grafana.
C) 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.
D) 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.

3. 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 ConfigMapmetadataname logging-operator-logging-overridesnamespace kommanderdatavalues.yaml
|fluentdresourceslimitscpu 1memory 1000Mirequestscpu 4memory 4GiEOF
B) 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
C) bashCopy
[nutanix@nkp-boot ~]$ cat <<EOF > configmap.yamlapiVersion v1kind ConfigMapmetadataname logging-operator-logging-overridesnamespace kommanderdatavalues.yaml
|fluentdresourceslimitscpu 4EOFvalues.yaml |fluentdresourceslimitscpu 4memory 4Girequestscpu
1memory 1000MiEOF
D) bashCopy
[nutanix@nkp-boot ~]$ cat <<EOF > configmap.yamlapiVersion: v1kind:
ConfigMapmetadata:name:
logging-operator-logging-overridesnamespace: kommanderdata:values.yaml:
|fluentdresourceslimitscpu 4memory 1000Mirequestscpu 1memory 4GiEOF

4. In an air-gapped environment, which action is critical for successful image building with nib?

A) Point to local mirrors or cached repositories
B) Enable a default storage class
C) Install Kommander on the bastion host
D) Run the build with an unrestricted public IP

5. A development team decided to employ an efficient monitoring system with Grafana-logging, which was successfully implemented as can be seen in the following output:
AppDeployment "kommander-default-workspace/grafana-logging" created in namespace
"kommander-default-workspace".
Which command did the team execute to complete this task?

A) kubectl get helmreleases grafana-logging -n kommander-default-workspace -w
B) export WORKSPACE_NAMESPACE=kommander-default-workspaceappdeploymentnkp create package-bundle grafana-logging
C) kubectl get appdeployment -n kommander-default-workspace
D) nkp create appdeployment grafana-logging --app grafana-logging-6.57.4 --workspace default- workspace

Solutions: