Prompt:
Explain this bash code:

kubectl delete namespaces <insert-some-namespace-name>

Response: This bash code 2.36 - Share a Cluster with Namespaces | This delete is asynchronous, so for a time you will see the namespace in the Terminating state.

Context: 2.36 - Share a Cluster with Namespaces | This delete is asynchronous, so for a time you will see the namespace in the Terminating state.


Prompt:
Explain this bash code:

kubectl create -f https://k8s.io/examples/admin/namespace-dev.json

Response: This bash code 2.36 - Share a Cluster with Namespaces | And then let's create the production namespace using kubectl:

Context: 2.36 - Share a Cluster with Namespaces | And then let's create the production namespace using kubectl:


Prompt:
Explain this bash code:

kubectl create -f https://k8s.io/examples/admin/namespace-prod.json

Response: This bash code 2.36 - Share a Cluster with Namespaces | To be sure things are right, list all of the namespaces in our cluster.

Context: 2.36 - Share a Cluster with Namespaces | To be sure things are right, list all of the namespaces in our cluster.


Prompt:
Complete this text code:

NAME          STATUS    AGE       LABELS
default       Active    32m       <none>

Response:
development   Active    29s       name=development
production    Active    23s       name=production

Context: 2.36 - Share a Cluster with Namespaces | A Kubernetes namespace provides the scope for Pods, Services, and Deployments in the cluster. Users interacting with one namespace do not see the content in another namespace. To demonstrate this, let


Prompt:
Explain this text code:

NAME          STATUS    AGE       LABELS
default       Active    32m       <none>
development   Active    29s       name=development
production    Active    23s       name=production

Response: This text code 2.36 - Share a Cluster with Namespaces | A Kubernetes namespace provides the scope for Pods, Services, and Deployments in the cluster. Users interacting with one namespace do not see the content in another namespace. To demonstrate this, let


Prompt:
Explain this bash code:

kubectl create deployment snowflake \
  --image=registry.k8s.io/serve_hostname \
  -n=development --replicas=2

Response: This bash code 2.36 - Share a Cluster with Namespaces | We have created a deployment whose replica size is 2 that is running the pod called snowflake with a basic container that serves the hostname.

Context: 2.36 - Share a Cluster with Namespaces | We have created a deployment whose replica size is 2 that is running the pod called snowflake with a basic container that serves the hostname.


Prompt:
Explain this text code:

NAME         READY   UP-TO-DATE   AVAILABLE   AGE
snowflake    2/2     2            2           2m

Response: This text code 2.36 - Share a Cluster with Namespaces | And this is great, developers are able to do what they want, and they do not have to worry about affecting content in the production namespace.

Context: 2.36 - Share a Cluster with Namespaces | And this is great, developers are able to do what they want, and they do not have to worry about affecting content in the production namespace.


Prompt:
Explain this text code:

NAME                         READY     STATUS    RESTARTS   AGE
snowflake-3968820950-9dgr8   1/1       Running   0          2m
snowflake-3968820950-vgc4n   1/1       Running   0          2m

Response: This text code 2.36 - Share a Cluster with Namespaces | And this is great, developers are able to do what they want, and they do not have to worry about affecting content in the production namespace.


Prompt:
Explain this bash code:

kubectl get deployment -n=production
kubectl get pods -n=production

Response: This bash code 2.36 - Share a Cluster with Namespaces | Production likes to run cattle, so let's create some cattle pods.

Context: 2.36 - Share a Cluster with Namespaces | Production likes to run cattle, so let's create some cattle pods.


Prompt:
Complete this bash code:

kubectl create deployment cattle --image=registry.k8s.io/serve_hostname -n=production
kubectl scale deployment cattle --replicas=5 -n=production

Response: kubectl get deployment -n=production

Context: 2.36 - Share a Cluster with Namespaces | At this point, it should be clear that the resources users create in one namespace are hidden from the other namespace.


Prompt:
Explain this bash code:

kubectl create deployment cattle --image=registry.k8s.io/serve_hostname -n=production
kubectl scale deployment cattle --replicas=5 -n=production

kubectl get deployment -n=production

Response: This bash code 2.36 - Share a Cluster with Namespaces | At this point, it should be clear that the resources users create in one namespace are hidden from the other namespace.


Prompt:
Explain this text code:

NAME         READY   UP-TO-DATE   AVAILABLE   AGE
cattle       5/5     5            5           10s

Response: This text code 2.36 - Share a Cluster with Namespaces | At this point, it should be clear that the resources users create in one namespace are hidden from the other namespace.


Prompt:
Complete this text code:

NAME                      READY     STATUS    RESTARTS   AGE
cattle-2263376956-41xy6   1/1       Running   0          34s
cattle-2263376956-kw466   1/1       Running   0          34s

Response:
cattle-2263376956-n4v97   1/1       Running   0          34s
cattle-2263376956-p5p3i   1/1       Running   0          34s
cattle-2263376956-sxpth   1/1       Running   0          34s


Prompt:
Explain this text code:

NAME                      READY     STATUS    RESTARTS   AGE
cattle-2263376956-41xy6   1/1       Running   0          34s
cattle-2263376956-kw466   1/1       Running   0          34s
cattle-2263376956-n4v97   1/1       Running   0          34s
cattle-2263376956-p5p3i   1/1       Running   0          34s
cattle-2263376956-sxpth   1/1       Running   0          34s

Response: This text code 2.36 - Share a Cluster with Namespaces | At this point, it should be clear that the resources users create in one namespace are hidden from the other namespace.


Prompt:
Complete this yaml code:

apiVersion: v1
    ...
    ownerReferences:
    - apiVersion: apps/v1
      blockOwnerDeletion: true

Response:
      controller: true
      kind: ReplicaSet
      name: nginx-deployment-6b474476c4
      uid: 4fdcd81c-bd5d-41f7-97af-3a3b759af9a7
    ...

Context: 2.38 - Use Cascading Deletion in a Cluster | By default, Kubernetes uses background cascading deletion to delete dependents of an object. You can switch to foreground cascading deletion using either kubectl or the Kubernetes API, depending on th


Prompt:
Explain this yaml code:

apiVersion: v1
    ...
    ownerReferences:
    - apiVersion: apps/v1
      blockOwnerDeletion: true
      controller: true
      kind: ReplicaSet
      name: nginx-deployment-6b474476c4
      uid: 4fdcd81c-bd5d-41f7-97af-3a3b759af9a7
    ...

Response: This yaml code 2.38 - Use Cascading Deletion in a Cluster | By default, Kubernetes uses background cascading deletion to delete dependents of an object. You can switch to foreground cascading deletion using either kubectl or the Kubernetes API, depending on th


Prompt:
Explain this bash code:

kubectl delete deployment nginx-deployment --cascade=foreground

Response: This bash code 2.38 - Use Cascading Deletion in a Cluster | Using the Kubernetes API

Context: 2.38 - Use Cascading Deletion in a Cluster | Using the Kubernetes API


Prompt:
Explain this text code:

curl -X DELETE localhost:8080/apis/apps/v1/namespaces/default/deployments/nginx-deployment \
    -d '{"kind":"DeleteOptions","apiVersion":"v1","propagationPolicy":"Foreground"}' \
    -H "Content-Type: application/json"

Response: This text code 2.38 - Use Cascading Deletion in a Cluster | The output contains a foregroundDeletion finalizer like this:

Context: 2.38 - Use Cascading Deletion in a Cluster | The output contains a foregroundDeletion finalizer like this:


Prompt:
Complete this text code:

"kind": "Deployment",
"apiVersion": "apps/v1",
"metadata": {
    "name": "nginx-deployment",
    "namespace": "default",
    "uid": "d1ce1b02-cae8-4288-8a53-30e84d8fa505",

Response:
    "resourceVersion": "1363097",
    "creationTimestamp": "2021-07-08T20:24:37Z",
    "deletionTimestamp": "2021-07-08T20:27:39Z",
    "finalizers": [
      "foregroundDeletion"
    ]
    ...

Context: 2.38 - Use Cascading Deletion in a Cluster | To check the version, enter kubectl version.


Prompt:
Explain this text code:

"kind": "Deployment",
"apiVersion": "apps/v1",
"metadata": {
    "name": "nginx-deployment",
    "namespace": "default",
    "uid": "d1ce1b02-cae8-4288-8a53-30e84d8fa505",
    "resourceVersion": "1363097",
    "creationTimestamp": "2021-07-08T20:24:37Z",
    "deletionTimestamp": "2021-07-08T20:27:39Z",
    "finalizers": [
      "foregroundDeletion"
    ]
    ...

Response: This text code 2.38 - Use Cascading Deletion in a Cluster | To check the version, enter kubectl version.


Prompt:
Explain this bash code:

kubectl delete deployment nginx-deployment --cascade=background

Response: This bash code 2.38 - Use Cascading Deletion in a Cluster | Using the Kubernetes API


Prompt:
Explain this text code:

curl -X DELETE localhost:8080/apis/apps/v1/namespaces/default/deployments/nginx-deployment \
    -d '{"kind":"DeleteOptions","apiVersion":"v1","propagationPolicy":"Background"}' \
    -H "Content-Type: application/json"

Response: This text code 2.38 - Use Cascading Deletion in a Cluster | The output is similar to this:

Context: 2.38 - Use Cascading Deletion in a Cluster | The output is similar to this:


Prompt:
Complete this text code:

"kind": "Status",
"apiVersion": "v1",
...
"status": "Success",
"details": {

Response:
    "name": "nginx-deployment",
    "group": "apps",
    "kind": "deployments",
    "uid": "cc9eefb9-2d49-4445-b1c1-d261c9396456"
}

Context: 2.38 - Use Cascading Deletion in a Cluster | By default, when you tell Kubernetes to delete an object, the controller also deletes dependent objects. You can make Kubernetes orphan these dependents using kubectl or the Kubernetes API, depending


Prompt:
Explain this text code:

"kind": "Status",
"apiVersion": "v1",
...
"status": "Success",
"details": {
    "name": "nginx-deployment",
    "group": "apps",
    "kind": "deployments",
    "uid": "cc9eefb9-2d49-4445-b1c1-d261c9396456"
}

Response: This text code 2.38 - Use Cascading Deletion in a Cluster | By default, when you tell Kubernetes to delete an object, the controller also deletes dependent objects. You can make Kubernetes orphan these dependents using kubectl or the Kubernetes API, depending


Prompt:
Explain this bash code:

kubectl delete deployment nginx-deployment --cascade=orphan

Response: This bash code 2.38 - Use Cascading Deletion in a Cluster | Using the Kubernetes API


Prompt:
Explain this text code:

curl -X DELETE localhost:8080/apis/apps/v1/namespaces/default/deployments/nginx-deployment \
    -d '{"kind":"DeleteOptions","apiVersion":"v1","propagationPolicy":"Orphan"}' \
    -H "Content-Type: application/json"

Response: This text code 2.38 - Use Cascading Deletion in a Cluster | The output contains orphan in the finalizers field, similar to this:

Context: 2.38 - Use Cascading Deletion in a Cluster | The output contains orphan in the finalizers field, similar to this:


Prompt:
Complete this text code:

"kind": "Deployment",
"apiVersion": "apps/v1",
"namespace": "default",
"uid": "6f577034-42a0-479d-be21-78018c466f1f",
"creationTimestamp": "2021-07-09T16:46:37Z",

Response:
"deletionTimestamp": "2021-07-09T16:47:08Z",
"deletionGracePeriodSeconds": 0,
"finalizers": [
  "orphan"
],
...

Context: 2.38 - Use Cascading Deletion in a Cluster | You can check that the Pods managed by the Deployment are still running:


Prompt:
Explain this text code:

"kind": "Deployment",
"apiVersion": "apps/v1",
"namespace": "default",
"uid": "6f577034-42a0-479d-be21-78018c466f1f",
"creationTimestamp": "2021-07-09T16:46:37Z",
"deletionTimestamp": "2021-07-09T16:47:08Z",
"deletionGracePeriodSeconds": 0,
"finalizers": [
  "orphan"
],
...

Response: This text code 2.38 - Use Cascading Deletion in a Cluster | You can check that the Pods managed by the Deployment are still running:


Prompt:
Complete this yaml code:

apiVersion: apiserver.config.k8s.io/v1
kind: EncryptionConfiguration
resources:
  - resources:
      - secrets
      - configmaps
      - pandas.awesome.bears.example
    providers:
      - kms:

Response:
          name: myKmsPluginFoo
          endpoint: unix:///tmp/socketfile-foo.sock
          cachesize: 100
          timeout: 3s
      - kms:
          name: myKmsPluginBar
          endpoint: unix:///tmp/socketfile-bar.sock
          cachesize: 100
          timeout: 3s

Context: 2.39 - Using a KMS provider for data encryption | Setting --encryption-provider-config-automatic-reload to true collapses all health checks to a single health check endpoint. Individual health checks are only available when KMS v1 providers are in us


Prompt:
Explain this yaml code:

apiVersion: apiserver.config.k8s.io/v1
kind: EncryptionConfiguration
resources:
  - resources:
      - secrets
      - configmaps
      - pandas.awesome.bears.example
    providers:
      - kms:
          name: myKmsPluginFoo
          endpoint: unix:///tmp/socketfile-foo.sock
          cachesize: 100
          timeout: 3s
      - kms:
          name: myKmsPluginBar
          endpoint: unix:///tmp/socketfile-bar.sock
          cachesize: 100
          timeout: 3s

Response: This yaml code 2.39 - Using a KMS provider for data encryption | Setting --encryption-provider-config-automatic-reload to true collapses all health checks to a single health check endpoint. Individual health checks are only available when KMS v1 providers are in us


Prompt:
Complete this yaml code:

apiVersion: apiserver.config.k8s.io/v1
kind: EncryptionConfiguration
resources:
  - resources:
      - secrets
      - configmaps
      - pandas.awesome.bears.example
    providers:
      - kms:

Response:
          apiVersion: v2
          name: myKmsPluginFoo
          endpoint: unix:///tmp/socketfile-foo.sock
          timeout: 3s
      - kms:
          apiVersion: v2
          name: myKmsPluginBar
          endpoint: unix:///tmp/socketfile-bar.sock
          timeout: 3s


Prompt:
Explain this yaml code:

apiVersion: apiserver.config.k8s.io/v1
kind: EncryptionConfiguration
resources:
  - resources:
      - secrets
      - configmaps
      - pandas.awesome.bears.example
    providers:
      - kms:
          apiVersion: v2
          name: myKmsPluginFoo
          endpoint: unix:///tmp/socketfile-foo.sock
          timeout: 3s
      - kms:
          apiVersion: v2
          name: myKmsPluginBar
          endpoint: unix:///tmp/socketfile-bar.sock
          timeout: 3s

Response: This yaml code 2.39 - Using a KMS provider for data encryption | Setting --encryption-provider-config-automatic-reload to true collapses all health checks to a single health check endpoint. Individual health checks are only available when KMS v1 providers are in us


Prompt:
Explain this bash code:

kubectl create secret generic secret1 -n default --from-literal=mykey=mydata

Response: This bash code 2.39 - Using a KMS provider for data encryption | Using the etcdctl command line, read that secret out of etcd:

Context: 2.39 - Using a KMS provider for data encryption | Using the etcdctl command line, read that secret out of etcd:


Prompt:
Explain this text code:

ETCDCTL_API=3 etcdctl get /kubernetes.io/secrets/default/secret1 [...] | hexdump -C

Response: This text code 2.39 - Using a KMS provider for data encryption | where [...] contains the additional arguments for connecting to the etcd server.

Context: 2.39 - Using a KMS provider for data encryption | where [...] contains the additional arguments for connecting to the etcd server.


Prompt:
Explain this bash code:

kubectl get secrets --all-namespaces -o json | kubectl replace -f -

Response: This bash code 2.39 - Using a KMS provider for data encryption | To switch from a local encryption provider to the kms provider and re-encrypt all of the secrets:

Context: 2.39 - Using a KMS provider for data encryption | To switch from a local encryption provider to the kms provider and re-encrypt all of the secrets:


Prompt:
Complete this yaml code:

apiVersion: apiserver.config.k8s.io/v1
kind: EncryptionConfiguration
resources:
  - resources:
      - secrets
    providers:
      - kms:

Response:
          apiVersion: v2
          name : myKmsPlugin
          endpoint: unix:///tmp/socketfile.sock
      - aescbc:
          keys:
            - name: key1
              secret: <BASE 64 ENCODED SECRET>

Context: 2.39 - Using a KMS provider for data encryption | Restart all kube-apiserver processes.


Prompt:
Explain this yaml code:

apiVersion: apiserver.config.k8s.io/v1
kind: EncryptionConfiguration
resources:
  - resources:
      - secrets
    providers:
      - kms:
          apiVersion: v2
          name : myKmsPlugin
          endpoint: unix:///tmp/socketfile.sock
      - aescbc:
          keys:
            - name: key1
              secret: <BASE 64 ENCODED SECRET>

Response: This yaml code 2.39 - Using a KMS provider for data encryption | Restart all kube-apiserver processes.


Prompt:
Explain this bash code:

kubectl get secrets --all-namespaces -o json | kubectl replace -f -

Response: This bash code 2.39 - Using a KMS provider for data encryption | If you no longer want to use encryption for data persisted in the Kubernetes API, read decrypt data that are already stored at rest.

Context: 2.39 - Using a KMS provider for data encryption | If you no longer want to use encryption for data persisted in the Kubernetes API, read decrypt data that are already stored at rest.


Prompt:
Explain this text code:

kubedns=`kubectl get svc kube-dns -n kube-system -o jsonpath={.spec.clusterIP}`
domain=<cluster-domain>
localdns=<node-local-address>

Response: This text code 2.41 - Using NodeLocal DNSCache in Kubernetes Clusters | <cluster-domain> is "cluster.local" by default. <node-local-address> is the local listen IP address chosen for NodeLocal DNSCache.

Context: 2.41 - Using NodeLocal DNSCache in Kubernetes Clusters | <cluster-domain> is "cluster.local" by default. <node-local-address> is the local listen IP address chosen for NodeLocal DNSCache.


Prompt:
Explain this text code:

sed -i "s/__PILLAR__LOCAL__DNS__/$localdns/g; s/__PILLAR__DNS__DOMAIN__/$domain/g; s/__PILLAR__DNS__SERVER__/$kubedns/g" nodelocaldns.yaml

Response: This text code 2.41 - Using NodeLocal DNSCache in Kubernetes Clusters | __PILLAR__CLUSTER__DNS__ and __PILLAR__UPSTREAM__SERVERS__ will be populated by the node-local-dns pods. In this mode, the node-local-dns pods listen on both the kube-dns service IP as well as <node-l

Context: 2.41 - Using NodeLocal DNSCache in Kubernetes Clusters | __PILLAR__CLUSTER__DNS__ and __PILLAR__UPSTREAM__SERVERS__ will be populated by the node-local-dns pods. In this mode, the node-local-dns pods listen on both the kube-dns service IP as well as <node-l


Prompt:
Explain this text code:

sed -i "s/__PILLAR__LOCAL__DNS__/$localdns/g; s/__PILLAR__DNS__DOMAIN__/$domain/g; s/,__PILLAR__DNS__SERVER__//g; s/__PILLAR__CLUSTER__DNS__/$kubedns/g" nodelocaldns.yaml

Response: This text code 2.41 - Using NodeLocal DNSCache in Kubernetes Clusters | In this mode, the node-local-dns pods listen only on <node-local-address>. The node-local-dns interface cannot bind the kube-dns cluster IP since the interface used for IPVS loadbalancing already uses

Context: 2.41 - Using NodeLocal DNSCache in Kubernetes Clusters | In this mode, the node-local-dns pods listen only on <node-local-address>. The node-local-dns interface cannot bind the kube-dns cluster IP since the interface used for IPVS loadbalancing already uses


Prompt:
Explain this text code:

kubelet --allowed-unsafe-sysctls \
  'kernel.msg*,net.core.somaxconn' ...

Response: This text code 2.42 - Using sysctls in a Kubernetes Cluster | For Minikube, this can be done via the extra-config flag:

Context: 2.42 - Using sysctls in a Kubernetes Cluster | For Minikube, this can be done via the extra-config flag:


Prompt:
Explain this text code:

minikube start --extra-config="kubelet.allowed-unsafe-sysctls=kernel.msg*,net.core.somaxconn"...

Response: This text code 2.42 - Using sysctls in a Kubernetes Cluster | Only namespaced sysctls can be enabled this way.

Context: 2.42 - Using sysctls in a Kubernetes Cluster | Only namespaced sysctls can be enabled this way.


Prompt:
Complete this yaml code:

apiVersion: v1
kind: Pod
metadata:
  name: sysctl-example
spec:
  securityContext:
    sysctls:

Response:
    - name: kernel.shm_rmid_forced
      value: "0"
    - name: net.core.somaxconn
      value: "1024"
    - name: kernel.msgmax
      value: "65536"
  ...

Context: 2.42 - Using sysctls in a Kubernetes Cluster | It is good practice to consider nodes with special sysctl settings as tainted within a cluster, and only schedule pods onto them which need those sysctl settings. It is suggested to use the Kubernetes


Prompt:
Explain this yaml code:

apiVersion: v1
kind: Pod
metadata:
  name: sysctl-example
spec:
  securityContext:
    sysctls:
    - name: kernel.shm_rmid_forced
      value: "0"
    - name: net.core.somaxconn
      value: "1024"
    - name: kernel.msgmax
      value: "65536"
  ...

Response: This yaml code 2.42 - Using sysctls in a Kubernetes Cluster | It is good practice to consider nodes with special sysctl settings as tainted within a cluster, and only schedule pods onto them which need those sysctl settings. It is suggested to use the Kubernetes


Prompt:
Complete this text code:

--kube-reserved=cpu=4,memory=4Gi
--system-reserved=cpu=1,memory=1Gi

Response:
--memory-manager-policy=Static
--reserved-memory '0:memory=3Gi;1:memory=2148Mi'

Context: 2.43 - Utilizing the NUMA-aware Memory Manager | Prior to Kubernetes 1.32, you also need to add


Prompt:
Explain this text code:

--kube-reserved=cpu=4,memory=4Gi
--system-reserved=cpu=1,memory=1Gi
--memory-manager-policy=Static
--reserved-memory '0:memory=3Gi;1:memory=2148Mi'

Response: This text code 2.43 - Utilizing the NUMA-aware Memory Manager | Prior to Kubernetes 1.32, you also need to add


Prompt:
Complete this text code:

spec:
  containers:
  - name: nginx
    image: nginx
    resources:
      limits:

Response:
        memory: "200Mi"
        cpu: "2"
        example.com/device: "1"
      requests:
        memory: "200Mi"
        cpu: "2"
        example.com/device: "1"

Context: 2.43 - Utilizing the NUMA-aware Memory Manager | Also, a pod sharing CPU(s) runs in the Guaranteed QoS class, when requests are equal to limits.


Prompt:
Explain this text code:

spec:
  containers:
  - name: nginx
    image: nginx
    resources:
      limits:
        memory: "200Mi"
        cpu: "2"
        example.com/device: "1"
      requests:
        memory: "200Mi"
        cpu: "2"
        example.com/device: "1"

Response: This text code 2.43 - Utilizing the NUMA-aware Memory Manager | Also, a pod sharing CPU(s) runs in the Guaranteed QoS class, when requests are equal to limits.


Prompt:
Complete this text code:

spec:
  containers:
  - name: nginx
    image: nginx
    resources:
      limits:

Response:
        memory: "200Mi"
        cpu: "300m"
        example.com/device: "1"
      requests:
        memory: "200Mi"
        cpu: "300m"
        example.com/device: "1"

Context: 2.43 - Utilizing the NUMA-aware Memory Manager | Notice that both CPU and memory requests must be specified for a Pod to lend it to Guaranteed QoS class.


Prompt:
Explain this text code:

spec:
  containers:
  - name: nginx
    image: nginx
    resources:
      limits:
        memory: "200Mi"
        cpu: "300m"
        example.com/device: "1"
      requests:
        memory: "200Mi"
        cpu: "300m"
        example.com/device: "1"

Response: This text code 2.43 - Utilizing the NUMA-aware Memory Manager | Notice that both CPU and memory requests must be specified for a Pod to lend it to Guaranteed QoS class.


Prompt:
Explain this text code:

NAME         READY   STATUS                  RESTARTS   AGE
guaranteed   0/1     TopologyAffinityError   0          113s

Response: This text code 2.43 - Utilizing the NUMA-aware Memory Manager | Use kubectl describe pod <id> or kubectl get events to obtain detailed error message:

Context: 2.43 - Utilizing the NUMA-aware Memory Manager | Use kubectl describe pod <id> or kubectl get events to obtain detailed error message:


Prompt:
Explain this text code:

Warning  TopologyAffinityError  10m   kubelet, dell8  Resources cannot be allocated with Topology locality

Response: This text code 2.43 - Utilizing the NUMA-aware Memory Manager | Search system logs with respect to a particular pod.

Context: 2.43 - Utilizing the NUMA-aware Memory Manager | Search system logs with respect to a particular pod.


Prompt:
Complete this yaml code:

apiVersion: v1
kind: Pod
metadata:
  name: guaranteed
spec:
  containers:
  - name: guaranteed
    image: consumer

Response:
    imagePullPolicy: Never
    resources:
      limits:
        cpu: "2"
        memory: 150Gi
      requests:
        cpu: "2"
        memory: 150Gi
    command: ["sleep","infinity"]

Context: 2.43 - Utilizing the NUMA-aware Memory Manager | Next, let us log into the node where it was deployed and examine the state file in /var/lib/kubelet/memory_manager_state:


Prompt:
Explain this yaml code:

apiVersion: v1
kind: Pod
metadata:
  name: guaranteed
spec:
  containers:
  - name: guaranteed
    image: consumer
    imagePullPolicy: Never
    resources:
      limits:
        cpu: "2"
        memory: 150Gi
      requests:
        cpu: "2"
        memory: 150Gi
    command: ["sleep","infinity"]

Response: This yaml code 2.43 - Utilizing the NUMA-aware Memory Manager | Next, let us log into the node where it was deployed and examine the state file in /var/lib/kubelet/memory_manager_state:


Prompt:
Complete this json code:

{
   "policyName":"Static",
   "machineState":{
      "0":{
         "numberOfAssignments":1,
         "memoryMap":{
            "hugepages-1Gi":{
               "total":0,
               "systemReserved":0,
               "allocatable":0,
               "reserved":0,
               "free":0
            },
            "memory":{
               "total":134987354112,
               "systemReserved":3221225472,
               "allocatable":131766128640,
               "reserved":131766128640,
               "free":0
            }
         },
         "nodes":[
            0,
            1
         ]
      },
      "1":{
         "numberOfAssignments":1,
         "memoryMap":{
            "hugepages-1Gi":{
               "total":0,
               "systemReserved":0,
               "allocatable":0,

Response:
               "reserved":0,
               "free":0
            },
            "memory":{
               "total":135286722560,
               "systemReserved":2252341248,
               "allocatable":133034381312,
               "reserved":29295144960,
               "free":103739236352
            }
         },
         "nodes":[
            0,
            1
         ]
      }
   },
   "entries":{
      "fa9bdd38-6df9-4cf9-aa67-8c4814da37a8":{
         "guaranteed":[
            {
               "numaAffinity":[
                  0,
                  1
               ],
               "type":"memory",
               "size":161061273600
            }
         ]
      }
   },
   "checksum":4142013182
}

Context: 2.43 - Utilizing the NUMA-aware Memory Manager | It can be deduced from the state file that the pod was pinned to both NUMA nodes, i.e.:


Prompt:
Explain this json code:

{
   "policyName":"Static",
   "machineState":{
      "0":{
         "numberOfAssignments":1,
         "memoryMap":{
            "hugepages-1Gi":{
               "total":0,
               "systemReserved":0,
               "allocatable":0,
               "reserved":0,
               "free":0
            },
            "memory":{
               "total":134987354112,
               "systemReserved":3221225472,
               "allocatable":131766128640,
               "reserved":131766128640,
               "free":0
            }
         },
         "nodes":[
            0,
            1
         ]
      },
      "1":{
         "numberOfAssignments":1,
         "memoryMap":{
            "hugepages-1Gi":{
               "total":0,
               "systemReserved":0,
               "allocatable":0,
               "reserved":0,
               "free":0
            },
            "memory":{
               "total":135286722560,
               "systemReserved":2252341248,
               "allocatable":133034381312,
               "reserved":29295144960,
               "free":103739236352
            }
         },
         "nodes":[
            0,
            1
         ]
      }
   },
   "entries":{
      "fa9bdd38-6df9-4cf9-aa67-8c4814da37a8":{
         "guaranteed":[
            {
               "numaAffinity":[
                  0,
                  1
               ],
               "type":"memory",
               "size":161061273600
            }
         ]
      }
   },
   "checksum":4142013182
}

Response: This json code 2.43 - Utilizing the NUMA-aware Memory Manager | It can be deduced from the state file that the pod was pinned to both NUMA nodes, i.e.:


Prompt:
Complete this text code:

URL=https://dl.k8s.io/release/v1.34.0/bin/linux/amd64
BINARY=kubectl

FILES=(
    "$BINARY"
    "$BINARY.sig"

Response:
    "$BINARY.cert"
)

for FILE in "${FILES[@]}"; do
    curl -sSfL --retry 3 --retry-delay 3 "$URL/$FILE" -o "$FILE"
done

Context: 2.44 - Verify Signed Kubernetes Artifacts | Then verify the blob by using cosign verify-blob:


Prompt:
Explain this text code:

URL=https://dl.k8s.io/release/v1.34.0/bin/linux/amd64
BINARY=kubectl

FILES=(
    "$BINARY"
    "$BINARY.sig"
    "$BINARY.cert"
)

for FILE in "${FILES[@]}"; do
    curl -sSfL --retry 3 --retry-delay 3 "$URL/$FILE" -o "$FILE"
done

Response: This text code 2.44 - Verify Signed Kubernetes Artifacts | Then verify the blob by using cosign verify-blob:


Prompt:
Complete this text code:

cosign verify-blob "$BINARY" \
  --signature "$BINARY".sig \

Response:
  --certificate "$BINARY".cert \
  --certificate-identity krel-staging@k8s-releng-prod.iam.gserviceaccount.com \
  --certificate-oidc-issuer https://accounts.google.com

Context: 2.44 - Verify Signed Kubernetes Artifacts | Cosign 2.0 requires the --certificate-identity and --certificate-oidc-issuer options.


Prompt:
Explain this text code:

cosign verify-blob "$BINARY" \
  --signature "$BINARY".sig \
  --certificate "$BINARY".cert \
  --certificate-identity krel-staging@k8s-releng-prod.iam.gserviceaccount.com \
  --certificate-oidc-issuer https://accounts.google.com

Response: This text code 2.44 - Verify Signed Kubernetes Artifacts | Cosign 2.0 requires the --certificate-identity and --certificate-oidc-issuer options.


Prompt:
Complete this text code:

cosign verify registry.k8s.io/kube-apiserver-amd64:v1.34.0 \
  --certificate-identity krel-trust@k8s-releng-prod.iam.gserviceaccount.com \

Response:
  --certificate-oidc-issuer https://accounts.google.com \
  | jq .

Context: 2.44 - Verify Signed Kubernetes Artifacts | To verify all signed control plane images for the latest stable version (v1.34.0), please run the following commands:


Prompt:
Explain this text code:

cosign verify registry.k8s.io/kube-apiserver-amd64:v1.34.0 \
  --certificate-identity krel-trust@k8s-releng-prod.iam.gserviceaccount.com \
  --certificate-oidc-issuer https://accounts.google.com \
  | jq .

Response: This text code 2.44 - Verify Signed Kubernetes Artifacts | To verify all signed control plane images for the latest stable version (v1.34.0), please run the following commands:


Prompt:
Complete this text code:

curl -Ls "https://sbom.k8s.io/$(curl -Ls https://dl.k8s.io/release/stable.txt)/release" \
  | grep "SPDXID: SPDXRef-Package-registry.k8s.io" \
  | grep -v sha256 | cut -d- -f3- | sed 's/-/\//' | sed 's/-v1/:v1/' \
  | sort > images.txt
input=images.txt
while IFS= read -r image

Response:
do
  cosign verify "$image" \
    --certificate-identity krel-trust@k8s-releng-prod.iam.gserviceaccount.com \
    --certificate-oidc-issuer https://accounts.google.com \
    | jq .
done < "$input"

Context: 2.44 - Verify Signed Kubernetes Artifacts | Once you have verified an image, you can specify the image by its digest in your Pod manifests as per this example:


Prompt:
Explain this text code:

curl -Ls "https://sbom.k8s.io/$(curl -Ls https://dl.k8s.io/release/stable.txt)/release" \
  | grep "SPDXID: SPDXRef-Package-registry.k8s.io" \
  | grep -v sha256 | cut -d- -f3- | sed 's/-/\//' | sed 's/-v1/:v1/' \
  | sort > images.txt
input=images.txt
while IFS= read -r image
do
  cosign verify "$image" \
    --certificate-identity krel-trust@k8s-releng-prod.iam.gserviceaccount.com \
    --certificate-oidc-issuer https://accounts.google.com \
    | jq .
done < "$input"

Response: This text code 2.44 - Verify Signed Kubernetes Artifacts | Once you have verified an image, you can specify the image by its digest in your Pod manifests as per this example:


Prompt:
Explain this text code:

registry-url/image-name@sha256:45b23dee08af5e43a7fea6c4cf9c25ccf269ee113168c19722f87876677c5cb2

Response: This text code 2.44 - Verify Signed Kubernetes Artifacts | For more information, please refer to the Image Pull Policy section.

Context: 2.44 - Verify Signed Kubernetes Artifacts | For more information, please refer to the Image Pull Policy section.


Prompt:
Complete this text code:

# Retrieve the latest available Kubernetes release version
VERSION=$(curl -Ls https://dl.k8s.io/release/stable.txt)

# Verify the SHA512 sum
curl -Ls "https://sbom.k8s.io/$VERSION/release" -o "$VERSION.spdx"
echo "$(curl -Ls "https://sbom.k8s.io/$VERSION/release.sha512") $VERSION.spdx" | sha512sum --check

# Verify the SHA256 sum
echo "$(curl -Ls "https://sbom.k8s.io/$VERSION/release.sha256") $VERSION.spdx" | sha256sum --check

Response:
# Retrieve sigstore signature and certificate
curl -Ls "https://sbom.k8s.io/$VERSION/release.sig" -o "$VERSION.spdx.sig"
curl -Ls "https://sbom.k8s.io/$VERSION/release.cert" -o "$VERSION.spdx.cert"

# Verify the sigstore signature
cosign verify-blob \
    --certificate "$VERSION.spdx.cert" \
    --signature "$VERSION.spdx.sig" \
    --certificate-identity krel-staging@k8s-releng-prod.iam.gserviceaccount.com \
    --certificate-oidc-issuer https://accounts.google.com \
    "$VERSION.spdx"

Context: 2.44 - Verify Signed Kubernetes Artifacts | This page shows how to assign a memory request and a memory limit to a Container. A Container is guaranteed to have as much memory as it requests, but is not allowed to use more memory than its limit.


Prompt:
Explain this text code:

# Retrieve the latest available Kubernetes release version
VERSION=$(curl -Ls https://dl.k8s.io/release/stable.txt)

# Verify the SHA512 sum
curl -Ls "https://sbom.k8s.io/$VERSION/release" -o "$VERSION.spdx"
echo "$(curl -Ls "https://sbom.k8s.io/$VERSION/release.sha512") $VERSION.spdx" | sha512sum --check

# Verify the SHA256 sum
echo "$(curl -Ls "https://sbom.k8s.io/$VERSION/release.sha256") $VERSION.spdx" | sha256sum --check

# Retrieve sigstore signature and certificate
curl -Ls "https://sbom.k8s.io/$VERSION/release.sig" -o "$VERSION.spdx.sig"
curl -Ls "https://sbom.k8s.io/$VERSION/release.cert" -o "$VERSION.spdx.cert"

# Verify the sigstore signature
cosign verify-blob \
    --certificate "$VERSION.spdx.cert" \
    --signature "$VERSION.spdx.sig" \
    --certificate-identity krel-staging@k8s-releng-prod.iam.gserviceaccount.com \
    --certificate-oidc-issuer https://accounts.google.com \
    "$VERSION.spdx"

Response: This text code 2.44 - Verify Signed Kubernetes Artifacts | This page shows how to assign a memory request and a memory limit to a Container. A Container is guaranteed to have as much memory as it requests, but is not allowed to use more memory than its limit.


Prompt:
Complete this yaml code:

apiVersion: v1
kind: Pod
metadata:
  name: memory-demo
  namespace: mem-example
spec:
  containers:
  - name: memory-demo-ctr

Response:
    image: polinux/stress
    resources:
      requests:
        memory: "100Mi"
      limits:
        memory: "200Mi"
    command: ["stress"]
    args: ["--vm", "1", "--vm-bytes", "150M", "--vm-hang", "1"]

Context: 3.1 - Assign Memory Resources to Containers and Pods | The args section in the configuration file provides arguments for the Container when it starts. The "--vm-bytes", "150M" arguments tell the Container to attempt to allocate 150 MiB of memory.


Prompt:
Explain this yaml code:

apiVersion: v1
kind: Pod
metadata:
  name: memory-demo
  namespace: mem-example
spec:
  containers:
  - name: memory-demo-ctr
    image: polinux/stress
    resources:
      requests:
        memory: "100Mi"
      limits:
        memory: "200Mi"
    command: ["stress"]
    args: ["--vm", "1", "--vm-bytes", "150M", "--vm-hang", "1"]

Response: This yaml code 3.1 - Assign Memory Resources to Containers and Pods | The args section in the configuration file provides arguments for the Container when it starts. The "--vm-bytes", "150M" arguments tell the Container to attempt to allocate 150 MiB of memory.


Prompt:
Explain this bash code:

kubectl apply -f https://k8s.io/examples/pods/resource/memory-request-limit.yaml --namespace=mem-example

Response: This bash code 3.1 - Assign Memory Resources to Containers and Pods | Verify that the Pod Container is running:

Context: 3.1 - Assign Memory Resources to Containers and Pods | Verify that the Pod Container is running:


Prompt:
Explain this bash code:

kubectl get pod memory-demo --namespace=mem-example

Response: This bash code 3.1 - Assign Memory Resources to Containers and Pods | View detailed information about the Pod:

Context: 3.1 - Assign Memory Resources to Containers and Pods | View detailed information about the Pod:


Prompt:
Explain this bash code:

kubectl get pod memory-demo --output=yaml --namespace=mem-example

Response: This bash code 3.1 - Assign Memory Resources to Containers and Pods | The output shows that the one Container in the Pod has a memory request of 100 MiB and a memory limit of 200 MiB.

Context: 3.1 - Assign Memory Resources to Containers and Pods | The output shows that the one Container in the Pod has a memory request of 100 MiB and a memory limit of 200 MiB.


Prompt:
Complete this text code:

...
resources:
  requests:

Response:
    memory: 100Mi
  limits:
    memory: 200Mi
...

Context: 3.1 - Assign Memory Resources to Containers and Pods | Run kubectl top to fetch the metrics for the pod:


Prompt:
Explain this text code:

...
resources:
  requests:
    memory: 100Mi
  limits:
    memory: 200Mi
...

Response: This text code 3.1 - Assign Memory Resources to Containers and Pods | Run kubectl top to fetch the metrics for the pod:


Prompt:
Explain this bash code:

kubectl top pod memory-demo --namespace=mem-example

Response: This bash code 3.1 - Assign Memory Resources to Containers and Pods | The output shows that the Pod is using about 162,900,000 bytes of memory, which is about 150 MiB. This is greater than the Pod's 100 MiB request, but within the Pod's 200 MiB limit.

Context: 3.1 - Assign Memory Resources to Containers and Pods | The output shows that the Pod is using about 162,900,000 bytes of memory, which is about 150 MiB. This is greater than the Pod's 100 MiB request, but within the Pod's 200 MiB limit.


Prompt:
Explain this text code:

NAME                        CPU(cores)   MEMORY(bytes)
memory-demo                 <something>  162856960

Response: This text code 3.1 - Assign Memory Resources to Containers and Pods | Delete your Pod:

Context: 3.1 - Assign Memory Resources to Containers and Pods | Delete your Pod:


Prompt:
Explain this bash code:

kubectl delete pod memory-demo --namespace=mem-example

Response: This bash code 3.1 - Assign Memory Resources to Containers and Pods | A Container can exceed its memory request if the Node has memory available. But a Container is not allowed to use more than its memory limit. If a Container allocates more memory than its limit, the C

Context: 3.1 - Assign Memory Resources to Containers and Pods | A Container can exceed its memory request if the Node has memory available. But a Container is not allowed to use more than its memory limit. If a Container allocates more memory than its limit, the C


Prompt:
Complete this yaml code:

apiVersion: v1
kind: Pod
metadata:
  name: memory-demo-2
  namespace: mem-example
spec:
  containers:
  - name: memory-demo-2-ctr

Response:
    image: polinux/stress
    resources:
      requests:
        memory: "50Mi"
      limits:
        memory: "100Mi"
    command: ["stress"]
    args: ["--vm", "1", "--vm-bytes", "250M", "--vm-hang", "1"]

Context: 3.1 - Assign Memory Resources to Containers and Pods | In the args section of the configuration file, you can see that the Container will attempt to allocate 250 MiB of memory, which is well above the 100 MiB limit.


Prompt:
Explain this yaml code:

apiVersion: v1
kind: Pod
metadata:
  name: memory-demo-2
  namespace: mem-example
spec:
  containers:
  - name: memory-demo-2-ctr
    image: polinux/stress
    resources:
      requests:
        memory: "50Mi"
      limits:
        memory: "100Mi"
    command: ["stress"]
    args: ["--vm", "1", "--vm-bytes", "250M", "--vm-hang", "1"]

Response: This yaml code 3.1 - Assign Memory Resources to Containers and Pods | In the args section of the configuration file, you can see that the Container will attempt to allocate 250 MiB of memory, which is well above the 100 MiB limit.


Prompt:
Explain this bash code:

kubectl apply -f https://k8s.io/examples/pods/resource/memory-request-limit-2.yaml --namespace=mem-example

Response: This bash code 3.1 - Assign Memory Resources to Containers and Pods | View detailed information about the Pod:


Prompt:
Explain this bash code:

kubectl get pod memory-demo-2 --namespace=mem-example

Response: This bash code 3.1 - Assign Memory Resources to Containers and Pods | At this point, the Container might be running or killed. Repeat the preceding command until the Container is killed:

Context: 3.1 - Assign Memory Resources to Containers and Pods | At this point, the Container might be running or killed. Repeat the preceding command until the Container is killed:


Prompt:
Explain this text code:

NAME            READY     STATUS      RESTARTS   AGE
memory-demo-2   0/1       OOMKilled   1          24s

Response: This text code 3.1 - Assign Memory Resources to Containers and Pods | Get a more detailed view of the Container status:

Context: 3.1 - Assign Memory Resources to Containers and Pods | Get a more detailed view of the Container status:


Prompt:
Explain this bash code:

kubectl get pod memory-demo-2 --output=yaml --namespace=mem-example

Response: This bash code 3.1 - Assign Memory Resources to Containers and Pods | The output shows that the Container was killed because it is out of memory (OOM):

Context: 3.1 - Assign Memory Resources to Containers and Pods | The output shows that the Container was killed because it is out of memory (OOM):


Prompt:
Complete this text code:

lastState:
   terminated:
     containerID: 65183c1877aaec2e8427bc95609cc52677a454b56fcb24340dbd22917c23b10f

Response:
     exitCode: 137
     finishedAt: 2017-06-20T20:52:19Z
     reason: OOMKilled
     startedAt: null

Context: 3.1 - Assign Memory Resources to Containers and Pods | The Container in this exercise can be restarted, so the kubelet restarts it. Repeat this command several times to see that the Container is repeatedly killed and restarted:


Prompt:
Explain this text code:

lastState:
   terminated:
     containerID: 65183c1877aaec2e8427bc95609cc52677a454b56fcb24340dbd22917c23b10f
     exitCode: 137
     finishedAt: 2017-06-20T20:52:19Z
     reason: OOMKilled
     startedAt: null

Response: This text code 3.1 - Assign Memory Resources to Containers and Pods | The Container in this exercise can be restarted, so the kubelet restarts it. Repeat this command several times to see that the Container is repeatedly killed and restarted:


Prompt:
Explain this bash code:

kubectl get pod memory-demo-2 --namespace=mem-example

Response: This bash code 3.1 - Assign Memory Resources to Containers and Pods | The output shows that the Container is killed, restarted, killed again, restarted again, and so on:

Context: 3.1 - Assign Memory Resources to Containers and Pods | The output shows that the Container is killed, restarted, killed again, restarted again, and so on:


Prompt:
Explain this bash code:

kubectl get pod memory-demo-2 --namespace=mem-example
NAME            READY     STATUS      RESTARTS   AGE
memory-demo-2   0/1       OOMKilled   1          37s

Response: This bash code 3.1 - Assign Memory Resources to Containers and Pods | View detailed information about the Pod history:

Context: 3.1 - Assign Memory Resources to Containers and Pods | View detailed information about the Pod history:


Prompt:
Explain this bash code:

kubectl get pod memory-demo-2 --namespace=mem-example
NAME            READY     STATUS    RESTARTS   AGE
memory-demo-2   1/1       Running   2          40s

Response: This bash code 3.1 - Assign Memory Resources to Containers and Pods | View detailed information about the Pod history:


Prompt:
Explain this bash code:

kubectl describe pod memory-demo-2 --namespace=mem-example

Response: This bash code 3.1 - Assign Memory Resources to Containers and Pods | The output shows that the Container starts and fails repeatedly:

Context: 3.1 - Assign Memory Resources to Containers and Pods | The output shows that the Container starts and fails repeatedly:


Prompt:
Explain this text code:

... Normal  Created   Created container with id 66a3a20aa7980e61be4922780bf9d24d1a1d8b7395c09861225b0eba1b1f8511
... Warning BackOff   Back-off restarting failed container

Response: This text code 3.1 - Assign Memory Resources to Containers and Pods | View detailed information about your cluster's Nodes:

Context: 3.1 - Assign Memory Resources to Containers and Pods | View detailed information about your cluster's Nodes:


Prompt:
Explain this text code:

Warning OOMKilling Memory cgroup out of memory: Kill process 4481 (stress) score 1994 or sacrifice child

Response: This text code 3.1 - Assign Memory Resources to Containers and Pods | Delete your Pod:


Prompt:
Explain this bash code:

kubectl delete pod memory-demo-2 --namespace=mem-example

Response: This bash code 3.1 - Assign Memory Resources to Containers and Pods | Memory requests and limits are associated with Containers, but it is useful to think of a Pod as having a memory request and limit. The memory request for the Pod is the sum of the memory requests for

Context: 3.1 - Assign Memory Resources to Containers and Pods | Memory requests and limits are associated with Containers, but it is useful to think of a Pod as having a memory request and limit. The memory request for the Pod is the sum of the memory requests for


Prompt:
Complete this yaml code:

apiVersion: v1
kind: Pod
metadata:
  name: memory-demo-3
  namespace: mem-example
spec:
  containers:
  - name: memory-demo-3-ctr

Response:
    image: polinux/stress
    resources:
      requests:
        memory: "1000Gi"
      limits:
        memory: "1000Gi"
    command: ["stress"]
    args: ["--vm", "1", "--vm-bytes", "150M", "--vm-hang", "1"]

Context: 3.1 - Assign Memory Resources to Containers and Pods | Create the Pod:


Prompt:
Explain this yaml code:

apiVersion: v1
kind: Pod
metadata:
  name: memory-demo-3
  namespace: mem-example
spec:
  containers:
  - name: memory-demo-3-ctr
    image: polinux/stress
    resources:
      requests:
        memory: "1000Gi"
      limits:
        memory: "1000Gi"
    command: ["stress"]
    args: ["--vm", "1", "--vm-bytes", "150M", "--vm-hang", "1"]

Response: This yaml code 3.1 - Assign Memory Resources to Containers and Pods | Create the Pod:


Prompt:
Explain this bash code:

kubectl apply -f https://k8s.io/examples/pods/resource/memory-request-limit-3.yaml --namespace=mem-example

Response: This bash code 3.1 - Assign Memory Resources to Containers and Pods | View the Pod status:

Context: 3.1 - Assign Memory Resources to Containers and Pods | View the Pod status:


Prompt:
Explain this bash code:

kubectl get pod memory-demo-3 --namespace=mem-example

Response: This bash code 3.1 - Assign Memory Resources to Containers and Pods | The output shows that the Pod status is PENDING. That is, the Pod is not scheduled to run on any Node, and it will remain in the PENDING state indefinitely:

Context: 3.1 - Assign Memory Resources to Containers and Pods | The output shows that the Pod status is PENDING. That is, the Pod is not scheduled to run on any Node, and it will remain in the PENDING state indefinitely:


Prompt:
Explain this bash code:

kubectl get pod memory-demo-3 --namespace=mem-example
NAME            READY     STATUS    RESTARTS   AGE
memory-demo-3   0/1       Pending   0          25s

Response: This bash code 3.1 - Assign Memory Resources to Containers and Pods | View detailed information about the Pod, including events:

Context: 3.1 - Assign Memory Resources to Containers and Pods | View detailed information about the Pod, including events:


Prompt:
Explain this bash code:

kubectl describe pod memory-demo-3 --namespace=mem-example

Response: This bash code 3.1 - Assign Memory Resources to Containers and Pods | The output shows that the Container cannot be scheduled because of insufficient memory on the Nodes:

Context: 3.1 - Assign Memory Resources to Containers and Pods | The output shows that the Container cannot be scheduled because of insufficient memory on the Nodes:


Prompt:
Complete this text code:

Events:
  ...  Reason            Message

Response:
       ------            -------
  ...  FailedScheduling  No nodes are available that match all of the following predicates:: Insufficient memory (3).

Context: 3.1 - Assign Memory Resources to Containers and Pods | The memory resource is measured in bytes. You can express memory as a plain integer or a fixed-point integer with one of these suffixes: E, P, T, G, M, K, Ei, Pi, Ti, Gi, Mi, Ki. For example, the foll


Prompt:
Explain this text code:

Events:
  ...  Reason            Message
       ------            -------
  ...  FailedScheduling  No nodes are available that match all of the following predicates:: Insufficient memory (3).

Response: This text code 3.1 - Assign Memory Resources to Containers and Pods | The memory resource is measured in bytes. You can express memory as a plain integer or a fixed-point integer with one of these suffixes: E, P, T, G, M, K, Ei, Pi, Ti, Gi, Mi, Ki. For example, the foll


Prompt:
Explain this bash code:

kubectl delete pod memory-demo-3 --namespace=mem-example

Response: This bash code 3.1 - Assign Memory Resources to Containers and Pods | If you do not specify a memory limit for a Container, one of the following situations applies:

Context: 3.1 - Assign Memory Resources to Containers and Pods | If you do not specify a memory limit for a Container, one of the following situations applies:


Prompt:
Complete this yaml code:

apiVersion: v1
kind: Pod
metadata:
  name: cpu-demo
  namespace: cpu-example
spec:
  containers:
  - name: cpu-demo-ctr

Response:
    image: vish/stress
    resources:
      limits:
        cpu: "1"
      requests:
        cpu: "0.5"
    args:
    - -cpus
    - "2"

Context: 3.2 - Assign CPU Resources to Containers and Pods | The args section of the configuration file provides arguments for the container when it starts. The -cpus "2" argument tells the Container to attempt to use 2 CPUs.


Prompt:
Explain this yaml code:

apiVersion: v1
kind: Pod
metadata:
  name: cpu-demo
  namespace: cpu-example
spec:
  containers:
  - name: cpu-demo-ctr
    image: vish/stress
    resources:
      limits:
        cpu: "1"
      requests:
        cpu: "0.5"
    args:
    - -cpus
    - "2"

Response: This yaml code 3.2 - Assign CPU Resources to Containers and Pods | The args section of the configuration file provides arguments for the container when it starts. The -cpus "2" argument tells the Container to attempt to use 2 CPUs.


Prompt:
Explain this bash code:

kubectl apply -f https://k8s.io/examples/pods/resource/cpu-request-limit.yaml --namespace=cpu-example

Response: This bash code 3.2 - Assign CPU Resources to Containers and Pods | Verify that the Pod is running:

Context: 3.2 - Assign CPU Resources to Containers and Pods | Verify that the Pod is running:


Prompt:
Explain this bash code:

kubectl get pod cpu-demo --output=yaml --namespace=cpu-example

Response: This bash code 3.2 - Assign CPU Resources to Containers and Pods | The output shows that the one container in the Pod has a CPU request of 500 milliCPU and a CPU limit of 1 CPU.

Context: 3.2 - Assign CPU Resources to Containers and Pods | The output shows that the one container in the Pod has a CPU request of 500 milliCPU and a CPU limit of 1 CPU.


Prompt:
Complete this text code:

resources:
  limits:

Response:
    cpu: "1"
  requests:
    cpu: 500m

Context: 3.2 - Assign CPU Resources to Containers and Pods | Use kubectl top to fetch the metrics for the Pod:


Prompt:
Explain this text code:

resources:
  limits:
    cpu: "1"
  requests:
    cpu: 500m

Response: This text code 3.2 - Assign CPU Resources to Containers and Pods | Use kubectl top to fetch the metrics for the Pod:


Prompt:
Explain this text code:

NAME                        CPU(cores)   MEMORY(bytes)
cpu-demo                    974m         <something>

Response: This text code 3.2 - Assign CPU Resources to Containers and Pods | Recall that by setting -cpu "2", you configured the Container to attempt to use 2 CPUs, but the Container is only being allowed to use about 1 CPU. The container's CPU use is being throttled, because

Context: 3.2 - Assign CPU Resources to Containers and Pods | Recall that by setting -cpu "2", you configured the Container to attempt to use 2 CPUs, but the Container is only being allowed to use about 1 CPU. The container's CPU use is being throttled, because


Prompt:
Explain this bash code:

kubectl delete pod cpu-demo --namespace=cpu-example

Response: This bash code 3.2 - Assign CPU Resources to Containers and Pods | CPU requests and limits are associated with Containers, but it is useful to think of a Pod as having a CPU request and limit. The CPU request for a Pod is the sum of the CPU requests for all the Conta

Context: 3.2 - Assign CPU Resources to Containers and Pods | CPU requests and limits are associated with Containers, but it is useful to think of a Pod as having a CPU request and limit. The CPU request for a Pod is the sum of the CPU requests for all the Conta


Prompt:
Complete this yaml code:

apiVersion: v1
kind: Pod
metadata:
  name: cpu-demo-2
  namespace: cpu-example
spec:
  containers:
  - name: cpu-demo-ctr-2

Response:
    image: vish/stress
    resources:
      limits:
        cpu: "100"
      requests:
        cpu: "100"
    args:
    - -cpus
    - "2"

Context: 3.2 - Assign CPU Resources to Containers and Pods | Create the Pod:


Prompt:
Explain this yaml code:

apiVersion: v1
kind: Pod
metadata:
  name: cpu-demo-2
  namespace: cpu-example
spec:
  containers:
  - name: cpu-demo-ctr-2
    image: vish/stress
    resources:
      limits:
        cpu: "100"
      requests:
        cpu: "100"
    args:
    - -cpus
    - "2"

Response: This yaml code 3.2 - Assign CPU Resources to Containers and Pods | Create the Pod:


Prompt:
Explain this bash code:

kubectl apply -f https://k8s.io/examples/pods/resource/cpu-request-limit-2.yaml --namespace=cpu-example

Response: This bash code 3.2 - Assign CPU Resources to Containers and Pods | View the Pod status:

Context: 3.2 - Assign CPU Resources to Containers and Pods | View the Pod status:


Prompt:
Explain this text code:

NAME         READY     STATUS    RESTARTS   AGE
cpu-demo-2   0/1       Pending   0          7m

Response: This text code 3.2 - Assign CPU Resources to Containers and Pods | View detailed information about the Pod, including events:

Context: 3.2 - Assign CPU Resources to Containers and Pods | View detailed information about the Pod, including events:


Prompt:
Explain this bash code:

kubectl describe pod cpu-demo-2 --namespace=cpu-example

Response: This bash code 3.2 - Assign CPU Resources to Containers and Pods | The output shows that the Container cannot be scheduled because of insufficient CPU resources on the Nodes:

Context: 3.2 - Assign CPU Resources to Containers and Pods | The output shows that the Container cannot be scheduled because of insufficient CPU resources on the Nodes:


Prompt:
Complete this text code:

Events:
  Reason                        Message

Response:
  ------                        -------
  FailedScheduling      No nodes are available that match all of the following predicates:: Insufficient cpu (3).

Context: 3.2 - Assign CPU Resources to Containers and Pods | Delete your Pod:


Prompt:
Explain this text code:

Events:
  Reason                        Message
  ------                        -------
  FailedScheduling      No nodes are available that match all of the following predicates:: Insufficient cpu (3).

Response: This text code 3.2 - Assign CPU Resources to Containers and Pods | Delete your Pod:


Prompt:
Explain this bash code:

kubectl delete pod cpu-demo-2 --namespace=cpu-example

Response: This bash code 3.2 - Assign CPU Resources to Containers and Pods | If you do not specify a CPU limit for a Container, then one of these situations applies:

Context: 3.2 - Assign CPU Resources to Containers and Pods | If you do not specify a CPU limit for a Container, then one of these situations applies:


Prompt:
Explain this text code:

* `resource.k8s.io/v1beta1`
* `resource.k8s.io/v1beta2`

Response: This text code 3.3.1 - Set Up DRA in a Cluster | For more information, see Enabling or disabling API groups.

Context: 3.3.1 - Set Up DRA in a Cluster | For more information, see Enabling or disabling API groups.


Prompt:
Explain this text code:

error: the server doesn't have a resource type "deviceclasses"

Response: This text code 3.3.1 - Set Up DRA in a Cluster | Try the following troubleshooting steps:

Context: 3.3.1 - Set Up DRA in a Cluster | Try the following troubleshooting steps:


Prompt:
Explain this text code:

NAME                                                  NODE                DRIVER               POOL                             AGE
cluster-1-device-pool-1-driver.example.com-lqx8x      cluster-1-node-1    driver.example.com   cluster-1-device-pool-1-r1gc     7s
cluster-1-device-pool-2-driver.example.com-29t7b      cluster-1-node-2    driver.example.com   cluster-1-device-pool-2-446z     8s

Response: This text code 3.3.1 - Set Up DRA in a Cluster | Try the following troubleshooting steps:


Prompt:
Explain this bash code:

kubectl get resourceslice <resourceslice-name> -o yaml

Response: This bash code 3.3.1 - Set Up DRA in a Cluster | The output is similar to the following:

Context: 3.3.1 - Set Up DRA in a Cluster | The output is similar to the following:


Prompt:
Complete this yaml code:

apiVersion: resource.k8s.io/v1
kind: ResourceSlice
# lines omitted for clarity
spec:
  devices:
  - attributes:
      type:
        string: gpu
    capacity:
      memory:
        value: 64Gi

Response:
    name: gpu-0
  - attributes:
      type:
        string: gpu
    capacity:
      memory:
        value: 64Gi
    name: gpu-1
  driver: driver.example.com
  nodeName: cluster-1-node-1
# lines omitted for clarity

Context: 3.3.1 - Set Up DRA in a Cluster | You can also check the driver provider's documentation for available properties and values.


Prompt:
Explain this yaml code:

apiVersion: resource.k8s.io/v1
kind: ResourceSlice
# lines omitted for clarity
spec:
  devices:
  - attributes:
      type:
        string: gpu
    capacity:
      memory:
        value: 64Gi
    name: gpu-0
  - attributes:
      type:
        string: gpu
    capacity:
      memory:
        value: 64Gi
    name: gpu-1
  driver: driver.example.com
  nodeName: cluster-1-node-1
# lines omitted for clarity

Response: This yaml code 3.3.1 - Set Up DRA in a Cluster | You can also check the driver provider's documentation for available properties and values.


Prompt:
Complete this yaml code:

apiVersion: resource.k8s.io/v1
kind: DeviceClass
metadata:
  name: example-device-class

Response:
spec:
  selectors:
  - cel:
      expression: |-
        device.driver == "driver.example.com"

Context: 3.3.1 - Set Up DRA in a Cluster | Create the DeviceClass in your cluster:


Prompt:
Explain this yaml code:

apiVersion: resource.k8s.io/v1
kind: DeviceClass
metadata:
  name: example-device-class
spec:
  selectors:
  - cel:
      expression: |-
        device.driver == "driver.example.com"

Response: This yaml code 3.3.1 - Set Up DRA in a Cluster | Create the DeviceClass in your cluster:


Prompt:
Explain this bash code:

kubectl apply -f https://k8s.io/examples/dra/deviceclass.yaml

Response: This bash code 3.3.1 - Set Up DRA in a Cluster | To delete the DeviceClass that you created in this task, run the following command:

Context: 3.3.1 - Set Up DRA in a Cluster | To delete the DeviceClass that you created in this task, run the following command:


Prompt:
Explain this bash code:

kubectl delete -f https://k8s.io/examples/dra/deviceclass.yaml

Response: This bash code 3.3.1 - Set Up DRA in a Cluster | This page shows you how to allocate devices to your Pods by using dynamic resource allocation (DRA). These instructions are for workload operators. Before reading this page, familiarize yourself with

Context: 3.3.1 - Set Up DRA in a Cluster | This page shows you how to allocate devices to your Pods by using dynamic resource allocation (DRA). These instructions are for workload operators. Before reading this page, familiarize yourself with


Prompt:
Complete this yaml code:

apiVersion: resource.k8s.io/v1
kind: ResourceClaimTemplate
metadata:
  name: example-resource-claim-template
spec:
  spec:
    devices:
      requests:

Response:
      - name: gpu-claim
        exactly:
          deviceClassName: example-device-class
          selectors:
          - cel:
              expression: |-
                device.attributes["driver.example.com"].type == "gpu" &&
                device.capacity["driver.example.com"].memory == quantity("64Gi")

Context: 3.3.2 - Allocate Devices to Workloads with DRA | This manifest creates a ResourceClaimTemplate that requests devices in the example-device-class DeviceClass that match both of the following parameters:


Prompt:
Explain this yaml code:

apiVersion: resource.k8s.io/v1
kind: ResourceClaimTemplate
metadata:
  name: example-resource-claim-template
spec:
  spec:
    devices:
      requests:
      - name: gpu-claim
        exactly:
          deviceClassName: example-device-class
          selectors:
          - cel:
              expression: |-
                device.attributes["driver.example.com"].type == "gpu" &&
                device.capacity["driver.example.com"].memory == quantity("64Gi")

Response: This yaml code 3.3.2 - Allocate Devices to Workloads with DRA | This manifest creates a ResourceClaimTemplate that requests devices in the example-device-class DeviceClass that match both of the following parameters:


Prompt:
Explain this bash code:

kubectl apply -f https://k8s.io/examples/dra/resourceclaimtemplate.yaml

Response: This bash code 3.3.2 - Allocate Devices to Workloads with DRA | Review the following example manifest:dra/resourceclaim.yaml apiVersion: resource.k8s.io/v1 kind: ResourceClaim metadata: name: example-resource-claim spec: devices: requests: - name: sing

Context: 3.3.2 - Allocate Devices to Workloads with DRA | Review the following example manifest:dra/resourceclaim.yaml apiVersion: resource.k8s.io/v1 kind: ResourceClaim metadata: name: example-resource-claim spec: devices: requests: - name: sing


Prompt:
Complete this yaml code:

apiVersion: resource.k8s.io/v1
kind: ResourceClaim
metadata:
  name: example-resource-claim
spec:
  devices:
    requests:
    - name: single-gpu-claim

Response:
      exactly:
        deviceClassName: example-device-class
        allocationMode: All
        selectors:
        - cel:
            expression: |-
              device.attributes["driver.example.com"].type == "gpu" &&
              device.capacity["driver.example.com"].memory == quantity("64Gi")

Context: 3.3.2 - Allocate Devices to Workloads with DRA | This manifest creates ResourceClaim that requests devices in the example-device-class DeviceClass that match both of the following parameters:


Prompt:
Explain this yaml code:

apiVersion: resource.k8s.io/v1
kind: ResourceClaim
metadata:
  name: example-resource-claim
spec:
  devices:
    requests:
    - name: single-gpu-claim
      exactly:
        deviceClassName: example-device-class
        allocationMode: All
        selectors:
        - cel:
            expression: |-
              device.attributes["driver.example.com"].type == "gpu" &&
              device.capacity["driver.example.com"].memory == quantity("64Gi")

Response: This yaml code 3.3.2 - Allocate Devices to Workloads with DRA | This manifest creates ResourceClaim that requests devices in the example-device-class DeviceClass that match both of the following parameters:


Prompt:
Explain this bash code:

kubectl apply -f https://k8s.io/examples/dra/resourceclaim.yaml

Response: This bash code 3.3.2 - Allocate Devices to Workloads with DRA | To request device allocation, specify a ResourceClaim or a ResourceClaimTemplate in the resourceClaims field of the Pod specification. Then, request a specific claim by name in the resources.claims fi

Context: 3.3.2 - Allocate Devices to Workloads with DRA | To request device allocation, specify a ResourceClaim or a ResourceClaimTemplate in the resourceClaims field of the Pod specification. Then, request a specific claim by name in the resources.claims fi


Prompt:
Complete this yaml code:

apiVersion: batch/v1
kind: Job
metadata:
  name: example-dra-job
spec:
  completions: 10
  parallelism: 2
  template:
    spec:
      restartPolicy: Never
      containers:
      - name: container0
        image: ubuntu:24.04
        command: ["sleep", "9999"]
        resources:
          claims:
          - name: separate-gpu-claim

Response:
      - name: container1
        image: ubuntu:24.04
        command: ["sleep", "9999"]
        resources:
          claims:
          - name: shared-gpu-claim
      - name: container2
        image: ubuntu:24.04
        command: ["sleep", "9999"]
        resources:
          claims:
          - name: shared-gpu-claim
      resourceClaims:
      - name: separate-gpu-claim
        resourceClaimTemplateName: example-resource-claim-template
      - name: shared-gpu-claim
        resourceClaimName: example-resource-claim

Context: 3.3.2 - Allocate Devices to Workloads with DRA | Each Pod in this Job has the following properties:


Prompt:
Explain this yaml code:

apiVersion: batch/v1
kind: Job
metadata:
  name: example-dra-job
spec:
  completions: 10
  parallelism: 2
  template:
    spec:
      restartPolicy: Never
      containers:
      - name: container0
        image: ubuntu:24.04
        command: ["sleep", "9999"]
        resources:
          claims:
          - name: separate-gpu-claim
      - name: container1
        image: ubuntu:24.04
        command: ["sleep", "9999"]
        resources:
          claims:
          - name: shared-gpu-claim
      - name: container2
        image: ubuntu:24.04
        command: ["sleep", "9999"]
        resources:
          claims:
          - name: shared-gpu-claim
      resourceClaims:
      - name: separate-gpu-claim
        resourceClaimTemplateName: example-resource-claim-template
      - name: shared-gpu-claim
        resourceClaimName: example-resource-claim

Response: This yaml code 3.3.2 - Allocate Devices to Workloads with DRA | Each Pod in this Job has the following properties:


Prompt:
Explain this bash code:

kubectl apply -f https://k8s.io/examples/dra/dra-example-job.yaml

Response: This bash code 3.3.2 - Allocate Devices to Workloads with DRA | Try the following troubleshooting steps:

Context: 3.3.2 - Allocate Devices to Workloads with DRA | Try the following troubleshooting steps:


Prompt:
Explain this bash code:

kubectl delete -f https://k8s.io/examples/dra/dra-example-job.yaml

Response: This bash code 3.3.2 - Allocate Devices to Workloads with DRA | To delete your resource claims, run one of the following commands:

Context: 3.3.2 - Allocate Devices to Workloads with DRA | To delete your resource claims, run one of the following commands:


Prompt:
Explain this bash code:

kubectl delete -f https://k8s.io/examples/dra/resourceclaimtemplate.yaml

Response: This bash code 3.3.2 - Allocate Devices to Workloads with DRA | Delete the ResourceClaim:

Context: 3.3.2 - Allocate Devices to Workloads with DRA | Delete the ResourceClaim:


Prompt:
Explain this bash code:

kubectl delete -f https://k8s.io/examples/dra/resourceclaim.yaml

Response: This bash code 3.3.2 - Allocate Devices to Workloads with DRA | This page shows how to specify CPU and memory resources for a Pod at pod-level in addition to container-level resource specifications. A Kubernetes node allocates resources to a pod based on the pod's

Context: 3.3.2 - Allocate Devices to Workloads with DRA | This page shows how to specify CPU and memory resources for a Pod at pod-level in addition to container-level resource specifications. A Kubernetes node allocates resources to a pod based on the pod's


Prompt:
Complete this yaml code:

apiVersion: v1
kind: Pod
metadata:
  name: memory-demo
  namespace: pod-resources-example
spec:
  resources:
    requests:

Response:
      memory: "100Mi"
    limits:
      memory: "200Mi"
  containers:
  - name: memory-demo-ctr
    image: nginx
    command: ["stress"]
    args: ["--vm", "1", "--vm-bytes", "150M", "--vm-hang", "1"]

Context: 3.4 - Assign Pod-level CPU and memory resources | The args section in the manifest provides arguments for the container when it starts. The "--vm-bytes", "150M" arguments tell the Container to attempt to allocate 150 MiB of memory.


Prompt:
Explain this yaml code:

apiVersion: v1
kind: Pod
metadata:
  name: memory-demo
  namespace: pod-resources-example
spec:
  resources:
    requests:
      memory: "100Mi"
    limits:
      memory: "200Mi"
  containers:
  - name: memory-demo-ctr
    image: nginx
    command: ["stress"]
    args: ["--vm", "1", "--vm-bytes", "150M", "--vm-hang", "1"]

Response: This yaml code 3.4 - Assign Pod-level CPU and memory resources | The args section in the manifest provides arguments for the container when it starts. The "--vm-bytes", "150M" arguments tell the Container to attempt to allocate 150 MiB of memory.


Prompt:
Explain this bash code:

kubectl apply -f https://k8s.io/examples/pods/resource/pod-level-memory-request-limit.yaml --namespace=pod-resources-example

Response: This bash code 3.4 - Assign Pod-level CPU and memory resources | Verify that the Pod is running:

Context: 3.4 - Assign Pod-level CPU and memory resources | Verify that the Pod is running:


Prompt:
Explain this bash code:

kubectl get pod memory-demo --namespace=pod-resources-example

Response: This bash code 3.4 - Assign Pod-level CPU and memory resources | View detailed information about the Pod:

Context: 3.4 - Assign Pod-level CPU and memory resources | View detailed information about the Pod:


Prompt:
Explain this bash code:

kubectl get pod memory-demo --output=yaml --namespace=pod-resources-example

Response: This bash code 3.4 - Assign Pod-level CPU and memory resources | The output shows that the Pod has a memory request of 100 MiB and a memory limit of 200 MiB.

Context: 3.4 - Assign Pod-level CPU and memory resources | The output shows that the Pod has a memory request of 100 MiB and a memory limit of 200 MiB.


Prompt:
Complete this text code:

...
spec:
  containers:
  ...
  resources:

Response:
    requests:
      memory: 100Mi
    limits:
      memory: 200Mi
...

Context: 3.4 - Assign Pod-level CPU and memory resources | Run kubectl top to fetch the metrics for the pod:


Prompt:
Explain this text code:

...
spec:
  containers:
  ...
  resources:
    requests:
      memory: 100Mi
    limits:
      memory: 200Mi
...

Response: This text code 3.4 - Assign Pod-level CPU and memory resources | Run kubectl top to fetch the metrics for the pod:


Prompt:
Explain this bash code:

kubectl top pod memory-demo --namespace=pod-resources-example

Response: This bash code 3.4 - Assign Pod-level CPU and memory resources | The output shows that the Pod is using about 162,900,000 bytes of memory, which is about 150 MiB. This is greater than the Pod's 100 MiB request, but within the Pod's 200 MiB limit.

Context: 3.4 - Assign Pod-level CPU and memory resources | The output shows that the Pod is using about 162,900,000 bytes of memory, which is about 150 MiB. This is greater than the Pod's 100 MiB request, but within the Pod's 200 MiB limit.


Prompt:
Explain this text code:

NAME                        CPU(cores)   MEMORY(bytes)
memory-demo                 <something>  162856960

Response: This text code 3.4 - Assign Pod-level CPU and memory resources | To specify a CPU request for a Pod, include the resources.requests.cpu field in the Pod spec manifest. To specify a CPU limit, include resources.limits.cpu.

Context: 3.4 - Assign Pod-level CPU and memory resources | To specify a CPU request for a Pod, include the resources.requests.cpu field in the Pod spec manifest. To specify a CPU limit, include resources.limits.cpu.


Prompt:
Complete this yaml code:

apiVersion: v1
kind: Pod
metadata:
  name: cpu-demo
  namespace: pod-resources-example
spec:
  resources:
    limits:

Response:
      cpu: "1"
    requests:
      cpu: "0.5"
  containers:
  - name: cpu-demo-ctr
    image: vish/stress
    args:
    - -cpus
    - "2"

Context: 3.4 - Assign Pod-level CPU and memory resources | The args section of the configuration file provides arguments for the container when it starts. The -cpus "2" argument tells the Container to attempt to use 2 CPUs.


Prompt:
Explain this yaml code:

apiVersion: v1
kind: Pod
metadata:
  name: cpu-demo
  namespace: pod-resources-example
spec:
  resources:
    limits:
      cpu: "1"
    requests:
      cpu: "0.5"
  containers:
  - name: cpu-demo-ctr
    image: vish/stress
    args:
    - -cpus
    - "2"

Response: This yaml code 3.4 - Assign Pod-level CPU and memory resources | The args section of the configuration file provides arguments for the container when it starts. The -cpus "2" argument tells the Container to attempt to use 2 CPUs.


Prompt:
Explain this bash code:

kubectl apply -f https://k8s.io/examples/pods/resource/pod-level-cpu-request-limit.yaml --namespace=pod-resources-example

Response: This bash code 3.4 - Assign Pod-level CPU and memory resources | Verify that the Pod is running:


Prompt:
Explain this bash code:

kubectl get pod cpu-demo --namespace=pod-resources-example

Response: This bash code 3.4 - Assign Pod-level CPU and memory resources | View detailed information about the Pod:


Prompt:
Explain this bash code:

kubectl get pod cpu-demo --output=yaml --namespace=pod-resources-example

Response: This bash code 3.4 - Assign Pod-level CPU and memory resources | The output shows that the Pod has a CPU request of 500 milliCPU and a CPU limit of 1 CPU.

Context: 3.4 - Assign Pod-level CPU and memory resources | The output shows that the Pod has a CPU request of 500 milliCPU and a CPU limit of 1 CPU.


Prompt:
Complete this text code:

spec:
  containers:
  ...
  resources:

Response:
    limits:
      cpu: "1"
    requests:
      cpu: 500m

Context: 3.4 - Assign Pod-level CPU and memory resources | Use kubectl top to fetch the metrics for the Pod:


Prompt:
Explain this text code:

spec:
  containers:
  ...
  resources:
    limits:
      cpu: "1"
    requests:
      cpu: 500m

Response: This text code 3.4 - Assign Pod-level CPU and memory resources | Use kubectl top to fetch the metrics for the Pod:


Prompt:
Explain this bash code:

kubectl top pod cpu-demo --namespace=pod-resources-example

Response: This bash code 3.4 - Assign Pod-level CPU and memory resources | This example output shows that the Pod is using 974 milliCPU, which is slightly less than the limit of 1 CPU specified in the Pod configuration.

Context: 3.4 - Assign Pod-level CPU and memory resources | This example output shows that the Pod is using 974 milliCPU, which is slightly less than the limit of 1 CPU specified in the Pod configuration.


Prompt:
Explain this text code:

NAME                        CPU(cores)   MEMORY(bytes)
cpu-demo                    974m         <something>

Response: This text code 3.4 - Assign Pod-level CPU and memory resources | Recall that by setting -cpu "2", you configured the Container to attempt to use 2 CPUs, but the Container is only being allowed to use about 1 CPU. The container's CPU use is being throttled, because

Context: 3.4 - Assign Pod-level CPU and memory resources | Recall that by setting -cpu "2", you configured the Container to attempt to use 2 CPUs, but the Container is only being allowed to use about 1 CPU. The container's CPU use is being throttled, because


Prompt:
Complete this yaml code:

apiVersion: v1
kind: Pod
metadata:
  name: pod-resources-demo
  namespace: pod-resources-example
spec:
  resources:
    limits:
      cpu: "1"
      memory: "200Mi"
    requests:
      cpu: "1"
      memory: "100Mi"
  containers:

Response:
  - name: pod-resources-demo-ctr-1
    image: nginx
    resources:
      limits:
        cpu: "0.5"
        memory: "100Mi"
      requests:
        cpu: "0.5"
        memory: "50Mi"
  - name: pod-resources-demo-ctr-2
    image: fedora
    command:
    - sleep
    - inf

Context: 3.4 - Assign Pod-level CPU and memory resources | Create the Pod:


Prompt:
Explain this yaml code:

apiVersion: v1
kind: Pod
metadata:
  name: pod-resources-demo
  namespace: pod-resources-example
spec:
  resources:
    limits:
      cpu: "1"
      memory: "200Mi"
    requests:
      cpu: "1"
      memory: "100Mi"
  containers:
  - name: pod-resources-demo-ctr-1
    image: nginx
    resources:
      limits:
        cpu: "0.5"
        memory: "100Mi"
      requests:
        cpu: "0.5"
        memory: "50Mi"
  - name: pod-resources-demo-ctr-2
    image: fedora
    command:
    - sleep
    - inf

Response: This yaml code 3.4 - Assign Pod-level CPU and memory resources | Create the Pod:


Prompt:
Explain this bash code:

kubectl apply -f https://k8s.io/examples/pods/resource/pod-level-resources.yaml --namespace=pod-resources-example

Response: This bash code 3.4 - Assign Pod-level CPU and memory resources | Verify that the Pod Container is running:

Context: 3.4 - Assign Pod-level CPU and memory resources | Verify that the Pod Container is running:


Prompt:
Explain this bash code:

kubectl get pod-resources-demo --namespace=pod-resources-example

Response: This bash code 3.4 - Assign Pod-level CPU and memory resources | View detailed information about the Pod:


Prompt:
Explain this bash code:

kubectl get pod memory-demo --output=yaml --namespace=pod-resources-example

Response: This bash code 3.4 - Assign Pod-level CPU and memory resources | The output shows that one container in the Pod has a memory request of 50 MiB and a CPU request of 0.5 cores, with a memory limit of 100 MiB and a CPU limit of 0.5 cores. The Pod itself has a memory r

Context: 3.4 - Assign Pod-level CPU and memory resources | The output shows that one container in the Pod has a memory request of 50 MiB and a CPU request of 0.5 cores, with a memory limit of 100 MiB and a CPU limit of 0.5 cores. The Pod itself has a memory r


Prompt:
Complete this text code:

...
containers:
  name: pod-resources-demo-ctr-1
  resources:
      requests:
        cpu: 500m
        memory: 50Mi
      limits:
        cpu: 500m
        memory: 100Mi

Response:
  ...
  name: pod-resources-demo-ctr-2
  resources: {}
resources:
  limits:
      cpu: 1
      memory: 200Mi
    requests:
      cpu: 1
      memory: 100Mi
...

Context: 3.4 - Assign Pod-level CPU and memory resources | Since pod-level requests and limits are specified, the request guarantees for both containers in the pod will be equal 1 core or CPU and 100Mi of memory. Additionally, both containers together won't b


Prompt:
Explain this text code:

...
containers:
  name: pod-resources-demo-ctr-1
  resources:
      requests:
        cpu: 500m
        memory: 50Mi
      limits:
        cpu: 500m
        memory: 100Mi
  ...
  name: pod-resources-demo-ctr-2
  resources: {}
resources:
  limits:
      cpu: 1
      memory: 200Mi
    requests:
      cpu: 1
      memory: 100Mi
...

Response: This text code 3.4 - Assign Pod-level CPU and memory resources | Since pod-level requests and limits are specified, the request guarantees for both containers in the pod will be equal 1 core or CPU and 100Mi of memory. Additionally, both containers together won't b


Prompt:
Complete this yaml code:

apiVersion: windows.k8s.io/v1
kind: GMSACredentialSpec
metadata:
  name: gmsa-WebApp1  # This is an arbitrary name but it will be used as a reference
credspec:
  ActiveDirectoryConfig:
    GroupManagedServiceAccounts:
    - Name: WebApp1   # Username of the GMSA account
      Scope: CONTOSO  # NETBIOS Domain Name
    - Name: WebApp1   # Username of the GMSA account

Response:
      Scope: contoso.com # DNS Domain Name
  CmsPlugins:
  - ActiveDirectory
  DomainJoinConfig:
    DnsName: contoso.com  # DNS Domain Name
    DnsTreeName: contoso.com # DNS Domain Name Root
    Guid: 244818ae-87ac-4fcd-92ec-e79e5252348a  # GUID of the Domain
    MachineAccountName: WebApp1 # Username of the GMSA account
    NetBiosName: CONTOSO  # NETBIOS Domain Name
    Sid: S-1-5-21-2126449477-2524075714-3094792973 # SID of the Domain

Context: 3.5 - Configure GMSA for Windows Pods and containers | The above credential spec resource may be saved as gmsa-Webapp1-credspec.yaml and applied to the cluster using: kubectl apply -f gmsa-Webapp1-credspec.yml


Prompt:
Explain this yaml code:

apiVersion: windows.k8s.io/v1
kind: GMSACredentialSpec
metadata:
  name: gmsa-WebApp1  # This is an arbitrary name but it will be used as a reference
credspec:
  ActiveDirectoryConfig:
    GroupManagedServiceAccounts:
    - Name: WebApp1   # Username of the GMSA account
      Scope: CONTOSO  # NETBIOS Domain Name
    - Name: WebApp1   # Username of the GMSA account
      Scope: contoso.com # DNS Domain Name
  CmsPlugins:
  - ActiveDirectory
  DomainJoinConfig:
    DnsName: contoso.com  # DNS Domain Name
    DnsTreeName: contoso.com # DNS Domain Name Root
    Guid: 244818ae-87ac-4fcd-92ec-e79e5252348a  # GUID of the Domain
    MachineAccountName: WebApp1 # Username of the GMSA account
    NetBiosName: CONTOSO  # NETBIOS Domain Name
    Sid: S-1-5-21-2126449477-2524075714-3094792973 # SID of the Domain

Response: This yaml code 3.5 - Configure GMSA for Windows Pods and containers | The above credential spec resource may be saved as gmsa-Webapp1-credspec.yaml and applied to the cluster using: kubectl apply -f gmsa-Webapp1-credspec.yml


Prompt:
Complete this yaml code:

# Create the Role to read the credspec
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRole
metadata:
  name: webapp1-role

Response:
rules:
- apiGroups: ["windows.k8s.io"]
  resources: ["gmsacredentialspecs"]
  verbs: ["use"]
  resourceNames: ["gmsa-WebApp1"]

Context: 3.5 - Configure GMSA for Windows Pods and containers | A service account (that Pods will be configured with) needs to be bound to the cluster role create above. This authorizes the service account to use the desired GMSA credential spec resource. The foll


Prompt:
Explain this yaml code:

# Create the Role to read the credspec
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRole
metadata:
  name: webapp1-role
rules:
- apiGroups: ["windows.k8s.io"]
  resources: ["gmsacredentialspecs"]
  verbs: ["use"]
  resourceNames: ["gmsa-WebApp1"]

Response: This yaml code 3.5 - Configure GMSA for Windows Pods and containers | A service account (that Pods will be configured with) needs to be bound to the cluster role create above. This authorizes the service account to use the desired GMSA credential spec resource. The foll


Prompt:
Complete this yaml code:

apiVersion: rbac.authorization.k8s.io/v1
kind: RoleBinding
metadata:
  name: allow-default-svc-account-read-on-gmsa-WebApp1
  namespace: default
subjects:

Response:
- kind: ServiceAccount
  name: default
  namespace: default
roleRef:
  kind: ClusterRole
  name: webapp1-role
  apiGroup: rbac.authorization.k8s.io

Context: 3.5 - Configure GMSA for Windows Pods and containers | The Pod spec field securityContext.windowsOptions.gmsaCredentialSpecName is used to specify references to desired GMSA credential spec custom resources in Pod specs. This configures all containers in


Prompt:
Explain this yaml code:

apiVersion: rbac.authorization.k8s.io/v1
kind: RoleBinding
metadata:
  name: allow-default-svc-account-read-on-gmsa-WebApp1
  namespace: default
subjects:
- kind: ServiceAccount
  name: default
  namespace: default
roleRef:
  kind: ClusterRole
  name: webapp1-role
  apiGroup: rbac.authorization.k8s.io

Response: This yaml code 3.5 - Configure GMSA for Windows Pods and containers | The Pod spec field securityContext.windowsOptions.gmsaCredentialSpecName is used to specify references to desired GMSA credential spec custom resources in Pod specs. This configures all containers in


Prompt:
Complete this yaml code:

apiVersion: apps/v1
kind: Deployment
metadata:
  labels:
    run: with-creds
  name: with-creds
  namespace: default
spec:
  replicas: 1
  selector:
    matchLabels:
      run: with-creds
  template:

Response:
    metadata:
      labels:
        run: with-creds
    spec:
      securityContext:
        windowsOptions:
          gmsaCredentialSpecName: gmsa-webapp1
      containers:
      - image: mcr.microsoft.com/windows/servercore/iis:windowsservercore-ltsc2019
        imagePullPolicy: Always
        name: iis
      nodeSelector:
        kubernetes.io/os: windows

Context: 3.5 - Configure GMSA for Windows Pods and containers | Individual containers in a Pod spec can also specify the desired GMSA credspec using a per-container securityContext.windowsOptions.gmsaCredentialSpecName field. For example:


Prompt:
Explain this yaml code:

apiVersion: apps/v1
kind: Deployment
metadata:
  labels:
    run: with-creds
  name: with-creds
  namespace: default
spec:
  replicas: 1
  selector:
    matchLabels:
      run: with-creds
  template:
    metadata:
      labels:
        run: with-creds
    spec:
      securityContext:
        windowsOptions:
          gmsaCredentialSpecName: gmsa-webapp1
      containers:
      - image: mcr.microsoft.com/windows/servercore/iis:windowsservercore-ltsc2019
        imagePullPolicy: Always
        name: iis
      nodeSelector:
        kubernetes.io/os: windows

Response: This yaml code 3.5 - Configure GMSA for Windows Pods and containers | Individual containers in a Pod spec can also specify the desired GMSA credspec using a per-container securityContext.windowsOptions.gmsaCredentialSpecName field. For example:


Prompt:
Complete this yaml code:

apiVersion: apps/v1
kind: Deployment
metadata:
  labels:
    run: with-creds
  name: with-creds
  namespace: default
spec:
  replicas: 1
  selector:
    matchLabels:
      run: with-creds
  template:

Response:
    metadata:
      labels:
        run: with-creds
    spec:
      containers:
      - image: mcr.microsoft.com/windows/servercore/iis:windowsservercore-ltsc2019
        imagePullPolicy: Always
        name: iis
        securityContext:
          windowsOptions:
            gmsaCredentialSpecName: gmsa-Webapp1
      nodeSelector:
        kubernetes.io/os: windows

Context: 3.5 - Configure GMSA for Windows Pods and containers | As Pod specs with GMSA fields populated (as described above) are applied in a cluster, the following sequence of events take place:


Prompt:
Explain this yaml code:

apiVersion: apps/v1
kind: Deployment
metadata:
  labels:
    run: with-creds
  name: with-creds
  namespace: default
spec:
  replicas: 1
  selector:
    matchLabels:
      run: with-creds
  template:
    metadata:
      labels:
        run: with-creds
    spec:
      containers:
      - image: mcr.microsoft.com/windows/servercore/iis:windowsservercore-ltsc2019
        imagePullPolicy: Always
        name: iis
        securityContext:
          windowsOptions:
            gmsaCredentialSpecName: gmsa-Webapp1
      nodeSelector:
        kubernetes.io/os: windows

Response: This yaml code 3.5 - Configure GMSA for Windows Pods and containers | As Pod specs with GMSA fields populated (as described above) are applied in a cluster, the following sequence of events take place:


Prompt:
Explain this text code:

reg add "HKLM\SYSTEM\CurrentControlSet\Services\hns\State" /v EnableCompartmentNamespace /t REG_DWORD /d 1

Response: This text code 3.5 - Configure GMSA for Windows Pods and containers | Running Pods will then need to be recreated to pick up the behavior changes. More information on how this registry key is used can be found here

Context: 3.5 - Configure GMSA for Windows Pods and containers | Running Pods will then need to be recreated to pick up the behavior changes. More information on how this registry key is used can be found here


Prompt:
Explain this bash code:

kubectl exec -it iis-auth-7776966999-n5nzr powershell.exe

Response: This bash code 3.5 - Configure GMSA for Windows Pods and containers | nltest.exe /parentdomain results in the following error:

Context: 3.5 - Configure GMSA for Windows Pods and containers | nltest.exe /parentdomain results in the following error:


Prompt:
Explain this text code:

Getting parent domain failed: Status = 1722 0x6ba RPC_S_SERVER_UNAVAILABLE

Response: This text code 3.5 - Configure GMSA for Windows Pods and containers | If your Pod did get the credspec correctly, then next check communication with the domain. First, from inside of your Pod, quickly do an nslookup to find the root of your domain.

Context: 3.5 - Configure GMSA for Windows Pods and containers | If your Pod did get the credspec correctly, then next check communication with the domain. First, from inside of your Pod, quickly do an nslookup to find the root of your domain.


Prompt:
Explain this text code:

I_NetLogonControl failed: Status = 1722 0x6ba RPC_S_SERVER_UNAVAILABLE

Response: This text code 3.5 - Configure GMSA for Windows Pods and containers | This tells us that for some reason, the Pod was unable to logon to the domain using the account specified in the credspec. You can try to repair the secure channel by running the following:

Context: 3.5 - Configure GMSA for Windows Pods and containers | This tells us that for some reason, the Pod was unable to logon to the domain using the account specified in the credspec. You can try to repair the secure channel by running the following:


Prompt:
Complete this text code:

Flags: 30 HAS_IP  HAS_TIMESERV
Trusted DC Name \\dc10.domain.example

Response:
Trusted DC Connection Status Status = 0 0x0 NERR_Success
The command completed successfully

Context: 3.5 - Configure GMSA for Windows Pods and containers | If the above corrects the error, you can automate the step by adding the following lifecycle hook to your Pod spec. If it did not correct the error, you will need to examine your credspec again and co


Prompt:
Explain this text code:

Flags: 30 HAS_IP  HAS_TIMESERV
Trusted DC Name \\dc10.domain.example
Trusted DC Connection Status Status = 0 0x0 NERR_Success
The command completed successfully

Response: This text code 3.5 - Configure GMSA for Windows Pods and containers | If the above corrects the error, you can automate the step by adding the following lifecycle hook to your Pod spec. If it did not correct the error, you will need to examine your credspec again and co


Prompt:
Complete this text code:

image: registry.domain.example/iis-auth:1809v1
        lifecycle:
          postStart:

Response:
            exec:
              command: ["powershell.exe","-command","do { Restart-Service -Name netlogon } while ( $($Result = (nltest.exe /query); if ($Result -like '*0x0 NERR_Success*') {return $true} else {return $false}) -eq $false)"]
        imagePullPolicy: IfNotPresent

Context: 3.5 - Configure GMSA for Windows Pods and containers | If you add the lifecycle section show above to your Pod spec, the Pod will execute the commands listed to restart the netlogon service until the nltest.exe /query command exits without error.


Prompt:
Explain this text code:

image: registry.domain.example/iis-auth:1809v1
        lifecycle:
          postStart:
            exec:
              command: ["powershell.exe","-command","do { Restart-Service -Name netlogon } while ( $($Result = (nltest.exe /query); if ($Result -like '*0x0 NERR_Success*') {return $true} else {return $false}) -eq $false)"]
        imagePullPolicy: IfNotPresent

Response: This text code 3.5 - Configure GMSA for Windows Pods and containers | If you add the lifecycle section show above to your Pod spec, the Pod will execute the commands listed to restart the netlogon service until the nltest.exe /query command exits without error.


Prompt:
Complete this text code:

resizePolicy:
    - resourceName: cpu

Response:
      restartPolicy: NotRequired
    - resourceName: memory
      restartPolicy: RestartContainer

Context: 3.6 - Resize CPU and Memory Resources assigned to Containers | If resizePolicy[*].restartPolicy is not specified for a resource, it defaults to NotRequired.


Prompt:
Explain this text code:

resizePolicy:
    - resourceName: cpu
      restartPolicy: NotRequired
    - resourceName: memory
      restartPolicy: RestartContainer

Response: This text code 3.6 - Resize CPU and Memory Resources assigned to Containers | If resizePolicy[*].restartPolicy is not specified for a resource, it defaults to NotRequired.


Prompt:
Complete this yaml code:

apiVersion: v1
kind: Pod
metadata:
  name: resize-demo
spec:
  containers:
  - name: pause
    image: registry.k8s.io/pause:3.8
    resizePolicy:
    - resourceName: cpu

Response:
      restartPolicy: NotRequired # Default, but explicit here
    - resourceName: memory
      restartPolicy: RestartContainer
    resources:
      limits:
        memory: "200Mi"
        cpu: "700m"
      requests:
        memory: "200Mi"
        cpu: "700m"

Context: 3.6 - Resize CPU and Memory Resources assigned to Containers | Create the pod:


Prompt:
Explain this yaml code:

apiVersion: v1
kind: Pod
metadata:
  name: resize-demo
spec:
  containers:
  - name: pause
    image: registry.k8s.io/pause:3.8
    resizePolicy:
    - resourceName: cpu
      restartPolicy: NotRequired # Default, but explicit here
    - resourceName: memory
      restartPolicy: RestartContainer
    resources:
      limits:
        memory: "200Mi"
        cpu: "700m"
      requests:
        memory: "200Mi"
        cpu: "700m"

Response: This yaml code 3.6 - Resize CPU and Memory Resources assigned to Containers | Create the pod:


Prompt:
Explain this text code:

# Wait a moment for the pod to be running
kubectl get pod resize-demo --output=yaml

Response: This text code 3.6 - Resize CPU and Memory Resources assigned to Containers | Observe the spec.containers[0].resources and status.containerStatuses[0].resources. They should match the manifest (700m CPU, 200Mi memory). Note the status.containerStatuses[0].restartCount (should b

Context: 3.6 - Resize CPU and Memory Resources assigned to Containers | Observe the spec.containers[0].resources and status.containerStatuses[0].resources. They should match the manifest (700m CPU, 200Mi memory). Note the status.containerStatuses[0].restartCount (should b


Prompt:
Complete this bash code:

kubectl patch pod resize-demo --subresource resize --patch \
  '{"spec":{"containers":[{"name":"pause", "resources":{"requests":{"cpu":"800m"}, "limits":{"cpu":"800m"}}}]}}'

Response:
# Alternative methods:
# kubectl -n qos-example edit pod resize-demo --subresource resize
# kubectl -n qos-example apply -f <updated-manifest> --subresource resize --server-side

Context: 3.6 - Resize CPU and Memory Resources assigned to Containers | Check the pod status again after patching:


Prompt:
Explain this bash code:

kubectl patch pod resize-demo --subresource resize --patch \
  '{"spec":{"containers":[{"name":"pause", "resources":{"requests":{"cpu":"800m"}, "limits":{"cpu":"800m"}}}]}}'

# Alternative methods:
# kubectl -n qos-example edit pod resize-demo --subresource resize
# kubectl -n qos-example apply -f <updated-manifest> --subresource resize --server-side

Response: This bash code 3.6 - Resize CPU and Memory Resources assigned to Containers | Check the pod status again after patching:


Prompt:
Explain this bash code:

kubectl get pod resize-demo --output=yaml --namespace=qos-example

Response: This bash code 3.6 - Resize CPU and Memory Resources assigned to Containers | You should see:

Context: 3.6 - Resize CPU and Memory Resources assigned to Containers | You should see:


Prompt:
Explain this bash code:

kubectl patch pod resize-demo --subresource resize --patch \
  '{"spec":{"containers":[{"name":"pause", "resources":{"requests":{"memory":"300Mi"}, "limits":{"memory":"300Mi"}}}]}}'

Response: This bash code 3.6 - Resize CPU and Memory Resources assigned to Containers | Check the pod status shortly after patching:

Context: 3.6 - Resize CPU and Memory Resources assigned to Containers | Check the pod status shortly after patching:


Prompt:
Explain this text code:

# Attempt to patch with an excessively large CPU request
kubectl patch pod resize-demo --subresource resize --patch \
  '{"spec":{"containers":[{"name":"pause", "resources":{"requests":{"cpu":"1000"}, "limits":{"cpu":"1000"}}}]}}'

Response: This text code 3.6 - Resize CPU and Memory Resources assigned to Containers | Query the Pod's details:

Context: 3.6 - Resize CPU and Memory Resources assigned to Containers | Query the Pod's details:


Prompt:
Complete this yaml code:

apiVersion: v1
kind: Pod
metadata:
  name: run-as-username-pod-demo
spec:
  securityContext:
    windowsOptions:

Response:
      runAsUserName: "ContainerUser"
  containers:
  - name: run-as-username-demo
    image: mcr.microsoft.com/windows/servercore:ltsc2019
    command: ["ping", "-t", "localhost"]
  nodeSelector:
    kubernetes.io/os: windows

Context: 3.7 - Configure RunAsUserName for Windows pods and containers | Create the Pod:


Prompt:
Explain this yaml code:

apiVersion: v1
kind: Pod
metadata:
  name: run-as-username-pod-demo
spec:
  securityContext:
    windowsOptions:
      runAsUserName: "ContainerUser"
  containers:
  - name: run-as-username-demo
    image: mcr.microsoft.com/windows/servercore:ltsc2019
    command: ["ping", "-t", "localhost"]
  nodeSelector:
    kubernetes.io/os: windows

Response: This yaml code 3.7 - Configure RunAsUserName for Windows pods and containers | Create the Pod:


Prompt:
Explain this bash code:

kubectl apply -f https://k8s.io/examples/windows/run-as-username-pod.yaml

Response: This bash code 3.7 - Configure RunAsUserName for Windows pods and containers | Verify that the Pod's Container is running:

Context: 3.7 - Configure RunAsUserName for Windows pods and containers | Verify that the Pod's Container is running: