Prompt:
Explain this yaml code:

apiVersion: kubescheduler.config.k8s.io/v1alpha1
kind: KubeSchedulerConfiguration
algorithmSource:
  provider: DefaultProvider

...

percentageOfNodesToScore: 50

Response: This yaml code 10.9 - Scheduler Performance Tuning | percentageOfNodesToScore must be a value between 1 and 100 with the default value being calculated based on the cluster size. There is also a hardcoded minimum value of 100 nodes.


Prompt:
Explain this text code:

Zone 1: Node 1, Node 2, Node 3, Node 4
Zone 2: Node 5, Node 6

Response: This text code 10.9 - Scheduler Performance Tuning | The Scheduler evaluates feasibility of the nodes in this order:

Context: 10.9 - Scheduler Performance Tuning | The Scheduler evaluates feasibility of the nodes in this order:


Prompt:
Complete this yaml code:

apiVersion: kubescheduler.config.k8s.io/v1
kind: KubeSchedulerConfiguration
profiles:
- pluginConfig:
  - args:
      scoringStrategy:
        resources:
        - name: cpu

Response:
          weight: 1
        - name: memory
          weight: 1
        - name: intel.com/foo
          weight: 3
        - name: intel.com/bar
          weight: 3
        type: MostAllocated
    name: NodeResourcesFit

Context: 10.10 - Resource Bin Packing | To learn more about other parameters and their default configuration, see the API documentation for NodeResourcesFitArgs.


Prompt:
Explain this yaml code:

apiVersion: kubescheduler.config.k8s.io/v1
kind: KubeSchedulerConfiguration
profiles:
- pluginConfig:
  - args:
      scoringStrategy:
        resources:
        - name: cpu
          weight: 1
        - name: memory
          weight: 1
        - name: intel.com/foo
          weight: 3
        - name: intel.com/bar
          weight: 3
        type: MostAllocated
    name: NodeResourcesFit

Response: This yaml code 10.10 - Resource Bin Packing | To learn more about other parameters and their default configuration, see the API documentation for NodeResourcesFitArgs.


Prompt:
Complete this yaml code:

apiVersion: kubescheduler.config.k8s.io/v1
kind: KubeSchedulerConfiguration
profiles:
- pluginConfig:
  - args:
      scoringStrategy:
        resources:
        - name: intel.com/foo
          weight: 3

Response:
        - name: intel.com/bar
          weight: 3
        requestedToCapacityRatio:
          shape:
          - utilization: 0
            score: 0
          - utilization: 100
            score: 10
        type: RequestedToCapacityRatio
    name: NodeResourcesFit

Context: 10.10 - Resource Bin Packing | Referencing the KubeSchedulerConfiguration file with the kube-scheduler flag --config=/path/to/config/file will pass the configuration to the scheduler.


Prompt:
Explain this yaml code:

apiVersion: kubescheduler.config.k8s.io/v1
kind: KubeSchedulerConfiguration
profiles:
- pluginConfig:
  - args:
      scoringStrategy:
        resources:
        - name: intel.com/foo
          weight: 3
        - name: intel.com/bar
          weight: 3
        requestedToCapacityRatio:
          shape:
          - utilization: 0
            score: 0
          - utilization: 100
            score: 10
        type: RequestedToCapacityRatio
    name: NodeResourcesFit

Response: This yaml code 10.10 - Resource Bin Packing | Referencing the KubeSchedulerConfiguration file with the kube-scheduler flag --config=/path/to/config/file will pass the configuration to the scheduler.


Prompt:
Complete this text code:

shape:
  - utilization: 0

Response:
    score: 0
  - utilization: 100
    score: 10

Context: 10.10 - Resource Bin Packing | The above arguments give the node a score of 0 if utilization is 0% and 10 for utilization 100%, thus enabling bin packing behavior. To enable least requested the score value must be reversed as follo


Prompt:
Explain this text code:

shape:
  - utilization: 0
    score: 0
  - utilization: 100
    score: 10

Response: This text code 10.10 - Resource Bin Packing | The above arguments give the node a score of 0 if utilization is 0% and 10 for utilization 100%, thus enabling bin packing behavior. To enable least requested the score value must be reversed as follo


Prompt:
Complete this text code:

shape:
  - utilization: 0

Response:
    score: 10
  - utilization: 100
    score: 0

Context: 10.10 - Resource Bin Packing | resources is an optional parameter which defaults to:


Prompt:
Explain this text code:

shape:
  - utilization: 0
    score: 10
  - utilization: 100
    score: 0

Response: This text code 10.10 - Resource Bin Packing | resources is an optional parameter which defaults to:


Prompt:
Complete this text code:

resources:
  - name: cpu

Response:
    weight: 1
  - name: memory
    weight: 1

Context: 10.10 - Resource Bin Packing | It can be used to add extended resources as follows:


Prompt:
Explain this text code:

resources:
  - name: cpu
    weight: 1
  - name: memory
    weight: 1

Response: This text code 10.10 - Resource Bin Packing | It can be used to add extended resources as follows:


Prompt:
Complete this text code:

resources:
  - name: intel.com/foo
    weight: 5

Response:
  - name: cpu
    weight: 3
  - name: memory
    weight: 1

Context: 10.10 - Resource Bin Packing | The weight parameter is optional and is set to 1 if not specified. Also, the weight cannot be set to a negative value.


Prompt:
Explain this text code:

resources:
  - name: intel.com/foo
    weight: 5
  - name: cpu
    weight: 3
  - name: memory
    weight: 1

Response: This text code 10.10 - Resource Bin Packing | The weight parameter is optional and is set to 1 if not specified. Also, the weight cannot be set to a negative value.


Prompt:
Complete this text code:

Available:
  intel.com/foo: 4
  memory: 1 GB
  cpu: 8

Response:
Used:
  intel.com/foo: 1
  memory: 256MB
  cpu: 1

Context: 10.10 - Resource Bin Packing | Node score:


Prompt:
Explain this text code:

Available:
  intel.com/foo: 4
  memory: 1 GB
  cpu: 8

Used:
  intel.com/foo: 1
  memory: 256MB
  cpu: 1

Response: This text code 10.10 - Resource Bin Packing | Node score:


Prompt:
Complete this text code:

intel.com/foo  = resourceScoringFunction((2+1),4)
               = (100 - ((4-3)*100/4)
               = (100 - 25)
               = 75                       # requested + used = 75% * available
               = rawScoringFunction(75)
               = 7                        # floor(75/10)

memory         = resourceScoringFunction((256+256),1024)
               = (100 -((1024-512)*100/1024))
               = 50                       # requested + used = 50% * available

Response:
               = rawScoringFunction(50)
               = 5                        # floor(50/10)

cpu            = resourceScoringFunction((2+1),8)
               = (100 -((8-3)*100/8))
               = 37.5                     # requested + used = 37.5% * available
               = rawScoringFunction(37.5)
               = 3                        # floor(37.5/10)

NodeScore   =  ((7 * 5) + (5 * 1) + (3 * 3)) / (5 + 1 + 3)
            =  5

Context: 10.10 - Resource Bin Packing | Node 2 spec:


Prompt:
Explain this text code:

intel.com/foo  = resourceScoringFunction((2+1),4)
               = (100 - ((4-3)*100/4)
               = (100 - 25)
               = 75                       # requested + used = 75% * available
               = rawScoringFunction(75)
               = 7                        # floor(75/10)

memory         = resourceScoringFunction((256+256),1024)
               = (100 -((1024-512)*100/1024))
               = 50                       # requested + used = 50% * available
               = rawScoringFunction(50)
               = 5                        # floor(50/10)

cpu            = resourceScoringFunction((2+1),8)
               = (100 -((8-3)*100/8))
               = 37.5                     # requested + used = 37.5% * available
               = rawScoringFunction(37.5)
               = 3                        # floor(37.5/10)

NodeScore   =  ((7 * 5) + (5 * 1) + (3 * 3)) / (5 + 1 + 3)
            =  5

Response: This text code 10.10 - Resource Bin Packing | Node 2 spec:


Prompt:
Complete this text code:

Available:
  intel.com/foo: 8
  memory: 1GB
  cpu: 8

Response:
Used:
  intel.com/foo: 2
  memory: 512MB
  cpu: 6


Prompt:
Explain this text code:

Available:
  intel.com/foo: 8
  memory: 1GB
  cpu: 8
Used:
  intel.com/foo: 2
  memory: 512MB
  cpu: 6

Response: This text code 10.10 - Resource Bin Packing | Node score:


Prompt:
Complete this text code:

intel.com/foo  = resourceScoringFunction((2+2),8)
               =  (100 - ((8-4)*100/8)
               =  (100 - 50)
               =  50
               =  rawScoringFunction(50)
               = 5

memory         = resourceScoringFunction((256+512),1024)
               = (100 -((1024-768)*100/1024))
               = 75

Response:
               = rawScoringFunction(75)
               = 7

cpu            = resourceScoringFunction((2+6),8)
               = (100 -((8-8)*100/8))
               = 100
               = rawScoringFunction(100)
               = 10

NodeScore   =  ((5 * 5) + (7 * 1) + (10 * 3)) / (5 + 1 + 3)
            =  7

Context: 10.10 - Resource Bin Packing | Pods can have priority. Priority indicates the importance of a Pod relative to other Pods. If a Pod cannot be scheduled, the scheduler tries to preempt (evict) lower priority Pods to make scheduling o


Prompt:
Explain this text code:

intel.com/foo  = resourceScoringFunction((2+2),8)
               =  (100 - ((8-4)*100/8)
               =  (100 - 50)
               =  50
               =  rawScoringFunction(50)
               = 5

memory         = resourceScoringFunction((256+512),1024)
               = (100 -((1024-768)*100/1024))
               = 75
               = rawScoringFunction(75)
               = 7

cpu            = resourceScoringFunction((2+6),8)
               = (100 -((8-8)*100/8))
               = 100
               = rawScoringFunction(100)
               = 10

NodeScore   =  ((5 * 5) + (7 * 1) + (10 * 3)) / (5 + 1 + 3)
            =  7

Response: This text code 10.10 - Resource Bin Packing | Pods can have priority. Priority indicates the importance of a Pod relative to other Pods. If a Pod cannot be scheduled, the scheduler tries to preempt (evict) lower priority Pods to make scheduling o


Prompt:
Complete this yaml code:

apiVersion: scheduling.k8s.io/v1
kind: PriorityClass
metadata:

Response:
  name: high-priority
value: 1000000
globalDefault: false
description: "This priority class should be used for XYZ service pods only."

Context: 10.11 - Pod Priority and Preemption | Pods with preemptionPolicy: Never will be placed in the scheduling queue ahead of lower-priority pods, but they cannot preempt other pods. A non-preempting pod waiting to be scheduled will stay in the


Prompt:
Explain this yaml code:

apiVersion: scheduling.k8s.io/v1
kind: PriorityClass
metadata:
  name: high-priority
value: 1000000
globalDefault: false
description: "This priority class should be used for XYZ service pods only."

Response: This yaml code 10.11 - Pod Priority and Preemption | Pods with preemptionPolicy: Never will be placed in the scheduling queue ahead of lower-priority pods, but they cannot preempt other pods. A non-preempting pod waiting to be scheduled will stay in the


Prompt:
Complete this yaml code:

apiVersion: scheduling.k8s.io/v1
kind: PriorityClass
metadata:
  name: high-priority-nonpreempting

Response:
value: 1000000
preemptionPolicy: Never
globalDefault: false
description: "This priority class will not cause other pods to be preempted."

Context: 10.11 - Pod Priority and Preemption | After you have one or more PriorityClasses, you can create Pods that specify one of those PriorityClass names in their specifications. The priority admission controller uses the priorityClassName fiel


Prompt:
Explain this yaml code:

apiVersion: scheduling.k8s.io/v1
kind: PriorityClass
metadata:
  name: high-priority-nonpreempting
value: 1000000
preemptionPolicy: Never
globalDefault: false
description: "This priority class will not cause other pods to be preempted."

Response: This yaml code 10.11 - Pod Priority and Preemption | After you have one or more PriorityClasses, you can create Pods that specify one of those PriorityClass names in their specifications. The priority admission controller uses the priorityClassName fiel


Prompt:
Complete this yaml code:

apiVersion: v1
kind: Pod
metadata:
  name: nginx
  labels:
    env: test

Response:
spec:
  containers:
  - name: nginx
    image: nginx
    imagePullPolicy: IfNotPresent
  priorityClassName: high-priority

Context: 10.11 - Pod Priority and Preemption | When Pod priority is enabled, the scheduler orders pending Pods by their priority and a pending Pod is placed ahead of other pending Pods with lower priority in the scheduling queue. As a result, the


Prompt:
Explain this yaml code:

apiVersion: v1
kind: Pod
metadata:
  name: nginx
  labels:
    env: test
spec:
  containers:
  - name: nginx
    image: nginx
    imagePullPolicy: IfNotPresent
  priorityClassName: high-priority

Response: This yaml code 10.11 - Pod Priority and Preemption | When Pod priority is enabled, the scheduler orders pending Pods by their priority and a pending Pod is placed ahead of other pending Pods with lower priority in the scheduling queue. As a result, the


Prompt:
Complete this yaml code:

apiVersion: kubelet.config.k8s.io/v1beta1
kind: KubeletConfiguration
evictionHard:
  memory.available: "500Mi"
  nodefs.available: "1Gi"

Response:
  imagefs.available: "100Gi"
evictionMinimumReclaim:
  memory.available: "0Mi"
  nodefs.available: "500Mi"
  imagefs.available: "2Gi"

Context: 10.12 - Node-pressure Eviction | In this example, if the nodefs.available signal meets the eviction threshold, the kubelet reclaims the resource until the signal reaches the threshold of 1GiB, and then continues to reclaim the minimu


Prompt:
Explain this yaml code:

apiVersion: kubelet.config.k8s.io/v1beta1
kind: KubeletConfiguration
evictionHard:
  memory.available: "500Mi"
  nodefs.available: "1Gi"
  imagefs.available: "100Gi"
evictionMinimumReclaim:
  memory.available: "0Mi"
  nodefs.available: "500Mi"
  imagefs.available: "2Gi"

Response: This yaml code 10.12 - Node-pressure Eviction | In this example, if the nodefs.available signal meets the eviction threshold, the kubelet reclaims the resource until the signal reaches the threshold of 1GiB, and then continues to reclaim the minimu


Prompt:
Explain this text code:

--eviction-hard=memory.available<500Mi
--system-reserved=memory=1.5Gi

Response: This text code 10.12 - Node-pressure Eviction | In this configuration, the --system-reserved flag reserves 1.5GiB of memory for the system, which is 10% of the total memory + the eviction threshold amount.

Context: 10.12 - Node-pressure Eviction | In this configuration, the --system-reserved flag reserves 1.5GiB of memory for the system, which is 10% of the total memory + the eviction threshold amount.


Prompt:
Complete this json code:

{
  "apiVersion": "policy/v1",
  "kind": "Eviction",
  "metadata": {

Response:
    "name": "quux",
    "namespace": "default"
  }
}

Context: 10.13 - API-initiated Eviction | Note:Deprecated in v1.22 in favor of policy/v1{ "apiVersion": "policy/v1beta1", "kind": "Eviction", "metadata": { "name": "quux", "namespace": "default" } }


Prompt:
Explain this json code:

{
  "apiVersion": "policy/v1",
  "kind": "Eviction",
  "metadata": {
    "name": "quux",
    "namespace": "default"
  }
}

Response: This json code 10.13 - API-initiated Eviction | Note:Deprecated in v1.22 in favor of policy/v1{ "apiVersion": "policy/v1beta1", "kind": "Eviction", "metadata": { "name": "quux", "namespace": "default" } }


Prompt:
Complete this json code:

{
  "apiVersion": "policy/v1beta1",
  "kind": "Eviction",
  "metadata": {

Response:
    "name": "quux",
    "namespace": "default"
  }
}

Context: 10.13 - API-initiated Eviction | Alternatively, you can attempt an eviction operation by accessing the API using curl or wget, similar to the following example:


Prompt:
Explain this json code:

{
  "apiVersion": "policy/v1beta1",
  "kind": "Eviction",
  "metadata": {
    "name": "quux",
    "namespace": "default"
  }
}

Response: This json code 10.13 - API-initiated Eviction | Alternatively, you can attempt an eviction operation by accessing the API using curl or wget, similar to the following example:


Prompt:
Explain this text code:

curl -v -H 'Content-type: application/json' https://your-cluster-api-endpoint.example/api/v1/namespaces/default/pods/quux/eviction -d @eviction.json

Response: This text code 10.13 - API-initiated Eviction | When you request an eviction using the API, the API server performs admission checks and responds in one of the following ways:

Context: 10.13 - API-initiated Eviction | When you request an eviction using the API, the API server performs admission checks and responds in one of the following ways:


Prompt:
Explain this text code:

Reason:         Terminated
Message:        Pod was terminated in response to imminent node shutdown.

Response: This text code 11.1 - Node Shutdowns | To provide more flexibility during graceful node shutdown around the ordering of pods during shutdown, graceful node shutdown honors the PriorityClass for Pods, provided that you enabled this feature

Context: 11.1 - Node Shutdowns | To provide more flexibility during graceful node shutdown around the ordering of pods during shutdown, graceful node shutdown honors the PriorityClass for Pods, provided that you enabled this feature


Prompt:
Complete this text code:

shutdownGracePeriodByPodPriority:
  - priority: 100000
    shutdownGracePeriodSeconds: 10
  - priority: 10000

Response:
    shutdownGracePeriodSeconds: 180
  - priority: 1000
    shutdownGracePeriodSeconds: 120
  - priority: 0
    shutdownGracePeriodSeconds: 60

Context: 11.1 - Node Shutdowns | The above table implies that any pod with priority value >= 100000 will get just 10 seconds to shut down, any pod with value >= 10000 and < 100000 will get 180 seconds to shut down, any pod with value


Prompt:
Explain this text code:

shutdownGracePeriodByPodPriority:
  - priority: 100000
    shutdownGracePeriodSeconds: 10
  - priority: 10000
    shutdownGracePeriodSeconds: 180
  - priority: 1000
    shutdownGracePeriodSeconds: 120
  - priority: 0
    shutdownGracePeriodSeconds: 60

Response: This text code 11.1 - Node Shutdowns | The above table implies that any pod with priority value >= 100000 will get just 10 seconds to shut down, any pod with value >= 10000 and < 100000 will get 180 seconds to shut down, any pod with value


Prompt:
Complete this text code:

NAME    CPU(cores)   CPU(%)   MEMORY(bytes)   MEMORY(%)   SWAP(bytes)    SWAP(%)
node1   1m           10%      2Mi             10%         1Mi            0%

Response:
node2   5m           10%      6Mi             10%         2Mi            0%
node3   3m           10%      4Mi             10%         <unknown>      <unknown>

Context: 11.2 - Swap memory management | In order to receive information about swap usage by pods, kubectl top nodes --show-swap can be used:


Prompt:
Explain this text code:

NAME    CPU(cores)   CPU(%)   MEMORY(bytes)   MEMORY(%)   SWAP(bytes)    SWAP(%)
node1   1m           10%      2Mi             10%         1Mi            0%
node2   5m           10%      6Mi             10%         2Mi            0%
node3   3m           10%      4Mi             10%         <unknown>      <unknown>

Response: This text code 11.2 - Swap memory management | In order to receive information about swap usage by pods, kubectl top nodes --show-swap can be used:


Prompt:
Complete this text code:

NAME                                      CPU(cores)   MEMORY(bytes)   SWAP(bytes)
coredns-58d5bc5cdb-5nbk4                  2m           19Mi            0Mi
coredns-58d5bc5cdb-jsh26                  3m           37Mi            0Mi
etcd-node01                               51m          143Mi           5Mi
kube-apiserver-node01                     98m          824Mi           16Mi

Response:
kube-controller-manager-node01            20m          135Mi           9Mi
kube-proxy-ffgs2                          1m           24Mi            0Mi
kube-proxy-fhvwx                          1m           39Mi            0Mi
kube-scheduler-node01                     13m          69Mi            0Mi
metrics-server-8598789fdb-d2kcj           5m           26Mi            0Mi

Context: 11.2 - Swap memory management | A new node status field is now added, node.status.nodeInfo.swap.capacity, to report the swap capacity of a node.


Prompt:
Explain this text code:

NAME                                      CPU(cores)   MEMORY(bytes)   SWAP(bytes)
coredns-58d5bc5cdb-5nbk4                  2m           19Mi            0Mi
coredns-58d5bc5cdb-jsh26                  3m           37Mi            0Mi
etcd-node01                               51m          143Mi           5Mi
kube-apiserver-node01                     98m          824Mi           16Mi
kube-controller-manager-node01            20m          135Mi           9Mi
kube-proxy-ffgs2                          1m           24Mi            0Mi
kube-proxy-fhvwx                          1m           39Mi            0Mi
kube-scheduler-node01                     13m          69Mi            0Mi
metrics-server-8598789fdb-d2kcj           5m           26Mi            0Mi

Response: This text code 11.2 - Swap memory management | A new node status field is now added, node.status.nodeInfo.swap.capacity, to report the swap capacity of a node.


Prompt:
Explain this bash code:

kubectl get nodes -o go-template='{{range .items}}{{.metadata.name}}: {{if .status.nodeInfo.swap.capacity}}{{.status.nodeInfo.swap.capacity}}{{else}}<unknown>{{end}}{{"\n"}}{{end}}'

Response: This bash code 11.2 - Swap memory management | This will result in an output similar to:

Context: 11.2 - Swap memory management | This will result in an output similar to:


Prompt:
Explain this text code:

node1: 21474836480
node2: 42949664768
node3: <unknown>

Response: This text code 11.2 - Swap memory management | Node Feature Discovery is a Kubernetes addon for detecting hardware features and configuration. It can be utilized to discover which nodes are provisioned with swap.

Context: 11.2 - Swap memory management | Node Feature Discovery is a Kubernetes addon for detecting hardware features and configuration. It can be utilized to discover which nodes are provisioned with swap.


Prompt:
Explain this bash code:

kubectl get nodes -o jsonpath='{range .items[?(@.metadata.labels.feature\.node\.kubernetes\.io/memory-swap)]}{.metadata.name}{"\t"}{.metadata.labels.feature\.node\.kubernetes\.io/memory-swap}{"\n"}{end}'

Response: This bash code 11.2 - Swap memory management | This will result in an output similar to:


Prompt:
Explain this text code:

k8s-worker1: true
k8s-worker2: true
k8s-worker3: false

Response: This text code 11.2 - Swap memory management | In this example, swap is provisioned on nodes k8s-worker1 and k8s-worker2, but not on k8s-worker3.

Context: 11.2 - Swap memory management | In this example, swap is provisioned on nodes k8s-worker1 and k8s-worker2, but not on k8s-worker3.


Prompt:
Complete this yaml code:

apiVersion: v1
kind: Pod
metadata:
  name: counter
spec:

Response:
  containers:
  - name: count
    image: busybox:1.28
    args: [/bin/sh, -c,
            'i=0; while true; do echo "$i: $(date)"; i=$((i+1)); sleep 1; done']

Context: 11.8 - Logging Architecture | To run this pod, use the following command:


Prompt:
Explain this yaml code:

apiVersion: v1
kind: Pod
metadata:
  name: counter
spec:
  containers:
  - name: count
    image: busybox:1.28
    args: [/bin/sh, -c,
            'i=0; while true; do echo "$i: $(date)"; i=$((i+1)); sleep 1; done']

Response: This yaml code 11.8 - Logging Architecture | To run this pod, use the following command:


Prompt:
Explain this bash code:

kubectl apply -f https://k8s.io/examples/debug/counter-pod.yaml

Response: This bash code 11.8 - Logging Architecture | The output is:

Context: 11.8 - Logging Architecture | The output is:


Prompt:
Explain this text code:

0: Fri Apr  1 11:42:23 UTC 2022
1: Fri Apr  1 11:42:24 UTC 2022
2: Fri Apr  1 11:42:25 UTC 2022

Response: This text code 11.8 - Logging Architecture | You can use kubectl logs --previous to retrieve logs from a previous instantiation of a container. If your pod has multiple containers, specify which container's logs you want to access by appending a

Context: 11.8 - Logging Architecture | You can use kubectl logs --previous to retrieve logs from a previous instantiation of a container. If your pod has multiple containers, specify which container's logs you want to access by appending a


Prompt:
Complete this yaml code:

apiVersion: v1
kind: Pod
metadata:
  name: counter-err
spec:

Response:
  containers:
  - name: count
    image: busybox:1.28
    args: [/bin/sh, -c,
            'i=0; while true; do echo "$i: $(date)"; echo "$i: err" >&2 ; i=$((i+1)); sleep 1; done']


Prompt:
Explain this yaml code:

apiVersion: v1
kind: Pod
metadata:
  name: counter-err
spec:
  containers:
  - name: count
    image: busybox:1.28
    args: [/bin/sh, -c,
            'i=0; while true; do echo "$i: $(date)"; echo "$i: err" >&2 ; i=$((i+1)); sleep 1; done']

Response: This yaml code 11.8 - Logging Architecture | To run this pod, use the following command:


Prompt:
Explain this bash code:

kubectl apply -f https://k8s.io/examples/debug/counter-pod-err.yaml

Response: This bash code 11.8 - Logging Architecture | To fetch only the stderr log stream, you can run:

Context: 11.8 - Logging Architecture | To fetch only the stderr log stream, you can run:


Prompt:
Explain this bash code:

kubectl get --raw "/api/v1/namespaces/default/pods/counter-err/log?stream=Stderr"

Response: This bash code 11.8 - Logging Architecture | See the kubectl logs documentation for more details.

Context: 11.8 - Logging Architecture | See the kubectl logs documentation for more details.


Prompt:
Complete this yaml code:

apiVersion: v1
kind: Pod
metadata:
  name: counter
spec:
  containers:
  - name: count
    image: busybox:1.28
    args:
    - /bin/sh
    - -c
    - >
      i=0;

Response:
      while true;
      do
        echo "$i: $(date)" >> /var/log/1.log;
        echo "$(date) INFO $i" >> /var/log/2.log;
        i=$((i+1));
        sleep 1;
      done
    volumeMounts:
    - name: varlog
      mountPath: /var/log
  volumes:
  - name: varlog
    emptyDir: {}

Context: 11.8 - Logging Architecture | It is not recommended to write log entries with different formats to the same log stream, even if you managed to redirect both components to the stdout stream of the container. Instead, you can create


Prompt:
Explain this yaml code:

apiVersion: v1
kind: Pod
metadata:
  name: counter
spec:
  containers:
  - name: count
    image: busybox:1.28
    args:
    - /bin/sh
    - -c
    - >
      i=0;
      while true;
      do
        echo "$i: $(date)" >> /var/log/1.log;
        echo "$(date) INFO $i" >> /var/log/2.log;
        i=$((i+1));
        sleep 1;
      done
    volumeMounts:
    - name: varlog
      mountPath: /var/log
  volumes:
  - name: varlog
    emptyDir: {}

Response: This yaml code 11.8 - Logging Architecture | It is not recommended to write log entries with different formats to the same log stream, even if you managed to redirect both components to the stdout stream of the container. Instead, you can create


Prompt:
Complete this yaml code:

apiVersion: v1
kind: Pod
metadata:
  name: counter
spec:
  containers:
  - name: count
    image: busybox:1.28
    args:
    - /bin/sh
    - -c
    - >
      i=0;
      while true;
      do
        echo "$i: $(date)" >> /var/log/1.log;
        echo "$(date) INFO $i" >> /var/log/2.log;
        i=$((i+1));
        sleep 1;

Response:
      done
    volumeMounts:
    - name: varlog
      mountPath: /var/log
  - name: count-log-1
    image: busybox:1.28
    args: [/bin/sh, -c, 'tail -n+1 -F /var/log/1.log']
    volumeMounts:
    - name: varlog
      mountPath: /var/log
  - name: count-log-2
    image: busybox:1.28
    args: [/bin/sh, -c, 'tail -n+1 -F /var/log/2.log']
    volumeMounts:
    - name: varlog
      mountPath: /var/log
  volumes:
  - name: varlog
    emptyDir: {}

Context: 11.8 - Logging Architecture | Now when you run this pod, you can access each log stream separately by running the following commands:


Prompt:
Explain this yaml code:

apiVersion: v1
kind: Pod
metadata:
  name: counter
spec:
  containers:
  - name: count
    image: busybox:1.28
    args:
    - /bin/sh
    - -c
    - >
      i=0;
      while true;
      do
        echo "$i: $(date)" >> /var/log/1.log;
        echo "$(date) INFO $i" >> /var/log/2.log;
        i=$((i+1));
        sleep 1;
      done
    volumeMounts:
    - name: varlog
      mountPath: /var/log
  - name: count-log-1
    image: busybox:1.28
    args: [/bin/sh, -c, 'tail -n+1 -F /var/log/1.log']
    volumeMounts:
    - name: varlog
      mountPath: /var/log
  - name: count-log-2
    image: busybox:1.28
    args: [/bin/sh, -c, 'tail -n+1 -F /var/log/2.log']
    volumeMounts:
    - name: varlog
      mountPath: /var/log
  volumes:
  - name: varlog
    emptyDir: {}

Response: This yaml code 11.8 - Logging Architecture | Now when you run this pod, you can access each log stream separately by running the following commands:


Prompt:
Complete this text code:

0: Fri Apr  1 11:42:26 UTC 2022
1: Fri Apr  1 11:42:27 UTC 2022

Response:
2: Fri Apr  1 11:42:28 UTC 2022
...

Context: 11.8 - Logging Architecture | The output is similar to:


Prompt:
Explain this text code:

0: Fri Apr  1 11:42:26 UTC 2022
1: Fri Apr  1 11:42:27 UTC 2022
2: Fri Apr  1 11:42:28 UTC 2022
...

Response: This text code 11.8 - Logging Architecture | The output is similar to:


Prompt:
Complete this text code:

Fri Apr  1 11:42:29 UTC 2022 INFO 0
Fri Apr  1 11:42:30 UTC 2022 INFO 0

Response:
Fri Apr  1 11:42:31 UTC 2022 INFO 0
...

Context: 11.8 - Logging Architecture | If you installed a node-level agent in your cluster, that agent picks up those log streams automatically without any further configuration. If you like, you can configure the agent to parse log lines


Prompt:
Explain this text code:

Fri Apr  1 11:42:29 UTC 2022 INFO 0
Fri Apr  1 11:42:30 UTC 2022 INFO 0
Fri Apr  1 11:42:31 UTC 2022 INFO 0
...

Response: This text code 11.8 - Logging Architecture | If you installed a node-level agent in your cluster, that agent picks up those log streams automatically without any further configuration. If you like, you can configure the agent to parse log lines


Prompt:
Complete this yaml code:

apiVersion: v1
kind: ConfigMap
metadata:
  name: fluentd-config
data:
  fluentd.conf: |
    <source>
      type tail
      format none
      path /var/log/1.log
      pos_file /var/log/1.log.pos
      tag count.format1

Response:
    </source>

    <source>
      type tail
      format none
      path /var/log/2.log
      pos_file /var/log/2.log.pos
      tag count.format2
    </source>

    <match **>
      type google_cloud
    </match>

Context: 11.8 - Logging Architecture | The second manifest describes a pod that has a sidecar container running fluentd. The pod mounts a volume where fluentd can pick up its configuration data.


Prompt:
Explain this yaml code:

apiVersion: v1
kind: ConfigMap
metadata:
  name: fluentd-config
data:
  fluentd.conf: |
    <source>
      type tail
      format none
      path /var/log/1.log
      pos_file /var/log/1.log.pos
      tag count.format1
    </source>

    <source>
      type tail
      format none
      path /var/log/2.log
      pos_file /var/log/2.log.pos
      tag count.format2
    </source>

    <match **>
      type google_cloud
    </match>

Response: This yaml code 11.8 - Logging Architecture | The second manifest describes a pod that has a sidecar container running fluentd. The pod mounts a volume where fluentd can pick up its configuration data.


Prompt:
Complete this yaml code:

apiVersion: v1
kind: Pod
metadata:
  name: counter
spec:
  containers:
  - name: count
    image: busybox:1.28
    args:
    - /bin/sh
    - -c
    - >
      i=0;
      while true;
      do
        echo "$i: $(date)" >> /var/log/1.log;
        echo "$(date) INFO $i" >> /var/log/2.log;
        i=$((i+1));
        sleep 1;

Response:
      done
    volumeMounts:
    - name: varlog
      mountPath: /var/log
  - name: count-agent
    image: registry.k8s.io/fluentd-gcp:1.30
    env:
    - name: FLUENTD_ARGS
      value: -c /etc/fluentd-config/fluentd.conf
    volumeMounts:
    - name: varlog
      mountPath: /var/log
    - name: config-volume
      mountPath: /etc/fluentd-config
  volumes:
  - name: varlog
    emptyDir: {}
  - name: config-volume
    configMap:
      name: fluentd-config

Context: 11.8 - Logging Architecture |


Prompt:
Explain this yaml code:

apiVersion: v1
kind: Pod
metadata:
  name: counter
spec:
  containers:
  - name: count
    image: busybox:1.28
    args:
    - /bin/sh
    - -c
    - >
      i=0;
      while true;
      do
        echo "$i: $(date)" >> /var/log/1.log;
        echo "$(date) INFO $i" >> /var/log/2.log;
        i=$((i+1));
        sleep 1;
      done
    volumeMounts:
    - name: varlog
      mountPath: /var/log
  - name: count-agent
    image: registry.k8s.io/fluentd-gcp:1.30
    env:
    - name: FLUENTD_ARGS
      value: -c /etc/fluentd-config/fluentd.conf
    volumeMounts:
    - name: varlog
      mountPath: /var/log
    - name: config-volume
      mountPath: /etc/fluentd-config
  volumes:
  - name: varlog
    emptyDir: {}
  - name: config-volume
    configMap:
      name: fluentd-config

Response: This yaml code 11.8 - Logging Architecture |

Context: 11.8 - Logging Architecture |


Prompt:
Complete this yaml code:

apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRole
metadata:
  name: prometheus

Response:
rules:
  - nonResourceURLs:
      - "/metrics"
    verbs:
      - get

Context: 11.10 - Metrics For Kubernetes System Components | Alpha metric → Stable metric → Deprecated metric → Hidden metric → Deleted metric


Prompt:
Explain this yaml code:

apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRole
metadata:
  name: prometheus
rules:
  - nonResourceURLs:
      - "/metrics"
    verbs:
      - get

Response: This yaml code 11.10 - Metrics For Kubernetes System Components | Alpha metric → Stable metric → Deprecated metric → Hidden metric → Deleted metric


Prompt:
Explain this text code:

# HELP some_counter this counts things
# TYPE some_counter counter
some_counter 0

Response: This text code 11.10 - Metrics For Kubernetes System Components | After deprecation

Context: 11.10 - Metrics For Kubernetes System Components | After deprecation


Prompt:
Explain this text code:

# HELP some_counter (Deprecated since 1.15.0) this counts things
# TYPE some_counter counter
some_counter 0

Response: This text code 11.10 - Metrics For Kubernetes System Components | Hidden metrics are no longer published for scraping, but are still available for use. To use a hidden metric, please refer to the Show hidden metrics section.

Context: 11.10 - Metrics For Kubernetes System Components | Hidden metrics are no longer published for scraping, but are still available for use. To use a hidden metric, please refer to the Show hidden metrics section.


Prompt:
Complete this text code:

cloudprovider_gce_api_request_duration_seconds { request = "instance_list"}
cloudprovider_gce_api_request_duration_seconds { request = "disk_insert"}
cloudprovider_gce_api_request_duration_seconds { request = "disk_delete"}

Response:
cloudprovider_gce_api_request_duration_seconds { request = "attach_disk"}
cloudprovider_gce_api_request_duration_seconds { request = "detach_disk"}
cloudprovider_gce_api_request_duration_seconds { request = "list_disk"}

Context: 11.10 - Metrics For Kubernetes System Components | The scheduler exposes optional metrics that reports the requested resources and the desired limits of all running pods. These metrics can be used to build capacity planning dashboards, assess current


Prompt:
Explain this text code:

cloudprovider_gce_api_request_duration_seconds { request = "instance_list"}
cloudprovider_gce_api_request_duration_seconds { request = "disk_insert"}
cloudprovider_gce_api_request_duration_seconds { request = "disk_delete"}
cloudprovider_gce_api_request_duration_seconds { request = "attach_disk"}
cloudprovider_gce_api_request_duration_seconds { request = "detach_disk"}
cloudprovider_gce_api_request_duration_seconds { request = "list_disk"}

Response: This text code 11.10 - Metrics For Kubernetes System Components | The scheduler exposes optional metrics that reports the requested resources and the desired limits of all running pods. These metrics can be used to build capacity planning dashboards, assess current


Prompt:
Complete this text code:

container_pressure_cpu_stalled_seconds_total
container_pressure_cpu_waiting_seconds_total
container_pressure_memory_stalled_seconds_total

Response:
container_pressure_memory_waiting_seconds_total
container_pressure_io_stalled_seconds_total
container_pressure_io_waiting_seconds_total

Context: 11.10 - Metrics For Kubernetes System Components | This feature is enabled by default, by setting the KubeletPSI feature gate. The information is also exposed in the Summary API.


Prompt:
Explain this text code:

container_pressure_cpu_stalled_seconds_total
container_pressure_cpu_waiting_seconds_total
container_pressure_memory_stalled_seconds_total
container_pressure_memory_waiting_seconds_total
container_pressure_io_stalled_seconds_total
container_pressure_io_waiting_seconds_total

Response: This text code 11.10 - Metrics For Kubernetes System Components | This feature is enabled by default, by setting the KubeletPSI feature gate. The information is also exposed in the Summary API.


Prompt:
Explain this text code:

--allow-metric-labels <metric_name>,<label_name>='<allow_value1>, <allow_value2>...', <metric_name2>,<label_name>='<allow_value1>, <allow_value2>...', ...

Response: This text code 11.10 - Metrics For Kubernetes System Components | Here is an example:

Context: 11.10 - Metrics For Kubernetes System Components | Here is an example:


Prompt:
Explain this text code:

--allow-metric-labels number_count_metric,odd_number='1,3,5', number_count_metric,even_number='2,4,6', date_gauge_metric,weekend='Saturday,Sunday'

Response: This text code 11.10 - Metrics For Kubernetes System Components | In addition to specifying this from the CLI, this can also be done within a configuration file. You can specify the path to that configuration file using the --allow-metric-labels-manifest command lin

Context: 11.10 - Metrics For Kubernetes System Components | In addition to specifying this from the CLI, this can also be done within a configuration file. You can specify the path to that configuration file using the --allow-metric-labels-manifest command lin


Prompt:
Explain this text code:

"metric1,label2": "v1,v2,v3"
"metric2,label1": "v1,v2,v3"

Response: This text code 11.10 - Metrics For Kubernetes System Components | Additionally, the cardinality_enforcement_unexpected_categorizations_total meta-metric records the count of unexpected categorizations during cardinality enforcement, that is, whenever a label value i

Context: 11.10 - Metrics For Kubernetes System Components | Additionally, the cardinality_enforcement_unexpected_categorizations_total meta-metric records the count of unexpected categorizations during cardinality enforcement, that is, whenever a label value i


Prompt:
Explain this text code:

count(kube_pod_status_ready{condition="false"}) by (namespace, pod)

Response: This text code 11.11 - Metrics for Kubernetes Object States | Metrics generated from kube-state-metrics also allow for alerting on issues in the cluster.

Context: 11.11 - Metrics for Kubernetes Object States | Metrics generated from kube-state-metrics also allow for alerting on issues in the cluster.


Prompt:
Complete this text code:

groups:
- name: Pod state
  rules:
  - alert: PodsBlockedInTerminatingState
    expr: count(kube_pod_deletion_timestamp) by (namespace, pod) * count(kube_pod_status_reason{reason="NodeLost"} == 0) by (namespace, pod) > 0

Response:
    for: 5m
    labels:
      severity: page
    annotations:
      summary: Pod {{$labels.namespace}}/{{$labels.pod}} blocked in Terminating state.

Context: 11.11 - Metrics for Kubernetes Object States | System component logs record events happening in cluster, which can be very useful for debugging. You can configure log verbosity to see more or less detail. Logs can be as coarse-grained as showing e


Prompt:
Explain this text code:

groups:
- name: Pod state
  rules:
  - alert: PodsBlockedInTerminatingState
    expr: count(kube_pod_deletion_timestamp) by (namespace, pod) * count(kube_pod_status_reason{reason="NodeLost"} == 0) by (namespace, pod) > 0
    for: 5m
    labels:
      severity: page
    annotations:
      summary: Pod {{$labels.namespace}}/{{$labels.pod}} blocked in Terminating state.

Response: This text code 11.11 - Metrics for Kubernetes Object States | System component logs record events happening in cluster, which can be very useful for debugging. You can configure log verbosity to see more or less detail. Logs can be as coarse-grained as showing e


Prompt:
Explain this text code:

I1025 00:15:15.525108       1 httplog.go:79] GET /api/v1/namespaces/kube-system/pods/metrics-server-v0.3.1-57c75779f-9p8wg: (1.512ms) 200 [pod_nanny/v0.0.0 (linux/amd64) kubernetes/$Format 10.56.1.19:51756]

Response: This text code 11.12 - System Logs | The message string may contain line breaks:

Context: 11.12 - System Logs | The message string may contain line breaks:


Prompt:
Explain this text code:

I1025 00:15:15.525108       1 example.go:79] This is a message
which has a line break.

Response: This text code 11.12 - System Logs | Migration to structured log messages is an ongoing process. Not all log messages are structured in this version. When parsing log files, you must also handle unstructured log messages.

Context: 11.12 - System Logs | Migration to structured log messages is an ongoing process. Not all log messages are structured in this version. When parsing log files, you must also handle unstructured log messages.


Prompt:
Explain this text code:

<klog header> "<message>" <key1>="<value1>" <key2>="<value2>" ...

Response: This text code 11.12 - System Logs | Example:

Context: 11.12 - System Logs | Example:


Prompt:
Explain this text code:

I1025 00:15:15.525108       1 controller_utils.go:116] "Pod status updated" pod="kube-system/kubedns" status="ready"

Response: This text code 11.12 - System Logs | Strings are quoted. Other values are formatted with %+v, which may cause log messages to continue on the next line depending on the data.

Context: 11.12 - System Logs | Strings are quoted. Other values are formatted with %+v, which may cause log messages to continue on the next line depending on the data.


Prompt:
Explain this text code:

I1025 00:15:15.525108       1 example.go:116] "Example" data="This is text with a line break\nand \"quotation marks\"." someInt=1 someFloat=0.1 someStruct={StringField: First line,
second line.}

Response: This text code 11.12 - System Logs | Contextual logging builds on top of structured logging. It is primarily about how developers use logging calls: code based on that concept is more flexible and supports additional use cases as describ

Context: 11.12 - System Logs | Contextual logging builds on top of structured logging. It is primarily about how developers use logging calls: code based on that concept is more flexible and supports additional use cases as describ


Prompt:
Complete this text code:

$ cd $GOPATH/src/k8s.io/kubernetes/staging/src/k8s.io/component-base/logs/example/cmd/
$ go run . --help
...
      --feature-gates mapStringBool  A set of key=value pairs that describe feature gates for alpha/experimental features. Options are:
                                     AllAlpha=true|false (ALPHA - default=false)

Response:
                                     AllBeta=true|false (BETA - default=false)
                                     ContextualLogging=true|false (BETA - default=true)
$ go run . --feature-gates ContextualLogging=true
...
I0222 15:13:31.645988  197901 example.go:54] "runtime" logger="example.myname" foo="bar" duration="1m0s"
I0222 15:13:31.646007  197901 example.go:55] "another runtime" logger="example" foo="bar" duration="1h0m0s" duration="1m0s"

Context: 11.12 - System Logs | The logger key and foo="bar" were added by the caller of the function which logs the runtime message and duration="1m0s" value, without having to modify that function.


Prompt:
Explain this text code:

$ cd $GOPATH/src/k8s.io/kubernetes/staging/src/k8s.io/component-base/logs/example/cmd/
$ go run . --help
...
      --feature-gates mapStringBool  A set of key=value pairs that describe feature gates for alpha/experimental features. Options are:
                                     AllAlpha=true|false (ALPHA - default=false)
                                     AllBeta=true|false (BETA - default=false)
                                     ContextualLogging=true|false (BETA - default=true)
$ go run . --feature-gates ContextualLogging=true
...
I0222 15:13:31.645988  197901 example.go:54] "runtime" logger="example.myname" foo="bar" duration="1m0s"
I0222 15:13:31.646007  197901 example.go:55] "another runtime" logger="example" foo="bar" duration="1h0m0s" duration="1m0s"

Response: This text code 11.12 - System Logs | The logger key and foo="bar" were added by the caller of the function which logs the runtime message and duration="1m0s" value, without having to modify that function.


Prompt:
Complete this text code:

$ go run . --feature-gates ContextualLogging=false
...

Response:
I0222 15:14:40.497333  198174 example.go:54] "runtime" duration="1m0s"
I0222 15:14:40.497346  198174 example.go:55] "another runtime" duration="1h0m0s" duration="1m0s"

Context: 11.12 - System Logs | JSON output does not support many standard klog flags. For list of unsupported klog flags, see the Command line tool reference.


Prompt:
Explain this text code:

$ go run . --feature-gates ContextualLogging=false
...
I0222 15:14:40.497333  198174 example.go:54] "runtime" duration="1m0s"
I0222 15:14:40.497346  198174 example.go:55] "another runtime" duration="1h0m0s" duration="1m0s"

Response: This text code 11.12 - System Logs | JSON output does not support many standard klog flags. For list of unsupported klog flags, see the Command line tool reference.


Prompt:
Complete this json code:

{
   "ts": 1580306777.04728,
   "v": 4,
   "msg": "Pod status updated",
   "pod":{

Response:
      "name": "nginx-1",
      "namespace": "default"
   },
   "status": "ready"
}

Context: 11.12 - System Logs | Keys with special meaning:


Prompt:
Explain this json code:

{
   "ts": 1580306777.04728,
   "v": 4,
   "msg": "Pod status updated",
   "pod":{
      "name": "nginx-1",
      "namespace": "default"
   },
   "status": "ready"
}

Response: This json code 11.12 - System Logs | Keys with special meaning:


Prompt:
Explain this text code:

# Fetch kubelet logs from a node named node-1.example
kubectl get --raw "/api/v1/nodes/node-1.example/proxy/logs/?query=kubelet"

Response: This text code 11.12 - System Logs | You can also fetch files, provided that the files are in a directory that the kubelet allows for log fetches. For example, you can fetch a log from /var/log on a Linux node:

Context: 11.12 - System Logs | You can also fetch files, provided that the files are in a directory that the kubelet allows for log fetches. For example, you can fetch a log from /var/log on a Linux node:


Prompt:
Explain this bash code:

kubectl get --raw "/api/v1/nodes/<insert-node-name-here>/proxy/logs/?query=/<insert-log-file-name-here>"

Response: This bash code 11.12 - System Logs | The kubelet uses heuristics to retrieve logs. This helps if you are not aware whether a given system service is writing logs to the operating system's native logger like journald or to a log file in /

Context: 11.12 - System Logs | The kubelet uses heuristics to retrieve logs. This helps if you are not aware whether a given system service is writing logs to the operating system's native logger like journald or to a log file in /


Prompt:
Explain this text code:

# Fetch kubelet logs from a node named node-1.example that have the word "error"
kubectl get --raw "/api/v1/nodes/node-1.example/proxy/logs/?query=kubelet&pattern=error"

Response: This text code 11.12 - System Logs | System component traces record the latency of and relationships between operations in the cluster.

Context: 11.12 - System Logs | System component traces record the latency of and relationships between operations in the cluster.


Prompt:
Complete this text code:

receivers:
  otlp:
    protocols:
      grpc:
exporters:
  # Replace this exporter with the exporter for your backend
  exporters:

Response:
    debug:
      verbosity: detailed
service:
  pipelines:
    traces:
      receivers: [otlp]
      exporters: [debug]

Context: 11.13 - Traces For Kubernetes System Components | To directly emit traces to a backend without utilizing a collector, specify the endpoint field in the Kubernetes tracing configuration file with the desired trace backend address. This method negates


Prompt:
Explain this text code:

receivers:
  otlp:
    protocols:
      grpc:
exporters:
  # Replace this exporter with the exporter for your backend
  exporters:
    debug:
      verbosity: detailed
service:
  pipelines:
    traces:
      receivers: [otlp]
      exporters: [debug]

Response: This text code 11.13 - Traces For Kubernetes System Components | To directly emit traces to a backend without utilizing a collector, specify the endpoint field in the Kubernetes tracing configuration file with the desired trace backend address. This method negates


Prompt:
Complete this yaml code:

apiVersion: apiserver.config.k8s.io/v1
kind: TracingConfiguration

Response:
# default value
#endpoint: localhost:4317
samplingRatePerMillion: 100

Context: 11.13 - Traces For Kubernetes System Components | For more information about the TracingConfiguration struct, see API server config API (v1).


Prompt:
Explain this yaml code:

apiVersion: apiserver.config.k8s.io/v1
kind: TracingConfiguration
# default value
#endpoint: localhost:4317
samplingRatePerMillion: 100

Response: This yaml code 11.13 - Traces For Kubernetes System Components | For more information about the TracingConfiguration struct, see API server config API (v1).


Prompt:
Complete this yaml code:

apiVersion: kubelet.config.k8s.io/v1beta1
kind: KubeletConfiguration
tracing:

Response:
  # default value
  #endpoint: localhost:4317
  samplingRatePerMillion: 100

Context: 11.13 - Traces For Kubernetes System Components | If the samplingRatePerMillion is set to one million (1000000), then every span will be sent to the exporter.


Prompt:
Explain this yaml code:

apiVersion: kubelet.config.k8s.io/v1beta1
kind: KubeletConfiguration
tracing:
  # default value
  #endpoint: localhost:4317
  samplingRatePerMillion: 100

Response: This yaml code 11.13 - Traces For Kubernetes System Components | If the samplingRatePerMillion is set to one million (1000000), then every span will be sent to the exporter.


Prompt:
Explain this text code:

kube-apiserver \
--runtime-config=flowcontrol.apiserver.k8s.io/v1beta3=false \
 # …and other flags as usual

Response: This text code 11.15 - API Priority and Fairness | The command-line flag --enable-priority-and-fairness=false will disable the API Priority and Fairness feature.

Context: 11.15 - API Priority and Fairness | The command-line flag --enable-priority-and-fairness=false will disable the API Priority and Fairness feature.


Prompt:
Complete this yaml code:

apiVersion: flowcontrol.apiserver.k8s.io/v1
kind: FlowSchema
metadata:
  name: health-for-strangers
spec:
  matchingPrecedence: 1000
  priorityLevelConfiguration:
    name: exempt
  rules:
    - nonResourceRules:

Response:
      - nonResourceURLs:
          - "/healthz"
          - "/livez"
          - "/readyz"
        verbs:
          - "*"
      subjects:
        - kind: Group
          group:
            name: "system:unauthenticated"

Context: 11.15 - API Priority and Fairness | When you enable the API Priority and Fairness feature, the kube-apiserver exports additional metrics. Monitoring these can help you determine whether your configuration is inappropriately throttling i


Prompt:
Explain this yaml code:

apiVersion: flowcontrol.apiserver.k8s.io/v1
kind: FlowSchema
metadata:
  name: health-for-strangers
spec:
  matchingPrecedence: 1000
  priorityLevelConfiguration:
    name: exempt
  rules:
    - nonResourceRules:
      - nonResourceURLs:
          - "/healthz"
          - "/livez"
          - "/readyz"
        verbs:
          - "*"
      subjects:
        - kind: Group
          group:
            name: "system:unauthenticated"

Response: This yaml code 11.15 - API Priority and Fairness | When you enable the API Priority and Fairness feature, the kube-apiserver exports additional metrics. Monitoring these can help you determine whether your configuration is inappropriately throttling i


Prompt:
Complete this yaml code:

apiVersion: flowcontrol.apiserver.k8s.io/v1
kind: FlowSchema
metadata:
  name: list-events-default-service-account
spec:
  distinguisherMethod:
    type: ByUser
  matchingPrecedence: 8000
  priorityLevelConfiguration:
    name: catch-all
  rules:
    - resourceRules:

Response:
      - apiGroups:
          - '*'
        namespaces:
          - default
        resources:
          - events
        verbs:
          - list
      subjects:
        - kind: ServiceAccount
          serviceAccount:
            name: default
            namespace: default

Context: 11.15 - API Priority and Fairness | Add-ons extend the functionality of Kubernetes.


Prompt:
Explain this yaml code:

apiVersion: flowcontrol.apiserver.k8s.io/v1
kind: FlowSchema
metadata:
  name: list-events-default-service-account
spec:
  distinguisherMethod:
    type: ByUser
  matchingPrecedence: 8000
  priorityLevelConfiguration:
    name: catch-all
  rules:
    - resourceRules:
      - apiGroups:
          - '*'
        namespaces:
          - default
        resources:
          - events
        verbs:
          - list
      subjects:
        - kind: ServiceAccount
          serviceAccount:
            name: default
            namespace: default

Response: This yaml code 11.15 - API Priority and Fairness | Add-ons extend the functionality of Kubernetes.


Prompt:
Complete this yaml code:

---
apiVersion: v1
kind: Service
metadata:
  name: win-webserver
  labels:
    app: win-webserver
spec:
  ports:
    # the port that this service should serve on
    - port: 80
      targetPort: 80
  selector:
    app: win-webserver
  type: NodePort
---
apiVersion: apps/v1
kind: Deployment
metadata:
  labels:
    app: win-webserver

Response:
  name: win-webserver
spec:
  replicas: 2
  selector:
    matchLabels:
      app: win-webserver
  template:
    metadata:
      labels:
        app: win-webserver
      name: win-webserver
    spec:
     containers:
      - name: windowswebserver
        image: mcr.microsoft.com/windows/servercore:ltsc2019
        command:
        - powershell.exe
        - -command
        - "<#code used from https://gist.github.com/19WAS85/5424431#> ; $$listener = New-Object System.Net.HttpListener ; $$listener.Prefixes.Add('http://*:80/') ; $$listener.Start() ; $$callerCounts = @{} ; Write-Host('Listening at http://*:80/') ; while ($$listener.IsListening) { ;$$context = $$listener.GetContext() ;$$requestUrl = $$context.Request.Url ;$$clientIP = $$context.Request.RemoteEndPoint.Address ;$$response = $$context.Response ;Write-Host '' ;Write-Host('> {0}' -f $$requestUrl) ;  ;$$count = 1 ;$$k=$$callerCounts.Get_Item($$clientIP) ;if ($$k -ne $$null) { $$count += $$k } ;$$callerCounts.Set_Item($$clientIP, $$count) ;$$ip=(Get-NetAdapter | Get-NetIpAddress); $$header='<html><body><H1>Windows Container Web Server</H1>' ;$$callerCountsString='' ;$$callerCounts.Keys | % { $$callerCountsString+='<p>IP {0} callerCount {1} ' -f $$ip[1].IPAddress,$$callerCounts.Item($$_) } ;$$footer='</body></html>' ;$$content='{0}{1}{2}' -f $$header,$$callerCountsString,$$footer ;Write-Output $$content ;$$buffer = [System.Text.Encoding]::UTF8.GetBytes($$content) ;$$response.ContentLength64 = $$buffer.Length ;$$response.OutputStream.Write($$buffer, 0, $$buffer.Length) ;$$response.Close() ;$$responseStatus = $$response.StatusCode ;Write-Host('< {0}' -f $$responseStatus)  } ; "
     nodeSelector:
      kubernetes.io/os: windows

Context: 12.2 - Guide for Running Windows Containers in Kubernetes | Check that all nodes are healthy:


Prompt:
Explain this yaml code:

---
apiVersion: v1
kind: Service
metadata:
  name: win-webserver
  labels:
    app: win-webserver
spec:
  ports:
    # the port that this service should serve on
    - port: 80
      targetPort: 80
  selector:
    app: win-webserver
  type: NodePort
---
apiVersion: apps/v1
kind: Deployment
metadata:
  labels:
    app: win-webserver
  name: win-webserver
spec:
  replicas: 2
  selector:
    matchLabels:
      app: win-webserver
  template:
    metadata:
      labels:
        app: win-webserver
      name: win-webserver
    spec:
     containers:
      - name: windowswebserver
        image: mcr.microsoft.com/windows/servercore:ltsc2019
        command:
        - powershell.exe
        - -command
        - "<#code used from https://gist.github.com/19WAS85/5424431#> ; $$listener = New-Object System.Net.HttpListener ; $$listener.Prefixes.Add('http://*:80/') ; $$listener.Start() ; $$callerCounts = @{} ; Write-Host('Listening at http://*:80/') ; while ($$listener.IsListening) { ;$$context = $$listener.GetContext() ;$$requestUrl = $$context.Request.Url ;$$clientIP = $$context.Request.RemoteEndPoint.Address ;$$response = $$context.Response ;Write-Host '' ;Write-Host('> {0}' -f $$requestUrl) ;  ;$$count = 1 ;$$k=$$callerCounts.Get_Item($$clientIP) ;if ($$k -ne $$null) { $$count += $$k } ;$$callerCounts.Set_Item($$clientIP, $$count) ;$$ip=(Get-NetAdapter | Get-NetIpAddress); $$header='
Windows Container Web Server
' ;$$callerCountsString='' ;$$callerCounts.Keys | % { $$callerCountsString+='
IP {0} callerCount {1} ' -f $$ip[1].IPAddress,$$callerCounts.Item($$_) } ;$$footer='' ;$$content='{0}{1}{2}' -f $$header,$$callerCountsString,$$footer ;Write-Output $$content ;$$buffer = [System.Text.Encoding]::UTF8.GetBytes($$content) ;$$response.ContentLength64 = $$buffer.Length ;$$response.OutputStream.Write($$buffer, 0, $$buffer.Length) ;$$response.Close() ;$$responseStatus = $$response.StatusCode ;Write-Host('< {0}' -f $$responseStatus)  } ; "
     nodeSelector:
      kubernetes.io/os: windows

Response: This yaml code 12.2 - Guide for Running Windows Containers in Kubernetes | Check that all nodes are healthy:


Prompt:
Explain this bash code:

kubectl apply -f win-webserver.yaml
kubectl get pods -o wide -w

Response: This bash code 12.2 - Guide for Running Windows Containers in Kubernetes | When the service is deployed correctly both Pods are marked as Ready. To exit the watch command, press Ctrl+C.

Context: 12.2 - Guide for Running Windows Containers in Kubernetes | When the service is deployed correctly both Pods are marked as Ready. To exit the watch command, press Ctrl+C.


Prompt:
Complete this text code:

nodeSelector:
    kubernetes.io/os: windows
    node.kubernetes.io/windows-build: '10.0.17763'
tolerations:

Response:
    - key: "os"
      operator: "Equal"
      value: "windows"
      effect: "NoSchedule"

Context: 12.2 - Guide for Running Windows Containers in Kubernetes | The Windows Server version used by each pod must match that of the node. If you want to use multiple Windows Server versions in the same cluster, then you should set additional node labels and nodeSel


Prompt:
Explain this text code:

nodeSelector:
    kubernetes.io/os: windows
    node.kubernetes.io/windows-build: '10.0.17763'
tolerations:
    - key: "os"
      operator: "Equal"
      value: "windows"
      effect: "NoSchedule"

Response: This text code 12.2 - Guide for Running Windows Containers in Kubernetes | The Windows Server version used by each pod must match that of the node. If you want to use multiple Windows Server versions in the same cluster, then you should set additional node labels and nodeSel


Prompt:
Complete this yaml code:

---
apiVersion: node.k8s.io/v1
kind: RuntimeClass
metadata:
  name: windows-2019
handler: example-container-runtime-handler
scheduling:
  nodeSelector:

Response:
    kubernetes.io/os: 'windows'
    kubernetes.io/arch: 'amd64'
    node.kubernetes.io/windows-build: '10.0.17763'
  tolerations:
  - effect: NoSchedule
    key: os
    operator: Equal
    value: "windows"

Context: 12.2 - Guide for Running Windows Containers in Kubernetes | Run kubectl create -f runtimeClasses.yml using as a cluster administrator


Prompt:
Explain this yaml code:

---
apiVersion: node.k8s.io/v1
kind: RuntimeClass
metadata:
  name: windows-2019
handler: example-container-runtime-handler
scheduling:
  nodeSelector:
    kubernetes.io/os: 'windows'
    kubernetes.io/arch: 'amd64'
    node.kubernetes.io/windows-build: '10.0.17763'
  tolerations:
  - effect: NoSchedule
    key: os
    operator: Equal
    value: "windows"

Response: This yaml code 12.2 - Guide for Running Windows Containers in Kubernetes | Run kubectl create -f runtimeClasses.yml using as a cluster administrator


Prompt:
Complete this yaml code:

---
apiVersion: apps/v1
kind: Deployment
metadata:
  name: iis-2019
  labels:
    app: iis-2019
spec:
  replicas: 1
  template:
    metadata:
      name: iis-2019
      labels:
        app: iis-2019
    spec:
      runtimeClassName: windows-2019
      containers:
      - name: iis
        image: mcr.microsoft.com/windows/servercore/iis:windowsservercore-ltsc2019
        resources:
          limits:

Response:
            cpu: 1
            memory: 800Mi
          requests:
            cpu: .1
            memory: 300Mi
        ports:
          - containerPort: 80
 selector:
    matchLabels:
      app: iis-2019
---
apiVersion: v1
kind: Service
metadata:
  name: iis
spec:
  type: LoadBalancer
  ports:
  - protocol: TCP
    port: 80
  selector:
    app: iis-2019

Context: 12.2 - Guide for Running Windows Containers in Kubernetes | Kubernetes is highly configurable and extensible. As a result, there is rarely a need to fork or submit patches to the Kubernetes project code.


Prompt:
Explain this yaml code:

---
apiVersion: apps/v1
kind: Deployment
metadata:
  name: iis-2019
  labels:
    app: iis-2019
spec:
  replicas: 1
  template:
    metadata:
      name: iis-2019
      labels:
        app: iis-2019
    spec:
      runtimeClassName: windows-2019
      containers:
      - name: iis
        image: mcr.microsoft.com/windows/servercore/iis:windowsservercore-ltsc2019
        resources:
          limits:
            cpu: 1
            memory: 800Mi
          requests:
            cpu: .1
            memory: 300Mi
        ports:
          - containerPort: 80
 selector:
    matchLabels:
      app: iis-2019
---
apiVersion: v1
kind: Service
metadata:
  name: iis
spec:
  type: LoadBalancer
  ports:
  - protocol: TCP
    port: 80
  selector:
    app: iis-2019

Response: This yaml code 12.2 - Guide for Running Windows Containers in Kubernetes | Kubernetes is highly configurable and extensible. As a result, there is rarely a need to fork or submit patches to the Kubernetes project code.


Prompt:
Complete this json code:

{
  "name": "k8s-pod-network",
  "cniVersion": "0.4.0",
  "plugins": [
    {
      "type": "calico",
      "log_level": "info",
      "datastore_type": "kubernetes",
      "nodename": "127.0.0.1",
      "ipam": {
        "type": "host-local",
        "subnet": "usePodCidr"
      },

Response:
      "policy": {
        "type": "k8s"
      },
      "kubernetes": {
        "kubeconfig": "/etc/cni/net.d/calico-kubeconfig"
      }
    },
    {
      "type": "portmap",
      "capabilities": {"portMappings": true},
      "externalSetMarkChain": "KUBE-MARK-MASQ"
    }
  ]
}

Context: 13.1.1 - Network Plugins | Experimental Feature


Prompt:
Explain this json code:

{
  "name": "k8s-pod-network",
  "cniVersion": "0.4.0",
  "plugins": [
    {
      "type": "calico",
      "log_level": "info",
      "datastore_type": "kubernetes",
      "nodename": "127.0.0.1",
      "ipam": {
        "type": "host-local",
        "subnet": "usePodCidr"
      },
      "policy": {
        "type": "k8s"
      },
      "kubernetes": {
        "kubeconfig": "/etc/cni/net.d/calico-kubeconfig"
      }
    },
    {
      "type": "portmap",
      "capabilities": {"portMappings": true},
      "externalSetMarkChain": "KUBE-MARK-MASQ"
    }
  ]
}

Response: This json code 13.1.1 - Network Plugins | Experimental Feature


Prompt:
Complete this json code:

{
  "name": "k8s-pod-network",
  "cniVersion": "0.4.0",
  "plugins": [
    {
      "type": "calico",
      "log_level": "info",
      "datastore_type": "kubernetes",
      "nodename": "127.0.0.1",
      "ipam": {
        "type": "host-local",
        "subnet": "usePodCidr"
      },

Response:
      "policy": {
        "type": "k8s"
      },
      "kubernetes": {
        "kubeconfig": "/etc/cni/net.d/calico-kubeconfig"
      }
    },
    {
      "type": "bandwidth",
      "capabilities": {"bandwidth": true}
    }
  ]
}

Context: 13.1.1 - Network Plugins | Now you can add the kubernetes.io/ingress-bandwidth and kubernetes.io/egress-bandwidth annotations to your Pod. For example:


Prompt:
Explain this json code:

{
  "name": "k8s-pod-network",
  "cniVersion": "0.4.0",
  "plugins": [
    {
      "type": "calico",
      "log_level": "info",
      "datastore_type": "kubernetes",
      "nodename": "127.0.0.1",
      "ipam": {
        "type": "host-local",
        "subnet": "usePodCidr"
      },
      "policy": {
        "type": "k8s"
      },
      "kubernetes": {
        "kubeconfig": "/etc/cni/net.d/calico-kubeconfig"
      }
    },
    {
      "type": "bandwidth",
      "capabilities": {"bandwidth": true}
    }
  ]
}

Response: This json code 13.1.1 - Network Plugins | Now you can add the kubernetes.io/ingress-bandwidth and kubernetes.io/egress-bandwidth annotations to your Pod. For example:


Prompt:
Complete this yaml code:

apiVersion: v1
kind: Pod
metadata:

Response:
  annotations:
    kubernetes.io/ingress-bandwidth: 1M
    kubernetes.io/egress-bandwidth: 1M
...

Context: 13.1.1 - Network Plugins | Kubernetes provides a device plugin framework that you can use to advertise system hardware resources to the Kubelet.


Prompt:
Explain this yaml code:

apiVersion: v1
kind: Pod
metadata:
  annotations:
    kubernetes.io/ingress-bandwidth: 1M
    kubernetes.io/egress-bandwidth: 1M
...

Response: This yaml code 13.1.1 - Network Plugins | Kubernetes provides a device plugin framework that you can use to advertise system hardware resources to the Kubelet.


Prompt:
Explain this text code:

service Registration {
	rpc Register(RegisterRequest) returns (Empty) {}
}

Response: This text code 13.1.2 - Device Plugins | A device plugin can register itself with the kubelet through this gRPC service. During the registration, the device plugin needs to send:

Context: 13.1.2 - Device Plugins | A device plugin can register itself with the kubelet through this gRPC service. During the registration, the device plugin needs to send:


Prompt:
Complete this yaml code:

---
apiVersion: v1
kind: Pod
metadata:
  name: demo-pod
spec:
  containers:
    - name: demo-container-1
      image: registry.k8s.io/pause:3.8

Response:
      resources:
        limits:
          hardware-vendor.example/foo: 2
#
# This Pod needs 2 of the hardware-vendor.example/foo devices
# and can only schedule onto a Node that's able to satisfy
# that need.
#
# If the Node has more than 2 of those devices available, the
# remainder would be available for other Pods to use.

Context: 13.1.2 - Device Plugins | The general workflow of a device plugin includes the following steps:


Prompt:
Explain this yaml code:

---
apiVersion: v1
kind: Pod
metadata:
  name: demo-pod
spec:
  containers:
    - name: demo-container-1
      image: registry.k8s.io/pause:3.8
      resources:
        limits:
          hardware-vendor.example/foo: 2
#
# This Pod needs 2 of the hardware-vendor.example/foo devices
# and can only schedule onto a Node that's able to satisfy
# that need.
#
# If the Node has more than 2 of those devices available, the
# remainder would be available for other Pods to use.

Response: This yaml code 13.1.2 - Device Plugins | The general workflow of a device plugin includes the following steps:


Prompt:
Complete this text code:

service DevicePlugin {
      // GetDevicePluginOptions returns options to be communicated with Device Manager.
      rpc GetDevicePluginOptions(Empty) returns (DevicePluginOptions) {}

      // ListAndWatch returns a stream of List of Devices
      // Whenever a Device state change or a Device disappears, ListAndWatch
      // returns the new list
      rpc ListAndWatch(Empty) returns (stream ListAndWatchResponse) {}

      // Allocate is called during container creation so that the Device
      // Plugin can run device specific operations and instruct Kubelet
      // of the steps to make the Device available in the container
      rpc Allocate(AllocateRequest) returns (AllocateResponse) {}

Response:
      // GetPreferredAllocation returns a preferred set of devices to allocate
      // from a list of available ones. The resulting preferred allocation is not
      // guaranteed to be the allocation ultimately performed by the
      // devicemanager. It is only designed to help the devicemanager make a more
      // informed allocation decision when possible.
      rpc GetPreferredAllocation(PreferredAllocationRequest) returns (PreferredAllocationResponse) {}

      // PreStartContainer is called, if indicated by Device Plugin during registration phase,
      // before each container start. Device plugin can run device specific operations
      // such as resetting the device before making devices available to the container.
      rpc PreStartContainer(PreStartContainerRequest) returns (PreStartContainerResponse) {}
}

Context: 13.1.2 - Device Plugins | The plugin registers itself with the kubelet through the Unix socket at host path /var/lib/kubelet/device-plugins/kubelet.sock.


Prompt:
Explain this text code:

service DevicePlugin {
      // GetDevicePluginOptions returns options to be communicated with Device Manager.
      rpc GetDevicePluginOptions(Empty) returns (DevicePluginOptions) {}

      // ListAndWatch returns a stream of List of Devices
      // Whenever a Device state change or a Device disappears, ListAndWatch
      // returns the new list
      rpc ListAndWatch(Empty) returns (stream ListAndWatchResponse) {}

      // Allocate is called during container creation so that the Device
      // Plugin can run device specific operations and instruct Kubelet
      // of the steps to make the Device available in the container
      rpc Allocate(AllocateRequest) returns (AllocateResponse) {}

      // GetPreferredAllocation returns a preferred set of devices to allocate
      // from a list of available ones. The resulting preferred allocation is not
      // guaranteed to be the allocation ultimately performed by the
      // devicemanager. It is only designed to help the devicemanager make a more
      // informed allocation decision when possible.
      rpc GetPreferredAllocation(PreferredAllocationRequest) returns (PreferredAllocationResponse) {}

      // PreStartContainer is called, if indicated by Device Plugin during registration phase,
      // before each container start. Device plugin can run device specific operations
      // such as resetting the device before making devices available to the container.
      rpc PreStartContainer(PreStartContainerRequest) returns (PreStartContainerResponse) {}
}

Response: This text code 13.1.2 - Device Plugins | The plugin registers itself with the kubelet through the Unix socket at host path /var/lib/kubelet/device-plugins/kubelet.sock.


Prompt:
Complete this text code:

// PodResourcesLister is a service provided by the kubelet that provides information about the
// node resources consumed by pods and containers on the node
service PodResourcesLister {

Response:
    rpc List(ListPodResourcesRequest) returns (ListPodResourcesResponse) {}
    rpc GetAllocatableResources(AllocatableResourcesRequest) returns (AllocatableResourcesResponse) {}
    rpc Get(GetPodResourcesRequest) returns (GetPodResourcesResponse) {}
}

Context: 13.1.2 - Device Plugins | The List endpoint provides information on resources of running pods, with details such as the id of exclusively allocated CPUs, device id as it was reported by device plugins and id of the NUMA node w


Prompt:
Explain this text code:

// PodResourcesLister is a service provided by the kubelet that provides information about the
// node resources consumed by pods and containers on the node
service PodResourcesLister {
    rpc List(ListPodResourcesRequest) returns (ListPodResourcesResponse) {}
    rpc GetAllocatableResources(AllocatableResourcesRequest) returns (AllocatableResourcesResponse) {}
    rpc Get(GetPodResourcesRequest) returns (GetPodResourcesResponse) {}
}

Response: This text code 13.1.2 - Device Plugins | The List endpoint provides information on resources of running pods, with details such as the id of exclusively allocated CPUs, device id as it was reported by device plugins and id of the NUMA node w


Prompt:
Explain this text code:

--feature-gates=KubeletPodResourcesDynamicResources=false

Response: This text code 13.1.2 - Device Plugins | cpu_ids in the ContainerResources in the List endpoint correspond to exclusive CPUs allocated to a particular container. If the goal is to evaluate CPUs that belong to the shared pool, the List endpoi

Context: 13.1.2 - Device Plugins | cpu_ids in the ContainerResources in the List endpoint correspond to exclusive CPUs allocated to a particular container. If the goal is to evaluate CPUs that belong to the shared pool, the List endpoi


Prompt:
Complete this text code:

// ListPodResourcesResponse is the response returned by List function
message ListPodResourcesResponse {
    repeated PodResources pod_resources = 1;
}

// PodResources contains information about the node resources assigned to a pod
message PodResources {
    string name = 1;
    string namespace = 2;
    repeated ContainerResources containers = 3;
}

// ContainerResources contains information about the resources assigned to a container
message ContainerResources {
    string name = 1;
    repeated ContainerDevices devices = 2;
    repeated int64 cpu_ids = 3;
    repeated ContainerMemory memory = 4;
    repeated DynamicResource dynamic_resources = 5;
}

// ContainerMemory contains information about memory and hugepages assigned to a container
message ContainerMemory {
    string memory_type = 1;
    uint64 size = 2;
    TopologyInfo topology = 3;
}

// Topology describes hardware topology of the resource
message TopologyInfo {
        repeated NUMANode nodes = 1;
}

Response:
// NUMA representation of NUMA node
message NUMANode {
        int64 ID = 1;
}

// ContainerDevices contains information about the devices assigned to a container
message ContainerDevices {
    string resource_name = 1;
    repeated string device_ids = 2;
    TopologyInfo topology = 3;
}

// DynamicResource contains information about the devices assigned to a container by Dynamic Resource Allocation
message DynamicResource {
    string class_name = 1;
    string claim_name = 2;
    string claim_namespace = 3;
    repeated ClaimResource claim_resources = 4;
}

// ClaimResource contains per-plugin resource information
message ClaimResource {
    repeated CDIDevice cdi_devices = 1 [(gogoproto.customname) = "CDIDevices"];
}

// CDIDevice specifies a CDI device information
message CDIDevice {
    // Fully qualified CDI device name
    // for example: vendor.com/gpu=gpudevice1
    // see more details in the CDI specification:
    // https://github.com/container-orchestrated-devices/container-device-interface/blob/main/SPEC.md
    string name = 1;
}


Prompt:
Explain this text code:

// ListPodResourcesResponse is the response returned by List function
message ListPodResourcesResponse {
    repeated PodResources pod_resources = 1;
}

// PodResources contains information about the node resources assigned to a pod
message PodResources {
    string name = 1;
    string namespace = 2;
    repeated ContainerResources containers = 3;
}

// ContainerResources contains information about the resources assigned to a container
message ContainerResources {
    string name = 1;
    repeated ContainerDevices devices = 2;
    repeated int64 cpu_ids = 3;
    repeated ContainerMemory memory = 4;
    repeated DynamicResource dynamic_resources = 5;
}

// ContainerMemory contains information about memory and hugepages assigned to a container
message ContainerMemory {
    string memory_type = 1;
    uint64 size = 2;
    TopologyInfo topology = 3;
}

// Topology describes hardware topology of the resource
message TopologyInfo {
        repeated NUMANode nodes = 1;
}

// NUMA representation of NUMA node
message NUMANode {
        int64 ID = 1;
}

// ContainerDevices contains information about the devices assigned to a container
message ContainerDevices {
    string resource_name = 1;
    repeated string device_ids = 2;
    TopologyInfo topology = 3;
}

// DynamicResource contains information about the devices assigned to a container by Dynamic Resource Allocation
message DynamicResource {
    string class_name = 1;
    string claim_name = 2;
    string claim_namespace = 3;
    repeated ClaimResource claim_resources = 4;
}

// ClaimResource contains per-plugin resource information
message ClaimResource {
    repeated CDIDevice cdi_devices = 1 [(gogoproto.customname) = "CDIDevices"];
}

// CDIDevice specifies a CDI device information
message CDIDevice {
    // Fully qualified CDI device name
    // for example: vendor.com/gpu=gpudevice1
    // see more details in the CDI specification:
    // https://github.com/container-orchestrated-devices/container-device-interface/blob/main/SPEC.md
    string name = 1;
}

Response: This text code 13.1.2 - Device Plugins | cpu_ids in the ContainerResources in the List endpoint correspond to exclusive CPUs allocated to a particular container. If the goal is to evaluate CPUs that belong to the shared pool, the List endpoi


Prompt:
Complete this text code:

// AllocatableResourcesResponses contains information about all the devices known by the kubelet
message AllocatableResourcesResponse {
    repeated ContainerDevices devices = 1;

Response:
    repeated int64 cpu_ids = 2;
    repeated ContainerMemory memory = 3;
}

Context: 13.1.2 - Device Plugins | ContainerDevices do expose the topology information declaring to which NUMA cells the device is affine. The NUMA cells are identified using a opaque integer ID, which value is consistent to what devic


Prompt:
Explain this text code:

// AllocatableResourcesResponses contains information about all the devices known by the kubelet
message AllocatableResourcesResponse {
    repeated ContainerDevices devices = 1;
    repeated int64 cpu_ids = 2;
    repeated ContainerMemory memory = 3;
}

Response: This text code 13.1.2 - Device Plugins | ContainerDevices do expose the topology information declaring to which NUMA cells the device is affine. The NUMA cells are identified using a opaque integer ID, which value is consistent to what devic


Prompt:
Complete this text code:

// GetPodResourcesRequest contains information about the pod
message GetPodResourcesRequest {

Response:
    string pod_name = 1;
    string pod_namespace = 2;
}

Context: 13.1.2 - Device Plugins | To disable this feature, you must start your kubelet services with the following flag:


Prompt:
Explain this text code:

// GetPodResourcesRequest contains information about the pod
message GetPodResourcesRequest {
    string pod_name = 1;
    string pod_namespace = 2;
}

Response: This text code 13.1.2 - Device Plugins | To disable this feature, you must start your kubelet services with the following flag:


Prompt:
Explain this text code:

--feature-gates=KubeletPodResourcesDynamicResources=false

Response: This text code 13.1.2 - Device Plugins | The Topology Manager is a Kubelet component that allows resources to be co-ordinated in a Topology aligned manner. In order to do this, the Device Plugin API was extended to include a TopologyInfo str

Context: 13.1.2 - Device Plugins | The Topology Manager is a Kubelet component that allows resources to be co-ordinated in a Topology aligned manner. In order to do this, the Device Plugin API was extended to include a TopologyInfo str


Prompt:
Complete this text code:

message TopologyInfo {
    repeated NUMANode nodes = 1;
}

Response:
message NUMANode {
    int64 ID = 1;
}

Context: 13.1.2 - Device Plugins | Device Plugins that wish to leverage the Topology Manager can send back a populated TopologyInfo struct as part of the device registration, along with the device IDs and the health of the device. The


Prompt:
Explain this text code:

message TopologyInfo {
    repeated NUMANode nodes = 1;
}

message NUMANode {
    int64 ID = 1;
}

Response: This text code 13.1.2 - Device Plugins | Device Plugins that wish to leverage the Topology Manager can send back a populated TopologyInfo struct as part of the device registration, along with the device IDs and the health of the device. The


Prompt:
Explain this text code:

pluginapi.Device{ID: "25102017", Health: pluginapi.Healthy, Topology:&pluginapi.TopologyInfo{Nodes: []*pluginapi.NUMANode{&pluginapi.NUMANode{ID: 0,},}}}

Response: This text code 13.1.2 - Device Plugins | Here are some examples of device plugin implementations:

Context: 13.1.2 - Device Plugins | Here are some examples of device plugin implementations:


Prompt:
Complete this yaml code:

apiVersion: apiextensions.k8s.io/v1
kind: CustomResourceDefinition
metadata:
  name: shirts.stable.example.com
spec:
  group: stable.example.com
  scope: Namespaced
  names:
    plural: shirts
    singular: shirt
    kind: Shirt
  versions:
  - name: v1
    served: true
    storage: true
    schema:
      openAPIV3Schema:
        type: object

Response:
        properties:
          spec:
            type: object
            properties:
              color:
                type: string
              size:
                type: string
    selectableFields:
    - jsonPath: .spec.color
    - jsonPath: .spec.size
    additionalPrinterColumns:
    - jsonPath: .spec.color
      name: Color
      type: string
    - jsonPath: .spec.size
      name: Size
      type: string

Context: 13.2.1 - Custom Resources | Field selectors can then be used to get only resources with a color of blue:


Prompt:
Explain this yaml code:

apiVersion: apiextensions.k8s.io/v1
kind: CustomResourceDefinition
metadata:
  name: shirts.stable.example.com
spec:
  group: stable.example.com
  scope: Namespaced
  names:
    plural: shirts
    singular: shirt
    kind: Shirt
  versions:
  - name: v1
    served: true
    storage: true
    schema:
      openAPIV3Schema:
        type: object
        properties:
          spec:
            type: object
            properties:
              color:
                type: string
              size:
                type: string
    selectableFields:
    - jsonPath: .spec.color
    - jsonPath: .spec.size
    additionalPrinterColumns:
    - jsonPath: .spec.color
      name: Color
      type: string
    - jsonPath: .spec.size
      name: Size
      type: string

Response: This yaml code 13.2.1 - Custom Resources | Field selectors can then be used to get only resources with a color of blue:


Prompt:
Explain this bash code:

kubectl get shirts.stable.example.com --field-selector spec.color=blue

Response: This bash code 13.2.1 - Custom Resources | The output should be:

Context: 13.2.1 - Custom Resources | The output should be:


Prompt:
Explain this text code:

NAME       COLOR  SIZE
example1   blue   S
example2   blue   M

Response: This text code 13.2.1 - Custom Resources | The aggregation layer allows Kubernetes to be extended with additional APIs, beyond what is offered by the core Kubernetes APIs. The additional APIs can either be ready-made solutions such as a metric

Context: 13.2.1 - Custom Resources | The aggregation layer allows Kubernetes to be extended with additional APIs, beyond what is offered by the core Kubernetes APIs. The additional APIs can either be ready-made solutions such as a metric


Prompt:
Explain this bash code:

kubectl get SampleDB                   # find configured databases

kubectl edit SampleDB/example-database # manually change some settings

Response: This bash code 13.3 - Operator pattern | …and that's it! The operator will take care of applying the changes as well as keeping the existing service in good shape.

Context: 13.3 - Operator pattern | …and that's it! The operator will take care of applying the changes as well as keeping the existing service in good shape.


Prompt:
Complete this yaml code:

apiVersion: apps/v1
kind: Deployment
metadata:
  name: nginx-deployment
spec:
  selector:
    matchLabels:
      app: nginx
  replicas: 2 # tells deployment to run 2 pods matching the template

Response:
  template:
    metadata:
      labels:
        app: nginx
    spec:
      containers:
      - name: nginx
        image: nginx:1.14.2
        ports:
        - containerPort: 80

Context: 1.2 - Objects In Kubernetes | One way to create a Deployment using a manifest file like the one above is to use the kubectl apply command in the kubectl command-line interface, passing the .yaml file as an argument. Here's an exam


Prompt:
Explain this yaml code:

apiVersion: apps/v1
kind: Deployment
metadata:
  name: nginx-deployment
spec:
  selector:
    matchLabels:
      app: nginx
  replicas: 2 # tells deployment to run 2 pods matching the template
  template:
    metadata:
      labels:
        app: nginx
    spec:
      containers:
      - name: nginx
        image: nginx:1.14.2
        ports:
        - containerPort: 80

Response: This yaml code 1.2 - Objects In Kubernetes | One way to create a Deployment using a manifest file like the one above is to use the kubectl apply command in the kubectl command-line interface, passing the .yaml file as an argument. Here's an exam


Prompt:
Explain this shell code:

kubectl apply -f https://k8s.io/examples/application/deployment.yaml

Response: This shell code 1.2 - Objects In Kubernetes | The output is similar to this:

Context: 1.2 - Objects In Kubernetes | The output is similar to this:


Prompt:
Explain this sh code:

kubectl diff -R -f configs/
kubectl apply -R -f configs/

Response: This sh code 1.2.1 - Kubernetes Object Management | Advantages compared to imperative object configuration:

Context: 1.2.1 - Kubernetes Object Management | Advantages compared to imperative object configuration:


Prompt:
Complete this yaml code:

apiVersion: v1
kind: Pod
metadata:
  name: nginx-demo
spec:

Response:
  containers:
  - name: nginx
    image: nginx:1.14.2
    ports:
    - containerPort: 80

Context: 1.2.2 - Object Names and IDs | A Kubernetes systems-generated string to uniquely identify objects.


Prompt:
Explain this yaml code:

apiVersion: v1
kind: Pod
metadata:
  name: nginx-demo
spec:
  containers:
  - name: nginx
    image: nginx:1.14.2
    ports:
    - containerPort: 80

Response: This yaml code 1.2.2 - Object Names and IDs | A Kubernetes systems-generated string to uniquely identify objects.


Prompt:
Complete this json code:

"metadata": {
  "labels": {
    "key1" : "value1",

Response:
    "key2" : "value2"
  }
}

Context: 1.2.3 - Labels and Selectors | Labels allow for efficient queries and watches and are ideal for use in UIs and CLIs. Non-identifying information should be recorded using annotations.


Prompt:
Explain this json code:

"metadata": {
  "labels": {
    "key1" : "value1",
    "key2" : "value2"
  }
}

Response: This json code 1.2.3 - Labels and Selectors | Labels allow for efficient queries and watches and are ideal for use in UIs and CLIs. Non-identifying information should be recorded using annotations.


Prompt:
Complete this yaml code:

apiVersion: v1
kind: Pod
metadata:
  name: label-demo
  labels:
    environment: production

Response:
    app: nginx
spec:
  containers:
  - name: nginx
    image: nginx:1.14.2
    ports:
    - containerPort: 80

Context: 1.2.3 - Labels and Selectors | Unlike names and UIDs, labels do not provide uniqueness. In general, we expect many objects to carry the same label(s).


Prompt:
Explain this yaml code:

apiVersion: v1
kind: Pod
metadata:
  name: label-demo
  labels:
    environment: production
    app: nginx
spec:
  containers:
  - name: nginx
    image: nginx:1.14.2
    ports:
    - containerPort: 80

Response: This yaml code 1.2.3 - Labels and Selectors | Unlike names and UIDs, labels do not provide uniqueness. In general, we expect many objects to carry the same label(s).


Prompt:
Complete this yaml code:

apiVersion: v1
kind: Pod
metadata:
  name: cuda-test
spec:
  containers:

Response:
    - name: cuda-test
      image: "registry.k8s.io/cuda-vector-add:v0.1"
      resources:
        limits:
          nvidia.com/gpu: 1
  nodeSelector:
    accelerator: nvidia-tesla-p100

Context: 1.2.3 - Labels and Selectors | Set-based label requirements allow filtering keys according to a set of values. Three kinds of operators are supported: in,notin and exists (only the key identifier). For example:


Prompt:
Explain this yaml code:

apiVersion: v1
kind: Pod
metadata:
  name: cuda-test
spec:
  containers:
    - name: cuda-test
      image: "registry.k8s.io/cuda-vector-add:v0.1"
      resources:
        limits:
          nvidia.com/gpu: 1
  nodeSelector:
    accelerator: nvidia-tesla-p100

Response: This yaml code 1.2.3 - Labels and Selectors | Set-based label requirements allow filtering keys according to a set of values. Three kinds of operators are supported: in,notin and exists (only the key identifier). For example:


Prompt:
Complete this text code:

environment in (production, qa)
tier notin (frontend, backend)

Response:
partition
!partition

Context: 1.2.3 - Labels and Selectors | Similarly the comma separator acts as an AND operator. So filtering resources with a partition key (no matter the value) and with environment different than qa can be achieved using partition,environm


Prompt:
Explain this text code:

environment in (production, qa)
tier notin (frontend, backend)
partition
!partition

Response: This text code 1.2.3 - Labels and Selectors | Similarly the comma separator acts as an AND operator. So filtering resources with a partition key (no matter the value) and with environment different than qa can be achieved using partition,environm


Prompt:
Explain this text code:

partition in (customerA, customerB),environment!=qa

Response: This text code 1.2.3 - Labels and Selectors | For list and watch operations, you can specify label selectors to filter the sets of objects returned; you specify the filter using a query parameter. (To learn in detail about watches in Kubernetes,

Context: 1.2.3 - Labels and Selectors | For list and watch operations, you can specify label selectors to filter the sets of objects returned; you specify the filter using a query parameter. (To learn in detail about watches in Kubernetes,


Prompt:
Explain this text code:

?labelSelector=environment%3Dproduction,tier%3Dfrontend

Response: This text code 1.2.3 - Labels and Selectors | Both label selector styles can be used to list or watch resources via a REST client. For example, targeting apiserver with kubectl and using equality-based one may write:

Context: 1.2.3 - Labels and Selectors | Both label selector styles can be used to list or watch resources via a REST client. For example, targeting apiserver with kubectl and using equality-based one may write:


Prompt:
Explain this text code:

?labelSelector=environment+in+%28production%2Cqa%29%2Ctier+in+%28frontend%29

Response: This text code 1.2.3 - Labels and Selectors | Both label selector styles can be used to list or watch resources via a REST client. For example, targeting apiserver with kubectl and using equality-based one may write:


Prompt:
Explain this shell code:

kubectl get pods -l environment=production,tier=frontend

Response: This shell code 1.2.3 - Labels and Selectors | or using set-based requirements:

Context: 1.2.3 - Labels and Selectors | or using set-based requirements:


Prompt:
Explain this shell code:

kubectl get pods -l 'environment in (production),tier in (frontend)'

Response: This shell code 1.2.3 - Labels and Selectors | As already mentioned set-based requirements are more expressive. For instance, they can implement the OR operator on values:

Context: 1.2.3 - Labels and Selectors | As already mentioned set-based requirements are more expressive. For instance, they can implement the OR operator on values:


Prompt:
Explain this shell code:

kubectl get pods -l 'environment in (production, qa)'

Response: This shell code 1.2.3 - Labels and Selectors | or restricting negative matching via notin operator:

Context: 1.2.3 - Labels and Selectors | or restricting negative matching via notin operator:


Prompt:
Explain this shell code:

kubectl get pods -l 'environment,environment notin (frontend)'

Response: This shell code 1.2.3 - Labels and Selectors | Some Kubernetes objects, such as services and replicationcontrollers, also use label selectors to specify sets of other resources, such as pods.

Context: 1.2.3 - Labels and Selectors | Some Kubernetes objects, such as services and replicationcontrollers, also use label selectors to specify sets of other resources, such as pods.


Prompt:
Complete this yaml code:

selector:
  matchLabels:
    component: redis

Response:
  matchExpressions:
    - { key: tier, operator: In, values: [cache] }
    - { key: environment, operator: NotIn, values: [dev] }

Context: 1.2.3 - Labels and Selectors | matchLabels is a map of {key,value} pairs. A single {key,value} in the matchLabels map is equivalent to an element of matchExpressions, whose key field is "key", the operator is "In", and the values a


Prompt:
Explain this yaml code:

selector:
  matchLabels:
    component: redis
  matchExpressions:
    - { key: tier, operator: In, values: [cache] }
    - { key: environment, operator: NotIn, values: [dev] }

Response: This yaml code 1.2.3 - Labels and Selectors | matchLabels is a map of {key,value} pairs. A single {key,value} in the matchLabels map is equivalent to an element of matchExpressions, whose key field is "key", the operator is "In", and the values a


Prompt:
Complete this yaml code:

labels:
  app: guestbook

Response:
  tier: backend
  role: master

Context: 1.2.3 - Labels and Selectors | and


Prompt:
Explain this yaml code:

labels:
  app: guestbook
  tier: backend
  role: master

Response: This yaml code 1.2.3 - Labels and Selectors | and

Context: 1.2.3 - Labels and Selectors | and


Prompt:
Complete this yaml code:

labels:
  app: guestbook

Response:
  tier: backend
  role: replica

Context: 1.2.3 - Labels and Selectors | The labels allow for slicing and dicing the resources along any dimension specified by a label:


Prompt:
Explain this yaml code:

labels:
  app: guestbook
  tier: backend
  role: replica

Response: This yaml code 1.2.3 - Labels and Selectors | The labels allow for slicing and dicing the resources along any dimension specified by a label:


Prompt:
Explain this shell code:

kubectl apply -f examples/guestbook/all-in-one/guestbook-all-in-one.yaml
kubectl get pods -Lapp -Ltier -Lrole

Response: This shell code 1.2.3 - Labels and Selectors | Sometimes you may want to relabel existing pods and other resources before creating new resources. This can be done with kubectl label. For example, if you want to label all your NGINX Pods as fronten

Context: 1.2.3 - Labels and Selectors | Sometimes you may want to relabel existing pods and other resources before creating new resources. This can be done with kubectl label. For example, if you want to label all your NGINX Pods as fronten


Prompt:
Complete this none code:

NAME                           READY  STATUS    RESTARTS   AGE   APP         TIER       ROLE
guestbook-fe-4nlpb             1/1    Running   0          1m    guestbook   frontend   <none>
guestbook-fe-ght6d             1/1    Running   0          1m    guestbook   frontend   <none>
guestbook-fe-jpy62             1/1    Running   0          1m    guestbook   frontend   <none>

Response:
guestbook-redis-master-5pg3b   1/1    Running   0          1m    guestbook   backend    master
guestbook-redis-replica-2q2yf  1/1    Running   0          1m    guestbook   backend    replica
guestbook-redis-replica-qgazl  1/1    Running   0          1m    guestbook   backend    replica
my-nginx-divi2                 1/1    Running   0          29m   nginx       <none>     <none>
my-nginx-o0ef1                 1/1    Running   0          29m   nginx       <none>     <none>


Prompt:
Explain this none code:

NAME                           READY  STATUS    RESTARTS   AGE   APP         TIER       ROLE
guestbook-fe-4nlpb             1/1    Running   0          1m    guestbook   frontend   <none>
guestbook-fe-ght6d             1/1    Running   0          1m    guestbook   frontend   <none>
guestbook-fe-jpy62             1/1    Running   0          1m    guestbook   frontend   <none>
guestbook-redis-master-5pg3b   1/1    Running   0          1m    guestbook   backend    master
guestbook-redis-replica-2q2yf  1/1    Running   0          1m    guestbook   backend    replica
guestbook-redis-replica-qgazl  1/1    Running   0          1m    guestbook   backend    replica
my-nginx-divi2                 1/1    Running   0          29m   nginx       <none>     <none>
my-nginx-o0ef1                 1/1    Running   0          29m   nginx       <none>     <none>

Response: This none code 1.2.3 - Labels and Selectors | Sometimes you may want to relabel existing pods and other resources before creating new resources. This can be done with kubectl label. For example, if you want to label all your NGINX Pods as fronten


Prompt:
Explain this none code:

NAME                           READY  STATUS   RESTARTS  AGE
guestbook-redis-replica-2q2yf  1/1    Running  0         3m
guestbook-redis-replica-qgazl  1/1    Running  0         3m

Response: This none code 1.2.3 - Labels and Selectors | Sometimes you may want to relabel existing pods and other resources before creating new resources. This can be done with kubectl label. For example, if you want to label all your NGINX Pods as fronten


Prompt:
Explain this none code:

pod/my-nginx-2035384211-j5fhi labeled
pod/my-nginx-2035384211-u2c7e labeled
pod/my-nginx-2035384211-u3t6x labeled

Response: This none code 1.2.3 - Labels and Selectors | This first filters all pods with the label "app=nginx", and then labels them with the "tier=fe". To see the pods you labeled, run:

Context: 1.2.3 - Labels and Selectors | This first filters all pods with the label "app=nginx", and then labels them with the "tier=fe". To see the pods you labeled, run: