Prompt:
Complete this text code:

redis:6379> rpush job2 "apple"
(integer) 1
redis:6379> rpush job2 "banana"
(integer) 2
redis:6379> rpush job2 "cherry"
(integer) 3
redis:6379> rpush job2 "date"
(integer) 4
redis:6379> rpush job2 "fig"
(integer) 5
redis:6379> rpush job2 "grape"
(integer) 6
redis:6379> rpush job2 "lemon"
(integer) 7

Response:
redis:6379> rpush job2 "melon"
(integer) 8
redis:6379> rpush job2 "orange"
(integer) 9
redis:6379> lrange job2 0 -1
1) "apple"
2) "banana"
3) "cherry"
4) "date"
5) "fig"
6) "grape"
7) "lemon"
8) "melon"
9) "orange"

Context: 3 - Fine Parallel Processing Using a Work Queue | So, the list with key job2 will be the work queue.


Prompt:
Explain this text code:

redis:6379> rpush job2 "apple"
(integer) 1
redis:6379> rpush job2 "banana"
(integer) 2
redis:6379> rpush job2 "cherry"
(integer) 3
redis:6379> rpush job2 "date"
(integer) 4
redis:6379> rpush job2 "fig"
(integer) 5
redis:6379> rpush job2 "grape"
(integer) 6
redis:6379> rpush job2 "lemon"
(integer) 7
redis:6379> rpush job2 "melon"
(integer) 8
redis:6379> rpush job2 "orange"
(integer) 9
redis:6379> lrange job2 0 -1
1) "apple"
2) "banana"
3) "cherry"
4) "date"
5) "fig"
6) "grape"
7) "lemon"
8) "melon"
9) "orange"

Response: This text code 3 - Fine Parallel Processing Using a Work Queue | So, the list with key job2 will be the work queue.


Prompt:
Complete this python code:

#!/usr/bin/env python

import time
import rediswq

host="redis"
# Uncomment next two lines if you do not have Kube-DNS working.
# import os
# host = os.getenv("REDIS_SERVICE_HOST")

q = rediswq.RedisWQ(name="job2", host=host)

Response:
print("Worker with sessionID: " +  q.sessionID())
print("Initial queue state: empty=" + str(q.empty()))
while not q.empty():
  item = q.lease(lease_secs=10, block=True, timeout=2)
  if item is not None:
    itemstr = item.decode("utf-8")
    print("Working on " + itemstr)
    time.sleep(10) # Put your actual work here instead of sleep.
    q.complete(item)
  else:
    print("Waiting for work")
print("Queue empty, exiting")

Context: 3 - Fine Parallel Processing Using a Work Queue | You could also download worker.py, rediswq.py, and Dockerfile files, then build the container image. Here's an example using Docker to do the image build:


Prompt:
Explain this python code:

#!/usr/bin/env python

import time
import rediswq

host="redis"
# Uncomment next two lines if you do not have Kube-DNS working.
# import os
# host = os.getenv("REDIS_SERVICE_HOST")

q = rediswq.RedisWQ(name="job2", host=host)
print("Worker with sessionID: " +  q.sessionID())
print("Initial queue state: empty=" + str(q.empty()))
while not q.empty():
  item = q.lease(lease_secs=10, block=True, timeout=2)
  if item is not None:
    itemstr = item.decode("utf-8")
    print("Working on " + itemstr)
    time.sleep(10) # Put your actual work here instead of sleep.
    q.complete(item)
  else:
    print("Waiting for work")
print("Queue empty, exiting")

Response: This python code 3 - Fine Parallel Processing Using a Work Queue | You could also download worker.py, rediswq.py, and Dockerfile files, then build the container image. Here's an example using Docker to do the image build:


Prompt:
Explain this bash code:

docker tag job-wq-2 <username>/job-wq-2
docker push <username>/job-wq-2

Response: This bash code 3 - Fine Parallel Processing Using a Work Queue | You need to push to a public repository or configure your cluster to be able to access your private repository.

Context: 3 - Fine Parallel Processing Using a Work Queue | You need to push to a public repository or configure your cluster to be able to access your private repository.


Prompt:
Complete this yaml code:

apiVersion: batch/v1
kind: Job
metadata:
  name: job-wq-2
spec:
  parallelism: 2
  template:

Response:
    metadata:
      name: job-wq-2
    spec:
      containers:
      - name: c
        image: gcr.io/myproject/job-wq-2
      restartPolicy: OnFailure

Context: 3 - Fine Parallel Processing Using a Work Queue | In this example, each pod works on several items from the queue and then exits when there are no more items. Since the workers themselves detect when the workqueue is empty, and the Job controller doe


Prompt:
Explain this yaml code:

apiVersion: batch/v1
kind: Job
metadata:
  name: job-wq-2
spec:
  parallelism: 2
  template:
    metadata:
      name: job-wq-2
    spec:
      containers:
      - name: c
        image: gcr.io/myproject/job-wq-2
      restartPolicy: OnFailure

Response: This yaml code 3 - Fine Parallel Processing Using a Work Queue | In this example, each pod works on several items from the queue and then exits when there are no more items. Since the workers themselves detect when the workqueue is empty, and the Job controller doe


Prompt:
Explain this text code:

# this assumes you downloaded and then edited the manifest already
kubectl apply -f ./job.yaml

Response: This text code 3 - Fine Parallel Processing Using a Work Queue | Now wait a bit, then check on the Job:

Context: 3 - Fine Parallel Processing Using a Work Queue | Now wait a bit, then check on the Job:


Prompt:
Complete this text code:

Name:             job-wq-2
Namespace:        default
Selector:         controller-uid=b1c7e4e3-92e1-11e7-b85e-fa163ee3c11f
Labels:           controller-uid=b1c7e4e3-92e1-11e7-b85e-fa163ee3c11f
                  job-name=job-wq-2
Annotations:      <none>
Parallelism:      2
Completions:      <unset>
Start Time:       Mon, 11 Jan 2022 17:07:59 +0000
Pods Statuses:    1 Running / 0 Succeeded / 0 Failed
Pod Template:
  Labels:       controller-uid=b1c7e4e3-92e1-11e7-b85e-fa163ee3c11f

Response:
                job-name=job-wq-2
  Containers:
   c:
    Image:              container-registry.example/exampleproject/job-wq-2
    Port:
    Environment:        <none>
    Mounts:             <none>
  Volumes:              <none>
Events:
  FirstSeen    LastSeen    Count    From            SubobjectPath    Type        Reason            Message
  ---------    --------    -----    ----            -------------    --------    ------            -------
  33s          33s         1        {job-controller }                Normal      SuccessfulCreate  Created pod: job-wq-2-lglf8

Context: 3 - Fine Parallel Processing Using a Work Queue | You can wait for the Job to succeed, with a timeout:


Prompt:
Explain this text code:

Name:             job-wq-2
Namespace:        default
Selector:         controller-uid=b1c7e4e3-92e1-11e7-b85e-fa163ee3c11f
Labels:           controller-uid=b1c7e4e3-92e1-11e7-b85e-fa163ee3c11f
                  job-name=job-wq-2
Annotations:      <none>
Parallelism:      2
Completions:      <unset>
Start Time:       Mon, 11 Jan 2022 17:07:59 +0000
Pods Statuses:    1 Running / 0 Succeeded / 0 Failed
Pod Template:
  Labels:       controller-uid=b1c7e4e3-92e1-11e7-b85e-fa163ee3c11f
                job-name=job-wq-2
  Containers:
   c:
    Image:              container-registry.example/exampleproject/job-wq-2
    Port:
    Environment:        <none>
    Mounts:             <none>
  Volumes:              <none>
Events:
  FirstSeen    LastSeen    Count    From            SubobjectPath    Type        Reason            Message
  ---------    --------    -----    ----            -------------    --------    ------            -------
  33s          33s         1        {job-controller }                Normal      SuccessfulCreate  Created pod: job-wq-2-lglf8

Response: This text code 3 - Fine Parallel Processing Using a Work Queue | You can wait for the Job to succeed, with a timeout:


Prompt:
Explain this text code:

# The check for condition name is case insensitive
kubectl wait --for=condition=complete --timeout=300s job/job-wq-2

Response: This text code 3 - Fine Parallel Processing Using a Work Queue | As you can see, one of the pods for this Job worked on several work units.

Context: 3 - Fine Parallel Processing Using a Work Queue | As you can see, one of the pods for this Job worked on several work units.


Prompt:
Complete this text code:

Worker with sessionID: bbd72d0a-9e5c-4dd6-abf6-416cc267991f
Initial queue state: empty=False

Response:
Working on banana
Working on date
Working on lemon


Prompt:
Explain this text code:

Worker with sessionID: bbd72d0a-9e5c-4dd6-abf6-416cc267991f
Initial queue state: empty=False
Working on banana
Working on date
Working on lemon

Response: This text code 3 - Fine Parallel Processing Using a Work Queue | As you can see, one of the pods for this Job worked on several work units.


Prompt:
Complete this yaml code:

apiVersion: batch/v1
kind: Job
metadata:
  name: 'indexed-job'
spec:
  completions: 5
  parallelism: 3
  completionMode: Indexed
  template:
    spec:
      restartPolicy: Never
      initContainers:
      - name: 'input'
        image: 'docker.io/library/bash'
        command:
        - "bash"
        - "-c"

Response:
        - |
          items=(foo bar baz qux xyz)
          echo ${items[$JOB_COMPLETION_INDEX]} > /input/data.txt
        volumeMounts:
        - mountPath: /input
          name: input
      containers:
      - name: 'worker'
        image: 'docker.io/library/busybox'
        command:
        - "rev"
        - "/input/data.txt"
        volumeMounts:
        - mountPath: /input
          name: input
      volumes:
      - name: input
        emptyDir: {}

Context: 4 - Indexed Job for Parallel Processing with Static Work Assignment | In the example above, you use the builtin JOB_COMPLETION_INDEX environment variable set by the Job controller for all containers. An init container maps the index to a static value and writes it to a


Prompt:
Explain this yaml code:

apiVersion: batch/v1
kind: Job
metadata:
  name: 'indexed-job'
spec:
  completions: 5
  parallelism: 3
  completionMode: Indexed
  template:
    spec:
      restartPolicy: Never
      initContainers:
      - name: 'input'
        image: 'docker.io/library/bash'
        command:
        - "bash"
        - "-c"
        - |
          items=(foo bar baz qux xyz)
          echo ${items[$JOB_COMPLETION_INDEX]} > /input/data.txt
        volumeMounts:
        - mountPath: /input
          name: input
      containers:
      - name: 'worker'
        image: 'docker.io/library/busybox'
        command:
        - "rev"
        - "/input/data.txt"
        volumeMounts:
        - mountPath: /input
          name: input
      volumes:
      - name: input
        emptyDir: {}

Response: This yaml code 4 - Indexed Job for Parallel Processing with Static Work Assignment | In the example above, you use the builtin JOB_COMPLETION_INDEX environment variable set by the Job controller for all containers. An init container maps the index to a static value and writes it to a


Prompt:
Complete this yaml code:

apiVersion: batch/v1
kind: Job
metadata:
  name: 'indexed-job'
spec:
  completions: 5
  parallelism: 3
  completionMode: Indexed
  template:
    spec:
      restartPolicy: Never
      containers:
      - name: 'worker'

Response:
        image: 'docker.io/library/busybox'
        command:
        - "rev"
        - "/input/data.txt"
        volumeMounts:
        - mountPath: /input
          name: input
      volumes:
      - name: input
        downwardAPI:
          items:
          - path: "data.txt"
            fieldRef:
              fieldPath: metadata.annotations['batch.kubernetes.io/job-completion-index']

Context: 4 - Indexed Job for Parallel Processing with Static Work Assignment | Now run the Job:


Prompt:
Explain this yaml code:

apiVersion: batch/v1
kind: Job
metadata:
  name: 'indexed-job'
spec:
  completions: 5
  parallelism: 3
  completionMode: Indexed
  template:
    spec:
      restartPolicy: Never
      containers:
      - name: 'worker'
        image: 'docker.io/library/busybox'
        command:
        - "rev"
        - "/input/data.txt"
        volumeMounts:
        - mountPath: /input
          name: input
      volumes:
      - name: input
        downwardAPI:
          items:
          - path: "data.txt"
            fieldRef:
              fieldPath: metadata.annotations['batch.kubernetes.io/job-completion-index']

Response: This yaml code 4 - Indexed Job for Parallel Processing with Static Work Assignment | Now run the Job:


Prompt:
Explain this text code:

# This uses the first approach (relying on $JOB_COMPLETION_INDEX)
kubectl apply -f https://kubernetes.io/examples/application/job/indexed-job.yaml

Response: This text code 4 - Indexed Job for Parallel Processing with Static Work Assignment | When you create this Job, the control plane creates a series of Pods, one for each index you specified. The value of .spec.parallelism determines how many can run at once whereas .spec.completions det

Context: 4 - Indexed Job for Parallel Processing with Static Work Assignment | When you create this Job, the control plane creates a series of Pods, one for each index you specified. The value of .spec.parallelism determines how many can run at once whereas .spec.completions det


Prompt:
Explain this text code:

# The check for condition name is case insensitive
kubectl wait --for=condition=complete --timeout=300s job/indexed-job

Response: This text code 4 - Indexed Job for Parallel Processing with Static Work Assignment | Now, describe the Job and check that it was successful.

Context: 4 - Indexed Job for Parallel Processing with Static Work Assignment | Now, describe the Job and check that it was successful.


Prompt:
Complete this text code:

Name:              indexed-job
Namespace:         default
Selector:          controller-uid=bf865e04-0b67-483b-9a90-74cfc4c3e756
Labels:            controller-uid=bf865e04-0b67-483b-9a90-74cfc4c3e756
                   job-name=indexed-job
Annotations:       <none>
Parallelism:       3
Completions:       5
Start Time:        Thu, 11 Mar 2021 15:47:34 +0000
Pods Statuses:     2 Running / 3 Succeeded / 0 Failed
Completed Indexes: 0-2
Pod Template:
  Labels:  controller-uid=bf865e04-0b67-483b-9a90-74cfc4c3e756
           job-name=indexed-job
  Init Containers:
   input:
    Image:      docker.io/library/bash
    Port:       <none>
    Host Port:  <none>
    Command:
      bash
      -c
      items=(foo bar baz qux xyz)
      echo ${items[$JOB_COMPLETION_INDEX]} > /input/data.txt

    Environment:  <none>

Response:
    Mounts:
      /input from input (rw)
  Containers:
   worker:
    Image:      docker.io/library/busybox
    Port:       <none>
    Host Port:  <none>
    Command:
      rev
      /input/data.txt
    Environment:  <none>
    Mounts:
      /input from input (rw)
  Volumes:
   input:
    Type:       EmptyDir (a temporary directory that shares a pod's lifetime)
    Medium:
    SizeLimit:  <unset>
Events:
  Type    Reason            Age   From            Message
  ----    ------            ----  ----            -------
  Normal  SuccessfulCreate  4s    job-controller  Created pod: indexed-job-njkjj
  Normal  SuccessfulCreate  4s    job-controller  Created pod: indexed-job-9kd4h
  Normal  SuccessfulCreate  4s    job-controller  Created pod: indexed-job-qjwsz
  Normal  SuccessfulCreate  1s    job-controller  Created pod: indexed-job-fdhq5
  Normal  SuccessfulCreate  1s    job-controller  Created pod: indexed-job-ncslj

Context: 4 - Indexed Job for Parallel Processing with Static Work Assignment | In this example, you run the Job with custom values for each index. You can inspect the output of one of the pods:


Prompt:
Explain this text code:

Name:              indexed-job
Namespace:         default
Selector:          controller-uid=bf865e04-0b67-483b-9a90-74cfc4c3e756
Labels:            controller-uid=bf865e04-0b67-483b-9a90-74cfc4c3e756
                   job-name=indexed-job
Annotations:       <none>
Parallelism:       3
Completions:       5
Start Time:        Thu, 11 Mar 2021 15:47:34 +0000
Pods Statuses:     2 Running / 3 Succeeded / 0 Failed
Completed Indexes: 0-2
Pod Template:
  Labels:  controller-uid=bf865e04-0b67-483b-9a90-74cfc4c3e756
           job-name=indexed-job
  Init Containers:
   input:
    Image:      docker.io/library/bash
    Port:       <none>
    Host Port:  <none>
    Command:
      bash
      -c
      items=(foo bar baz qux xyz)
      echo ${items[$JOB_COMPLETION_INDEX]} > /input/data.txt

    Environment:  <none>
    Mounts:
      /input from input (rw)
  Containers:
   worker:
    Image:      docker.io/library/busybox
    Port:       <none>
    Host Port:  <none>
    Command:
      rev
      /input/data.txt
    Environment:  <none>
    Mounts:
      /input from input (rw)
  Volumes:
   input:
    Type:       EmptyDir (a temporary directory that shares a pod's lifetime)
    Medium:
    SizeLimit:  <unset>
Events:
  Type    Reason            Age   From            Message
  ----    ------            ----  ----            -------
  Normal  SuccessfulCreate  4s    job-controller  Created pod: indexed-job-njkjj
  Normal  SuccessfulCreate  4s    job-controller  Created pod: indexed-job-9kd4h
  Normal  SuccessfulCreate  4s    job-controller  Created pod: indexed-job-qjwsz
  Normal  SuccessfulCreate  1s    job-controller  Created pod: indexed-job-fdhq5
  Normal  SuccessfulCreate  1s    job-controller  Created pod: indexed-job-ncslj

Response: This text code 4 - Indexed Job for Parallel Processing with Static Work Assignment | In this example, you run the Job with custom values for each index. You can inspect the output of one of the pods:


Prompt:
Explain this bash code:

kubectl logs indexed-job-fdhq5 # Change this to match the name of a Pod from that Job

Response: This bash code 4 - Indexed Job for Parallel Processing with Static Work Assignment | The output is similar to:

Context: 4 - Indexed Job for Parallel Processing with Static Work Assignment | The output is similar to:


Prompt:
Complete this yaml code:

apiVersion: v1
kind: Service
metadata:
  name: headless-svc
spec:
  clusterIP: None # clusterIP must be None to create a headless service
  selector:
    job-name: example-job # must match Job name
---
apiVersion: batch/v1
kind: Job
metadata:
  name: example-job
spec:
  completions: 3
  parallelism: 3
  completionMode: Indexed
  template:
    spec:
      subdomain: headless-svc # has to match Service name
      restartPolicy: Never

Response:
      containers:
      - name: example-workload
        image: bash:latest
        command:
        - bash
        - -c
        - |
          for i in 0 1 2
          do
            gotStatus="-1"
            wantStatus="0"
            while [ $gotStatus -ne $wantStatus ]
            do
              ping -c 1 example-job-${i}.headless-svc > /dev/null 2>&1
              gotStatus=$?
              if [ $gotStatus -ne $wantStatus ]; then
                echo "Failed to ping pod example-job-${i}.headless-svc, retrying in 1 second..."
                sleep 1
              fi
            done
            echo "Successfully pinged pod: example-job-${i}.headless-svc"
          done

Context: 5 - Job with Pod-to-Pod Communication | After applying the example above, reach each other over the network using: <pod-hostname>.<headless-service-name>. You should see output similar to the following:


Prompt:
Explain this yaml code:

apiVersion: v1
kind: Service
metadata:
  name: headless-svc
spec:
  clusterIP: None # clusterIP must be None to create a headless service
  selector:
    job-name: example-job # must match Job name
---
apiVersion: batch/v1
kind: Job
metadata:
  name: example-job
spec:
  completions: 3
  parallelism: 3
  completionMode: Indexed
  template:
    spec:
      subdomain: headless-svc # has to match Service name
      restartPolicy: Never
      containers:
      - name: example-workload
        image: bash:latest
        command:
        - bash
        - -c
        - |
          for i in 0 1 2
          do
            gotStatus="-1"
            wantStatus="0"
            while [ $gotStatus -ne $wantStatus ]
            do
              ping -c 1 example-job-${i}.headless-svc > /dev/null 2>&1
              gotStatus=$?
              if [ $gotStatus -ne $wantStatus ]; then
                echo "Failed to ping pod example-job-${i}.headless-svc, retrying in 1 second..."
                sleep 1
              fi
            done
            echo "Successfully pinged pod: example-job-${i}.headless-svc"
          done

Response: This yaml code 5 - Job with Pod-to-Pod Communication | After applying the example above, reach each other over the network using: <pod-hostname>.<headless-service-name>. You should see output similar to the following:


Prompt:
Complete this text code:

Failed to ping pod example-job-0.headless-svc, retrying in 1 second...
Successfully pinged pod: example-job-0.headless-svc

Response:
Successfully pinged pod: example-job-1.headless-svc
Successfully pinged pod: example-job-2.headless-svc

Context: 5 - Job with Pod-to-Pod Communication | This task demonstrates running multiple Jobs based on a common template. You can use this approach to process batches of work in parallel.


Prompt:
Explain this text code:

Failed to ping pod example-job-0.headless-svc, retrying in 1 second...
Successfully pinged pod: example-job-0.headless-svc
Successfully pinged pod: example-job-1.headless-svc
Successfully pinged pod: example-job-2.headless-svc

Response: This text code 5 - Job with Pod-to-Pod Communication | This task demonstrates running multiple Jobs based on a common template. You can use this approach to process batches of work in parallel.


Prompt:
Complete this yaml code:

apiVersion: batch/v1
kind: Job
metadata:
  name: process-item-$ITEM
  labels:
    jobgroup: jobexample
spec:
  template:
    metadata:

Response:
      name: jobexample
      labels:
        jobgroup: jobexample
    spec:
      containers:
      - name: c
        image: busybox:1.28
        command: ["sh", "-c", "echo Processing item $ITEM && sleep 5"]
      restartPolicy: Never

Context: 6 - Parallel Processing using Expansions | The file you downloaded is not yet a valid Kubernetes manifest. Instead that template is a YAML representation of a Job object with some placeholders that need to be filled in before it can be used. T


Prompt:
Explain this yaml code:

apiVersion: batch/v1
kind: Job
metadata:
  name: process-item-$ITEM
  labels:
    jobgroup: jobexample
spec:
  template:
    metadata:
      name: jobexample
      labels:
        jobgroup: jobexample
    spec:
      containers:
      - name: c
        image: busybox:1.28
        command: ["sh", "-c", "echo Processing item $ITEM && sleep 5"]
      restartPolicy: Never

Response: This yaml code 6 - Parallel Processing using Expansions | The file you downloaded is not yet a valid Kubernetes manifest. Instead that template is a YAML representation of a Job object with some placeholders that need to be filled in before it can be used. T


Prompt:
Explain this text code:

# Use curl to download job-tmpl.yaml
curl -L -s -O https://k8s.io/examples/application/job/job-tmpl.yaml

Response: This text code 6 - Parallel Processing using Expansions | The file you downloaded is not yet a valid Kubernetes manifest. Instead that template is a YAML representation of a Job object with some placeholders that need to be filled in before it can be used. T


Prompt:
Complete this text code:

# Expand the template into multiple files, one for each item to be processed.
mkdir ./jobs
for i in apple banana cherry

Response:
do
  cat job-tmpl.yaml | sed "s/\$ITEM/$i/" > ./jobs/job-$i.yaml
done

Context: 6 - Parallel Processing using Expansions | Check if it worked:


Prompt:
Explain this text code:

# Expand the template into multiple files, one for each item to be processed.
mkdir ./jobs
for i in apple banana cherry
do
  cat job-tmpl.yaml | sed "s/\$ITEM/$i/" > ./jobs/job-$i.yaml
done

Response: This text code 6 - Parallel Processing using Expansions | Check if it worked:


Prompt:
Explain this text code:

job.batch/process-item-apple created
job.batch/process-item-banana created
job.batch/process-item-cherry created

Response: This text code 6 - Parallel Processing using Expansions | Now, check on the jobs:

Context: 6 - Parallel Processing using Expansions | Now, check on the jobs:


Prompt:
Complete this text code:

NAME                  COMPLETIONS   DURATION   AGE
process-item-apple    1/1           14s        22s

Response:
process-item-banana   1/1           12s        21s
process-item-cherry   1/1           12s        20s

Context: 6 - Parallel Processing using Expansions | Using the -l option to kubectl selects only the Jobs that are part of this group of jobs (there might be other unrelated jobs in the system).


Prompt:
Explain this text code:

NAME                  COMPLETIONS   DURATION   AGE
process-item-apple    1/1           14s        22s
process-item-banana   1/1           12s        21s
process-item-cherry   1/1           12s        20s

Response: This text code 6 - Parallel Processing using Expansions | Using the -l option to kubectl selects only the Jobs that are part of this group of jobs (there might be other unrelated jobs in the system).


Prompt:
Complete this text code:

NAME                        READY     STATUS      RESTARTS   AGE
process-item-apple-kixwv    0/1       Completed   0          4m

Response:
process-item-banana-wrsf7   0/1       Completed   0          4m
process-item-cherry-dnfu9   0/1       Completed   0          4m

Context: 6 - Parallel Processing using Expansions | We can use this single command to check on the output of all jobs at once:


Prompt:
Explain this text code:

NAME                        READY     STATUS      RESTARTS   AGE
process-item-apple-kixwv    0/1       Completed   0          4m
process-item-banana-wrsf7   0/1       Completed   0          4m
process-item-cherry-dnfu9   0/1       Completed   0          4m

Response: This text code 6 - Parallel Processing using Expansions | We can use this single command to check on the output of all jobs at once:


Prompt:
Explain this text code:

Processing item apple
Processing item banana
Processing item cherry

Response: This text code 6 - Parallel Processing using Expansions | In the first example, each instance of the template had one parameter, and that parameter was also used in the Job's name. However, names are restricted to contain only certain characters.

Context: 6 - Parallel Processing using Expansions | In the first example, each instance of the template had one parameter, and that parameter was also used in the Job's name. However, names are restricted to contain only certain characters.


Prompt:
Explain this text code:

# Remove the Jobs you created
# Your cluster automatically cleans up their Pods
kubectl delete job -l jobgroup=jobexample

Response: This text code 6 - Parallel Processing using Expansions | In the first example, each instance of the template had one parameter, and that parameter was also used in the Job's name. However, names are restricted to contain only certain characters.


Prompt:
Complete this yaml code:

{% set params = [{ "name": "apple", "url": "http://dbpedia.org/resource/Apple", },
                  { "name": "banana", "url": "http://dbpedia.org/resource/Banana", },
                  { "name": "cherry", "url": "http://dbpedia.org/resource/Cherry" }]
%}
{% for p in params %}
{% set name = p["name"] %}
{% set url = p["url"] %}
---
apiVersion: batch/v1
kind: Job
metadata:
  name: jobexample-{{ name }}
  labels:

Response:
    jobgroup: jobexample
spec:
  template:
    metadata:
      name: jobexample
      labels:
        jobgroup: jobexample
    spec:
      containers:
      - name: c
        image: busybox:1.28
        command: ["sh", "-c", "echo Processing URL {{ url }} && sleep 5"]
      restartPolicy: Never
{% endfor %}

Context: 6 - Parallel Processing using Expansions | The above template defines two parameters for each Job object using a list of python dicts (lines 1-4). A for loop emits one Job manifest for each set of parameters (remaining lines).


Prompt:
Explain this yaml code:

{% set params = [{ "name": "apple", "url": "http://dbpedia.org/resource/Apple", },
                  { "name": "banana", "url": "http://dbpedia.org/resource/Banana", },
                  { "name": "cherry", "url": "http://dbpedia.org/resource/Cherry" }]
%}
{% for p in params %}
{% set name = p["name"] %}
{% set url = p["url"] %}
---
apiVersion: batch/v1
kind: Job
metadata:
  name: jobexample-{{ name }}
  labels:
    jobgroup: jobexample
spec:
  template:
    metadata:
      name: jobexample
      labels:
        jobgroup: jobexample
    spec:
      containers:
      - name: c
        image: busybox:1.28
        command: ["sh", "-c", "echo Processing URL {{ url }} && sleep 5"]
      restartPolicy: Never
{% endfor %}

Response: This yaml code 6 - Parallel Processing using Expansions | The above template defines two parameters for each Job object using a list of python dicts (lines 1-4). A for loop emits one Job manifest for each set of parameters (remaining lines).


Prompt:
Explain this python code:

alias render_template='python -c "from jinja2 import Template; import sys; print(Template(sys.stdin.read()).render());"'

Response: This python code 6 - Parallel Processing using Expansions | Use render_template to convert the parameters and template into a single YAML file containing Kubernetes manifests:

Context: 6 - Parallel Processing using Expansions | Use render_template to convert the parameters and template into a single YAML file containing Kubernetes manifests:


Prompt:
Explain this text code:

# This requires the alias you defined earlier
cat job.yaml.jinja2 | render_template > jobs.yaml

Response: This text code 6 - Parallel Processing using Expansions | You can view jobs.yaml to verify that the render_template script worked correctly.

Context: 6 - Parallel Processing using Expansions | You can view jobs.yaml to verify that the render_template script worked correctly.


Prompt:
Explain this text code:

cat job.yaml.jinja2 | render_template | kubectl apply -f -

Response: This text code 6 - Parallel Processing using Expansions | Kubernetes accepts and runs the Jobs you created.

Context: 6 - Parallel Processing using Expansions | Kubernetes accepts and runs the Jobs you created.


Prompt:
Explain this text code:

# Remove the Jobs you created
# Your cluster automatically cleans up their Pods
kubectl delete job -l jobgroup=jobexample

Response: This text code 6 - Parallel Processing using Expansions | In a real use case, each Job performs some substantial computation, such as rendering a frame of a movie, or processing a range of rows in a database. If you were rendering a movie you would set $ITEM

Context: 6 - Parallel Processing using Expansions | In a real use case, each Job performs some substantial computation, such as rendering a frame of a movie, or processing a range of rows in a database. If you were rendering a movie you would set $ITEM


Prompt:
Complete this yaml code:

apiVersion: batch/v1
kind: Job
metadata:
  name: job-pod-failure-policy-failjob
spec:
  completions: 8
  parallelism: 2
  template:
    spec:
      restartPolicy: Never
      containers:
      - name: main

Response:
        image: docker.io/library/bash:5
        command: ["bash"]
        args:
        - -c
        - echo "Hello world! I'm going to exit with 42 to simulate a software bug." && sleep 30 && exit 42
  backoffLimit: 6
  podFailurePolicy:
    rules:
    - action: FailJob
      onExitCodes:
        containerName: main
        operator: In
        values: [42]

Context: 7 - Handling retriable and non-retriable pod failures with Pod failure policy | Apply the manifest:


Prompt:
Explain this yaml code:

apiVersion: batch/v1
kind: Job
metadata:
  name: job-pod-failure-policy-failjob
spec:
  completions: 8
  parallelism: 2
  template:
    spec:
      restartPolicy: Never
      containers:
      - name: main
        image: docker.io/library/bash:5
        command: ["bash"]
        args:
        - -c
        - echo "Hello world! I'm going to exit with 42 to simulate a software bug." && sleep 30 && exit 42
  backoffLimit: 6
  podFailurePolicy:
    rules:
    - action: FailJob
      onExitCodes:
        containerName: main
        operator: In
        values: [42]

Response: This yaml code 7 - Handling retriable and non-retriable pod failures with Pod failure policy | Apply the manifest:


Prompt:
Explain this bash code:

kubectl create -f https://k8s.io/examples/controllers/job-pod-failure-policy-failjob.yaml

Response: This bash code 7 - Handling retriable and non-retriable pod failures with Pod failure policy | After around 30 seconds the entire Job should be terminated. Inspect the status of the Job by running:

Context: 7 - Handling retriable and non-retriable pod failures with Pod failure policy | After around 30 seconds the entire Job should be terminated. Inspect the status of the Job by running:


Prompt:
Explain this bash code:

kubectl get jobs -l job-name=job-pod-failure-policy-failjob -o yaml

Response: This bash code 7 - Handling retriable and non-retriable pod failures with Pod failure policy | In the Job status, the following conditions display:

Context: 7 - Handling retriable and non-retriable pod failures with Pod failure policy | In the Job status, the following conditions display:


Prompt:
Complete this yaml code:

apiVersion: batch/v1
kind: Job
metadata:
  name: job-pod-failure-policy-ignore
spec:
  completions: 4
  parallelism: 2
  template:
    spec:
      restartPolicy: Never
      containers:

Response:
      - name: main
        image: docker.io/library/bash:5
        command: ["bash"]
        args:
        - -c
        - echo "Hello world! I'm going to exit with 0 (success)." && sleep 90 && exit 0
  backoffLimit: 0
  podFailurePolicy:
    rules:
    - action: Ignore
      onPodConditions:
      - type: DisruptionTarget


Prompt:
Explain this yaml code:

apiVersion: batch/v1
kind: Job
metadata:
  name: job-pod-failure-policy-ignore
spec:
  completions: 4
  parallelism: 2
  template:
    spec:
      restartPolicy: Never
      containers:
      - name: main
        image: docker.io/library/bash:5
        command: ["bash"]
        args:
        - -c
        - echo "Hello world! I'm going to exit with 0 (success)." && sleep 90 && exit 0
  backoffLimit: 0
  podFailurePolicy:
    rules:
    - action: Ignore
      onPodConditions:
      - type: DisruptionTarget

Response: This yaml code 7 - Handling retriable and non-retriable pod failures with Pod failure policy | Apply the manifest:


Prompt:
Explain this bash code:

kubectl create -f https://k8s.io/examples/controllers/job-pod-failure-policy-ignore.yaml

Response: This bash code 7 - Handling retriable and non-retriable pod failures with Pod failure policy | Run this command to check the nodeName the Pod is scheduled to:

Context: 7 - Handling retriable and non-retriable pod failures with Pod failure policy | Run this command to check the nodeName the Pod is scheduled to:


Prompt:
Explain this text code:

nodeName=$(kubectl get pods -l job-name=job-pod-failure-policy-ignore -o jsonpath='{.items[0].spec.nodeName}')

Response: This text code 7 - Handling retriable and non-retriable pod failures with Pod failure policy | Drain the node to evict the Pod before it completes (within 90s):

Context: 7 - Handling retriable and non-retriable pod failures with Pod failure policy | Drain the node to evict the Pod before it completes (within 90s):


Prompt:
Explain this bash code:

kubectl drain nodes/$nodeName --ignore-daemonsets --grace-period=0

Response: This bash code 7 - Handling retriable and non-retriable pod failures with Pod failure policy | Inspect the .status.failed to check the counter for the Job is not incremented:

Context: 7 - Handling retriable and non-retriable pod failures with Pod failure policy | Inspect the .status.failed to check the counter for the Job is not incremented:


Prompt:
Explain this bash code:

kubectl get jobs -l job-name=job-pod-failure-policy-ignore -o yaml

Response: This bash code 7 - Handling retriable and non-retriable pod failures with Pod failure policy | Uncordon the node:

Context: 7 - Handling retriable and non-retriable pod failures with Pod failure policy | Uncordon the node:


Prompt:
Complete this yaml code:

apiVersion: batch/v1
kind: Job
metadata:
  name: job-pod-failure-policy-config-issue
spec:
  completions: 8
  parallelism: 2
  template:
    spec:

Response:
      restartPolicy: Never
      containers:
      - name: main
        image: "non-existing-repo/non-existing-image:example"
  backoffLimit: 6
  podFailurePolicy:
    rules:
    - action: FailJob
      onPodConditions:
      - type: ConfigIssue


Prompt:
Explain this yaml code:

apiVersion: batch/v1
kind: Job
metadata:
  name: job-pod-failure-policy-config-issue
spec:
  completions: 8
  parallelism: 2
  template:
    spec:
      restartPolicy: Never
      containers:
      - name: main
        image: "non-existing-repo/non-existing-image:example"
  backoffLimit: 6
  podFailurePolicy:
    rules:
    - action: FailJob
      onPodConditions:
      - type: ConfigIssue

Response: This yaml code 7 - Handling retriable and non-retriable pod failures with Pod failure policy | Apply the manifest:


Prompt:
Explain this bash code:

kubectl create -f https://k8s.io/examples/controllers/job-pod-failure-policy-config-issue.yaml

Response: This bash code 7 - Handling retriable and non-retriable pod failures with Pod failure policy | Note that, the image is misconfigured, as it does not exist.

Context: 7 - Handling retriable and non-retriable pod failures with Pod failure policy | Note that, the image is misconfigured, as it does not exist.


Prompt:
Explain this bash code:

kubectl get pods -l job-name=job-pod-failure-policy-config-issue -o yaml

Response: This bash code 7 - Handling retriable and non-retriable pod failures with Pod failure policy | You will see output similar to this:

Context: 7 - Handling retriable and non-retriable pod failures with Pod failure policy | You will see output similar to this:


Prompt:
Complete this text code:

containerStatuses:
- image: non-existing-repo/non-existing-image:example
   ...
   state:

Response:
   waiting:
      message: Back-off pulling image "non-existing-repo/non-existing-image:example"
      reason: ImagePullBackOff
      ...
phase: Pending

Context: 7 - Handling retriable and non-retriable pod failures with Pod failure policy | Note that the pod remains in the Pending phase as it fails to pull the misconfigured image. This, in principle, could be a transient issue and the image could get pulled. However, in this case, the im


Prompt:
Explain this text code:

containerStatuses:
- image: non-existing-repo/non-existing-image:example
   ...
   state:
   waiting:
      message: Back-off pulling image "non-existing-repo/non-existing-image:example"
      reason: ImagePullBackOff
      ...
phase: Pending

Response: This text code 7 - Handling retriable and non-retriable pod failures with Pod failure policy | Note that the pod remains in the Pending phase as it fails to pull the misconfigured image. This, in principle, could be a transient issue and the image could get pulled. However, in this case, the im


Prompt:
Complete this text code:

cat <<EOF > patch.yaml
status:
  conditions:
  - type: ConfigIssue

Response:
    status: "True"
    reason: "NonExistingImage"
    lastTransitionTime: "$(date -u +"%Y-%m-%dT%H:%M:%SZ")"
EOF

Context: 7 - Handling retriable and non-retriable pod failures with Pod failure policy | Second, select one of the pods created by the job by running:


Prompt:
Explain this text code:

cat <<EOF > patch.yaml
status:
  conditions:
  - type: ConfigIssue
    status: "True"
    reason: "NonExistingImage"
    lastTransitionTime: "$(date -u +"%Y-%m-%dT%H:%M:%SZ")"
EOF

Response: This text code 7 - Handling retriable and non-retriable pod failures with Pod failure policy | Second, select one of the pods created by the job by running:


Prompt:
Explain this text code:

podName=$(kubectl get pods -l job-name=job-pod-failure-policy-config-issue -o jsonpath='{.items[0].metadata.name}')

Response: This text code 7 - Handling retriable and non-retriable pod failures with Pod failure policy | Then, apply the patch on one of the pods by running the following command:

Context: 7 - Handling retriable and non-retriable pod failures with Pod failure policy | Then, apply the patch on one of the pods by running the following command:


Prompt:
Explain this bash code:

kubectl patch pod $podName --subresource=status --patch-file=patch.yaml

Response: This bash code 7 - Handling retriable and non-retriable pod failures with Pod failure policy | If applied successfully, you will get a notification like this:

Context: 7 - Handling retriable and non-retriable pod failures with Pod failure policy | If applied successfully, you will get a notification like this:


Prompt:
Explain this text code:

pod/job-pod-failure-policy-config-issue-k6pvp patched

Response: This text code 7 - Handling retriable and non-retriable pod failures with Pod failure policy | Delete the pod to transition it to Failed phase, by running the command:

Context: 7 - Handling retriable and non-retriable pod failures with Pod failure policy | Delete the pod to transition it to Failed phase, by running the command:


Prompt:
Explain this bash code:

kubectl get jobs -l job-name=job-pod-failure-policy-config-issue -o yaml

Response: This bash code 7 - Handling retriable and non-retriable pod failures with Pod failure policy | In the Job status, see a job Failed condition with the field reason equal PodFailurePolicy. Additionally, the message field contains a more detailed information about the Job termination, such as: Pod

Context: 7 - Handling retriable and non-retriable pod failures with Pod failure policy | In the Job status, see a job Failed condition with the field reason equal PodFailurePolicy. Additionally, the message field contains a more detailed information about the Job termination, such as: Pod


Prompt:
Explain this bash code:

kubectl delete jobs/job-pod-failure-policy-config-issue

Response: This bash code 7 - Handling retriable and non-retriable pod failures with Pod failure policy | The cluster automatically cleans up the Pods.

Context: 7 - Handling retriable and non-retriable pod failures with Pod failure policy | The cluster automatically cleans up the Pods.


Prompt:
Complete this yaml code:

apiVersion: batch/v1
kind: Job
metadata:
  name: job-backoff-limit-per-index-failindex
spec:
  completions: 4
  parallelism: 2
  completionMode: Indexed
  backoffLimitPerIndex: 1
  template:
    spec:
      restartPolicy: Never
      containers:
      - name: main
        image: docker.io/library/python:3
        command:
          # The script:
          # - fails the Pod with index 0 with exit code 1, which results in one retry;
          # - fails the Pod with index 1 with exit code 42 which results
          #   in failing the index without retry.

Response:
          # - succeeds Pods with any other index.
          - python3
          - -c
          - |
            import os, sys
            index = int(os.environ.get("JOB_COMPLETION_INDEX"))
            if index == 0:
              sys.exit(1)
            elif index == 1:
              sys.exit(42)
            else:
              sys.exit(0)
  backoffLimit: 6
  podFailurePolicy:
    rules:
    - action: FailIndex
      onExitCodes:
        containerName: main
        operator: In
        values: [42]


Prompt:
Explain this yaml code:

apiVersion: batch/v1
kind: Job
metadata:
  name: job-backoff-limit-per-index-failindex
spec:
  completions: 4
  parallelism: 2
  completionMode: Indexed
  backoffLimitPerIndex: 1
  template:
    spec:
      restartPolicy: Never
      containers:
      - name: main
        image: docker.io/library/python:3
        command:
          # The script:
          # - fails the Pod with index 0 with exit code 1, which results in one retry;
          # - fails the Pod with index 1 with exit code 42 which results
          #   in failing the index without retry.
          # - succeeds Pods with any other index.
          - python3
          - -c
          - |
            import os, sys
            index = int(os.environ.get("JOB_COMPLETION_INDEX"))
            if index == 0:
              sys.exit(1)
            elif index == 1:
              sys.exit(42)
            else:
              sys.exit(0)
  backoffLimit: 6
  podFailurePolicy:
    rules:
    - action: FailIndex
      onExitCodes:
        containerName: main
        operator: In
        values: [42]

Response: This yaml code 7 - Handling retriable and non-retriable pod failures with Pod failure policy | Apply the manifest:


Prompt:
Explain this bash code:

kubectl create -f https://k8s.io/examples/controllers/job-backoff-limit-per-index-failindex.yaml

Response: This bash code 7 - Handling retriable and non-retriable pod failures with Pod failure policy | After around 15 seconds, inspect the status of the Pods for the Job. You can do that by running:

Context: 7 - Handling retriable and non-retriable pod failures with Pod failure policy | After around 15 seconds, inspect the status of the Pods for the Job. You can do that by running:


Prompt:
Explain this bash code:

kubectl get pods -l job-name=job-backoff-limit-per-index-failindex -o yaml

Response: This bash code 7 - Handling retriable and non-retriable pod failures with Pod failure policy | You will see output similar to this:


Prompt:
Complete this text code:

NAME                                            READY   STATUS      RESTARTS   AGE
job-backoff-limit-per-index-failindex-0-4g4cm   0/1     Error       0          4s
job-backoff-limit-per-index-failindex-0-fkdzq   0/1     Error       0          15s

Response:
job-backoff-limit-per-index-failindex-1-2bgdj   0/1     Error       0          15s
job-backoff-limit-per-index-failindex-2-vs6lt   0/1     Completed   0          11s
job-backoff-limit-per-index-failindex-3-s7s47   0/1     Completed   0          6s

Context: 7 - Handling retriable and non-retriable pod failures with Pod failure policy | Note that the output shows the following:


Prompt:
Explain this text code:

NAME                                            READY   STATUS      RESTARTS   AGE
job-backoff-limit-per-index-failindex-0-4g4cm   0/1     Error       0          4s
job-backoff-limit-per-index-failindex-0-fkdzq   0/1     Error       0          15s
job-backoff-limit-per-index-failindex-1-2bgdj   0/1     Error       0          15s
job-backoff-limit-per-index-failindex-2-vs6lt   0/1     Completed   0          11s
job-backoff-limit-per-index-failindex-3-s7s47   0/1     Completed   0          6s

Response: This text code 7 - Handling retriable and non-retriable pod failures with Pod failure policy | Note that the output shows the following:


Prompt:
Explain this bash code:

kubectl get jobs -l job-name=job-backoff-limit-per-index-failindex -o yaml

Response: This bash code 7 - Handling retriable and non-retriable pod failures with Pod failure policy | In the Job status, see that the failedIndexes field shows "0,1", because both indexes failed. Because the index 1 was not retried the number of failed Pods, indicated by the status field "failed" equa

Context: 7 - Handling retriable and non-retriable pod failures with Pod failure policy | In the Job status, see that the failedIndexes field shows "0,1", because both indexes failed. Because the index 1 was not retried the number of failed Pods, indicated by the status field "failed" equa


Prompt:
Explain this bash code:

kubectl delete jobs/job-backoff-limit-per-index-failindex

Response: This bash code 7 - Handling retriable and non-retriable pod failures with Pod failure policy | The cluster automatically cleans up the Pods.


Prompt:
Complete this yaml code:

apiVersion: batch/v1
kind: CronJob
metadata:
  name: hello
spec:
  schedule: "* * * * *"
  jobTemplate:
    spec:
      template:

Response:
        spec:
          containers:
          - name: hello
            image: busybox:1.28
            imagePullPolicy: IfNotPresent
            command:
            - /bin/sh
            - -c
            - date; echo Hello from the Kubernetes cluster
          restartPolicy: OnFailure

Context: 1 - Running Automated Tasks with a CronJob | Run the example CronJob by using this command:


Prompt:
Explain this yaml code:

apiVersion: batch/v1
kind: CronJob
metadata:
  name: hello
spec:
  schedule: "* * * * *"
  jobTemplate:
    spec:
      template:
        spec:
          containers:
          - name: hello
            image: busybox:1.28
            imagePullPolicy: IfNotPresent
            command:
            - /bin/sh
            - -c
            - date; echo Hello from the Kubernetes cluster
          restartPolicy: OnFailure

Response: This yaml code 1 - Running Automated Tasks with a CronJob | Run the example CronJob by using this command:


Prompt:
Explain this shell code:

kubectl create -f https://k8s.io/examples/application/job/cronjob.yaml

Response: This shell code 1 - Running Automated Tasks with a CronJob | The output is similar to this:

Context: 1 - Running Automated Tasks with a CronJob | The output is similar to this:


Prompt:
Explain this text code:

NAME    SCHEDULE      SUSPEND   ACTIVE   LAST SCHEDULE   AGE
hello   */1 * * * *   False     0        <none>          10s

Response: This text code 1 - Running Automated Tasks with a CronJob | As you can see from the results of the command, the cron job has not scheduled or run any jobs yet. Watch for the job to be created in around one minute:

Context: 1 - Running Automated Tasks with a CronJob | As you can see from the results of the command, the cron job has not scheduled or run any jobs yet. Watch for the job to be created in around one minute:


Prompt:
Complete this text code:

NAME               COMPLETIONS   DURATION   AGE
hello-4111706356   0/1                      0s

Response:
hello-4111706356   0/1           0s         0s
hello-4111706356   1/1           5s         5s

Context: 1 - Running Automated Tasks with a CronJob | Now you've seen one running job scheduled by the "hello" cron job. You can stop watching the job and view the cron job again to see that it scheduled the job:


Prompt:
Explain this text code:

NAME               COMPLETIONS   DURATION   AGE
hello-4111706356   0/1                      0s
hello-4111706356   0/1           0s         0s
hello-4111706356   1/1           5s         5s

Response: This text code 1 - Running Automated Tasks with a CronJob | Now you've seen one running job scheduled by the "hello" cron job. You can stop watching the job and view the cron job again to see that it scheduled the job:


Prompt:
Explain this text code:

NAME    SCHEDULE      SUSPEND   ACTIVE   LAST SCHEDULE   AGE
hello   */1 * * * *   False     0        50s             75s

Response: This text code 1 - Running Automated Tasks with a CronJob | You should see that the cron job hello successfully scheduled a job at the time specified in LAST SCHEDULE. There are currently 0 active jobs, meaning that the job has completed or failed.

Context: 1 - Running Automated Tasks with a CronJob | You should see that the cron job hello successfully scheduled a job at the time specified in LAST SCHEDULE. There are currently 0 active jobs, meaning that the job has completed or failed.


Prompt:
Explain this shell code:

# Replace "hello-4111706356" with the job name in your system
pods=$(kubectl get pods --selector=job-name=hello-4111706356 --output=jsonpath={.items[*].metadata.name})

Response: This shell code 1 - Running Automated Tasks with a CronJob | Show the pod log:

Context: 1 - Running Automated Tasks with a CronJob | Show the pod log:


Prompt:
Explain this text code:

Fri Feb 22 11:02:09 UTC 2019
Hello from the Kubernetes cluster

Response: This text code 1 - Running Automated Tasks with a CronJob | When you don't need a cron job any more, delete it with kubectl delete cronjob <cronjob name>:

Context: 1 - Running Automated Tasks with a CronJob | When you don't need a cron job any more, delete it with kubectl delete cronjob <cronjob name>:


Prompt:
Explain this shell code:

# make a Service for the StatefulSet to use
kubectl create -f https://kubernetes.io/examples/application/job/rabbitmq/rabbitmq-service.yaml

Response: This shell code 2 - Coarse Parallel Processing Using a Work Queue | Now, we can experiment with accessing the message queue. We will create a temporary interactive pod, install some tools on it, and experiment with queues.

Context: 2 - Coarse Parallel Processing Using a Work Queue | Now, we can experiment with accessing the message queue. We will create a temporary interactive pod, install some tools on it, and experiment with queues.


Prompt:
Explain this shell code:

kubectl create -f https://kubernetes.io/examples/application/job/rabbitmq/rabbitmq-statefulset.yaml

Response: This shell code 2 - Coarse Parallel Processing Using a Work Queue | Now, we can experiment with accessing the message queue. We will create a temporary interactive pod, install some tools on it, and experiment with queues.


Prompt:
Explain this shell code:

# Create a temporary interactive container
kubectl run -i --tty temp --image ubuntu:22.04

Response: This shell code 2 - Coarse Parallel Processing Using a Work Queue | Note that your pod name and command prompt will be different.

Context: 2 - Coarse Parallel Processing Using a Work Queue | Note that your pod name and command prompt will be different.


Prompt:
Explain this text code:

Waiting for pod default/temp-loe07 to be running, status is Pending, pod ready: false
... [ previous line repeats several times .. hit return when it stops ] ...

Response: This text code 2 - Coarse Parallel Processing Using a Work Queue | Note that your pod name and command prompt will be different.


Prompt:
Explain this shell code:

apt-get update && apt-get install -y curl ca-certificates amqp-tools python3 dnsutils

Response: This shell code 2 - Coarse Parallel Processing Using a Work Queue | Later, you will make a container image that includes these packages.

Context: 2 - Coarse Parallel Processing Using a Work Queue | Later, you will make a container image that includes these packages.


Prompt:
Explain this text code:

# Run these commands inside the Pod
# Note the rabbitmq-service has a DNS name, provided by Kubernetes:
nslookup rabbitmq-service

Response: This text code 2 - Coarse Parallel Processing Using a Work Queue | (the IP addresses will vary)

Context: 2 - Coarse Parallel Processing Using a Work Queue | (the IP addresses will vary)


Prompt:
Complete this text code:

Server:        10.0.0.10
Address:    10.0.0.10#53

Response:
Name:    rabbitmq-service.default.svc.cluster.local
Address: 10.0.147.152


Prompt:
Explain this text code:

Server:        10.0.0.10
Address:    10.0.0.10#53

Name:    rabbitmq-service.default.svc.cluster.local
Address: 10.0.147.152

Response: This text code 2 - Coarse Parallel Processing Using a Work Queue | (the IP addresses will vary)


Prompt:
Explain this shell code:

# run this check inside the Pod
env | grep RABBITMQ_SERVICE | grep HOST

Response: This shell code 2 - Coarse Parallel Processing Using a Work Queue | (the IP address will vary)

Context: 2 - Coarse Parallel Processing Using a Work Queue | (the IP address will vary)


Prompt:
Complete this shell code:

# Run these commands inside the Pod
# In the next line, rabbitmq-service is the hostname where the rabbitmq-service
# can be reached.  5672 is the standard port for rabbitmq.
export BROKER_URL=amqp://guest:guest@rabbitmq-service:5672
# If you could not resolve "rabbitmq-service" in the previous step,

Response:
# then use this command instead:
BROKER_URL=amqp://guest:guest@$RABBITMQ_SERVICE_SERVICE_HOST:5672

# Now create a queue:

/usr/bin/amqp-declare-queue --url=$BROKER_URL -q foo -d

Context: 2 - Coarse Parallel Processing Using a Work Queue | Publish one message to the queue:


Prompt:
Explain this shell code:

# Run these commands inside the Pod
# In the next line, rabbitmq-service is the hostname where the rabbitmq-service
# can be reached.  5672 is the standard port for rabbitmq.
export BROKER_URL=amqp://guest:guest@rabbitmq-service:5672
# If you could not resolve "rabbitmq-service" in the previous step,
# then use this command instead:
BROKER_URL=amqp://guest:guest@$RABBITMQ_SERVICE_SERVICE_HOST:5672

# Now create a queue:

/usr/bin/amqp-declare-queue --url=$BROKER_URL -q foo -d

Response: This shell code 2 - Coarse Parallel Processing Using a Work Queue | Publish one message to the queue:


Prompt:
Complete this shell code:

/usr/bin/amqp-publish --url=$BROKER_URL -r foo -p -b Hello

Response:
# And get it back.

/usr/bin/amqp-consume --url=$BROKER_URL -q foo -c 1 cat && echo 1>&2

Context: 2 - Coarse Parallel Processing Using a Work Queue | In the last command, the amqp-consume tool took one message (-c 1) from the queue, and passes that message to the standard input of an arbitrary command. In this case, the program cat prints out the c


Prompt:
Explain this shell code:

/usr/bin/amqp-publish --url=$BROKER_URL -r foo -p -b Hello

# And get it back.

/usr/bin/amqp-consume --url=$BROKER_URL -q foo -c 1 cat && echo 1>&2

Response: This shell code 2 - Coarse Parallel Processing Using a Work Queue | In the last command, the amqp-consume tool took one message (-c 1) from the queue, and passes that message to the standard input of an arbitrary command. In this case, the program cat prints out the c


Prompt:
Explain this shell code:

# Run this on your computer, not in the Pod
/usr/bin/amqp-declare-queue --url=$BROKER_URL -q job1  -d

Response: This shell code 2 - Coarse Parallel Processing Using a Work Queue | Add items to the queue:

Context: 2 - Coarse Parallel Processing Using a Work Queue | Add items to the queue:


Prompt:
Complete this shell code:

for f in apple banana cherry date fig grape lemon melon
do

Response:
  /usr/bin/amqp-publish --url=$BROKER_URL -r job1 -p -b $f
done

Context: 2 - Coarse Parallel Processing Using a Work Queue | You added 8 messages to the queue.


Prompt:
Explain this shell code:

for f in apple banana cherry date fig grape lemon melon
do
  /usr/bin/amqp-publish --url=$BROKER_URL -r job1 -p -b $f
done

Response: This shell code 2 - Coarse Parallel Processing Using a Work Queue | You added 8 messages to the queue.


Prompt:
Complete this python code:

#!/usr/bin/env python

# Just prints standard out and sleeps for 10 seconds.

Response:
import sys
import time
print("Processing " + sys.stdin.readlines()[0])
time.sleep(10)

Context: 2 - Coarse Parallel Processing Using a Work Queue | Give the script execution permission:


Prompt:
Explain this python code:

#!/usr/bin/env python

# Just prints standard out and sleeps for 10 seconds.
import sys
import time
print("Processing " + sys.stdin.readlines()[0])
time.sleep(10)

Response: This python code 2 - Coarse Parallel Processing Using a Work Queue | Give the script execution permission:


Prompt:
Explain this shell code:

docker tag job-wq-1 <username>/job-wq-1
docker push <username>/job-wq-1

Response: This shell code 2 - Coarse Parallel Processing Using a Work Queue | If you are using an alternative container image registry, tag the image and push it there instead.

Context: 2 - Coarse Parallel Processing Using a Work Queue | If you are using an alternative container image registry, tag the image and push it there instead.


Prompt:
Complete this yaml code:

apiVersion: batch/v1
kind: Job
metadata:
  name: job-wq-1
spec:
  completions: 8
  parallelism: 2
  template:
    metadata:
      name: job-wq-1

Response:
    spec:
      containers:
      - name: c
        image: gcr.io/<project>/job-wq-1
        env:
        - name: BROKER_URL
          value: amqp://guest:guest@rabbitmq-service:5672
        - name: QUEUE
          value: job1
      restartPolicy: OnFailure

Context: 2 - Coarse Parallel Processing Using a Work Queue | In this example, each pod works on one item from the queue and then exits. So, the completion count of the Job corresponds to the number of work items done. That is why the example manifest has .spec.


Prompt:
Explain this yaml code:

apiVersion: batch/v1
kind: Job
metadata:
  name: job-wq-1
spec:
  completions: 8
  parallelism: 2
  template:
    metadata:
      name: job-wq-1
    spec:
      containers:
      - name: c
        image: gcr.io/<project>/job-wq-1
        env:
        - name: BROKER_URL
          value: amqp://guest:guest@rabbitmq-service:5672
        - name: QUEUE
          value: job1
      restartPolicy: OnFailure

Response: This yaml code 2 - Coarse Parallel Processing Using a Work Queue | In this example, each pod works on one item from the queue and then exits. So, the completion count of the Job corresponds to the number of work items done. That is why the example manifest has .spec.


Prompt:
Explain this shell code:

# this assumes you downloaded and then edited the manifest already
kubectl apply -f ./job.yaml

Response: This shell code 2 - Coarse Parallel Processing Using a Work Queue | You can wait for the Job to succeed, with a timeout:

Context: 2 - Coarse Parallel Processing Using a Work Queue | You can wait for the Job to succeed, with a timeout:


Prompt:
Explain this shell code:

# The check for condition name is case insensitive
kubectl wait --for=condition=complete --timeout=300s job/job-wq-1

Response: This shell code 2 - Coarse Parallel Processing Using a Work Queue | Next, check on the Job:

Context: 2 - Coarse Parallel Processing Using a Work Queue | Next, check on the Job:


Prompt:
Complete this text code:

Name:             job-wq-1
Namespace:        default
Selector:         controller-uid=41d75705-92df-11e7-b85e-fa163ee3c11f
Labels:           controller-uid=41d75705-92df-11e7-b85e-fa163ee3c11f
                  job-name=job-wq-1
Annotations:      <none>
Parallelism:      2
Completions:      8
Start Time:       Wed, 06 Sep 2022 16:42:02 +0000
Pods Statuses:    0 Running / 8 Succeeded / 0 Failed
Pod Template:
  Labels:       controller-uid=41d75705-92df-11e7-b85e-fa163ee3c11f
                job-name=job-wq-1
  Containers:
   c:
    Image:      container-registry.example/causal-jigsaw-637/job-wq-1

Response:
    Port:
    Environment:
      BROKER_URL:       amqp://guest:guest@rabbitmq-service:5672
      QUEUE:            job1
    Mounts:             <none>
  Volumes:              <none>
Events:
  FirstSeen  LastSeen   Count    From    SubobjectPath    Type      Reason              Message
  ─────────  ────────   ─────    ────    ─────────────    ──────    ──────              ───────
  27s        27s        1        {job }                   Normal    SuccessfulCreate    Created pod: job-wq-1-hcobb
  27s        27s        1        {job }                   Normal    SuccessfulCreate    Created pod: job-wq-1-weytj
  27s        27s        1        {job }                   Normal    SuccessfulCreate    Created pod: job-wq-1-qaam5
  27s        27s        1        {job }                   Normal    SuccessfulCreate    Created pod: job-wq-1-b67sr
  26s        26s        1        {job }                   Normal    SuccessfulCreate    Created pod: job-wq-1-xe5hj
  15s        15s        1        {job }                   Normal    SuccessfulCreate    Created pod: job-wq-1-w2zqe
  14s        14s        1        {job }                   Normal    SuccessfulCreate    Created pod: job-wq-1-d6ppa
  14s        14s        1        {job }                   Normal    SuccessfulCreate    Created pod: job-wq-1-p17e0

Context: 2 - Coarse Parallel Processing Using a Work Queue | All the pods for that Job succeeded! You're done.


Prompt:
Explain this text code:

Name:             job-wq-1
Namespace:        default
Selector:         controller-uid=41d75705-92df-11e7-b85e-fa163ee3c11f
Labels:           controller-uid=41d75705-92df-11e7-b85e-fa163ee3c11f
                  job-name=job-wq-1
Annotations:      <none>
Parallelism:      2
Completions:      8
Start Time:       Wed, 06 Sep 2022 16:42:02 +0000
Pods Statuses:    0 Running / 8 Succeeded / 0 Failed
Pod Template:
  Labels:       controller-uid=41d75705-92df-11e7-b85e-fa163ee3c11f
                job-name=job-wq-1
  Containers:
   c:
    Image:      container-registry.example/causal-jigsaw-637/job-wq-1
    Port:
    Environment:
      BROKER_URL:       amqp://guest:guest@rabbitmq-service:5672
      QUEUE:            job1
    Mounts:             <none>
  Volumes:              <none>
Events:
  FirstSeen  LastSeen   Count    From    SubobjectPath    Type      Reason              Message
  ─────────  ────────   ─────    ────    ─────────────    ──────    ──────              ───────
  27s        27s        1        {job }                   Normal    SuccessfulCreate    Created pod: job-wq-1-hcobb
  27s        27s        1        {job }                   Normal    SuccessfulCreate    Created pod: job-wq-1-weytj
  27s        27s        1        {job }                   Normal    SuccessfulCreate    Created pod: job-wq-1-qaam5
  27s        27s        1        {job }                   Normal    SuccessfulCreate    Created pod: job-wq-1-b67sr
  26s        26s        1        {job }                   Normal    SuccessfulCreate    Created pod: job-wq-1-xe5hj
  15s        15s        1        {job }                   Normal    SuccessfulCreate    Created pod: job-wq-1-w2zqe
  14s        14s        1        {job }                   Normal    SuccessfulCreate    Created pod: job-wq-1-d6ppa
  14s        14s        1        {job }                   Normal    SuccessfulCreate    Created pod: job-wq-1-p17e0

Response: This text code 2 - Coarse Parallel Processing Using a Work Queue | All the pods for that Job succeeded! You're done.


Prompt:
Explain this shell code:

kubectl apply -f https://k8s.io/examples/application/job/redis/redis-pod.yaml
kubectl apply -f https://k8s.io/examples/application/job/redis/redis-service.yaml

Response: This shell code 3 - Fine Parallel Processing Using a Work Queue | Now let's fill the queue with some "tasks". In this example, the tasks are strings to be printed.

Context: 3 - Fine Parallel Processing Using a Work Queue | Now let's fill the queue with some "tasks". In this example, the tasks are strings to be printed.


Prompt:
Explain this shell code:

kubectl run -i --tty temp --image redis --command "/bin/sh"

Response: This shell code 3 - Fine Parallel Processing Using a Work Queue | Now hit enter, start the Redis CLI, and create a list with some work items in it.

Context: 3 - Fine Parallel Processing Using a Work Queue | Now hit enter, start the Redis CLI, and create a list with some work items in it.


Prompt:
Explain this text code:

Waiting for pod default/redis2-c7h78 to be running, status is Pending, pod ready: false
Hit enter for command prompt

Response: This text code 3 - Fine Parallel Processing Using a Work Queue | Now hit enter, start the Redis CLI, and create a list with some work items in it.


Prompt:
Complete this console code:

redis:6379> rpush job2 "apple"
(integer) 1
redis:6379> rpush job2 "banana"
(integer) 2
redis:6379> rpush job2 "cherry"
(integer) 3
redis:6379> rpush job2 "date"
(integer) 4
redis:6379> rpush job2 "fig"
(integer) 5
redis:6379> rpush job2 "grape"
(integer) 6
redis:6379> rpush job2 "lemon"
(integer) 7

Response:
redis:6379> rpush job2 "melon"
(integer) 8
redis:6379> rpush job2 "orange"
(integer) 9
redis:6379> lrange job2 0 -1
1) "apple"
2) "banana"
3) "cherry"
4) "date"
5) "fig"
6) "grape"
7) "lemon"
8) "melon"
9) "orange"

Context: 3 - Fine Parallel Processing Using a Work Queue | So, the list with key job2 will be the work queue.


Prompt:
Explain this console code:

redis:6379> rpush job2 "apple"
(integer) 1
redis:6379> rpush job2 "banana"
(integer) 2
redis:6379> rpush job2 "cherry"
(integer) 3
redis:6379> rpush job2 "date"
(integer) 4
redis:6379> rpush job2 "fig"
(integer) 5
redis:6379> rpush job2 "grape"
(integer) 6
redis:6379> rpush job2 "lemon"
(integer) 7
redis:6379> rpush job2 "melon"
(integer) 8
redis:6379> rpush job2 "orange"
(integer) 9
redis:6379> lrange job2 0 -1
1) "apple"
2) "banana"
3) "cherry"
4) "date"
5) "fig"
6) "grape"
7) "lemon"
8) "melon"
9) "orange"

Response: This console code 3 - Fine Parallel Processing Using a Work Queue | So, the list with key job2 will be the work queue.


Prompt:
Complete this python code:

#!/usr/bin/env python

import time
import rediswq

host="redis"
# Uncomment next two lines if you do not have Kube-DNS working.
# import os
# host = os.getenv("REDIS_SERVICE_HOST")

q = rediswq.RedisWQ(name="job2", host=host)

Response:
print("Worker with sessionID: " +  q.sessionID())
print("Initial queue state: empty=" + str(q.empty()))
while not q.empty():
  item = q.lease(lease_secs=10, block=True, timeout=2)
  if item is not None:
    itemstr = item.decode("utf-8")
    print("Working on " + itemstr)
    time.sleep(10) # Put your actual work here instead of sleep.
    q.complete(item)
  else:
    print("Waiting for work")
print("Queue empty, exiting")

Context: 3 - Fine Parallel Processing Using a Work Queue | You could also download worker.py, rediswq.py, and Dockerfile files, then build the container image. Here's an example using Docker to do the image build:


Prompt:
Explain this python code:

#!/usr/bin/env python

import time
import rediswq

host="redis"
# Uncomment next two lines if you do not have Kube-DNS working.
# import os
# host = os.getenv("REDIS_SERVICE_HOST")

q = rediswq.RedisWQ(name="job2", host=host)
print("Worker with sessionID: " +  q.sessionID())
print("Initial queue state: empty=" + str(q.empty()))
while not q.empty():
  item = q.lease(lease_secs=10, block=True, timeout=2)
  if item is not None:
    itemstr = item.decode("utf-8")
    print("Working on " + itemstr)
    time.sleep(10) # Put your actual work here instead of sleep.
    q.complete(item)
  else:
    print("Waiting for work")
print("Queue empty, exiting")

Response: This python code 3 - Fine Parallel Processing Using a Work Queue | You could also download worker.py, rediswq.py, and Dockerfile files, then build the container image. Here's an example using Docker to do the image build:


Prompt:
Explain this shell code:

docker tag job-wq-2 <username>/job-wq-2
docker push <username>/job-wq-2

Response: This shell code 3 - Fine Parallel Processing Using a Work Queue | You need to push to a public repository or configure your cluster to be able to access your private repository.

Context: 3 - Fine Parallel Processing Using a Work Queue | You need to push to a public repository or configure your cluster to be able to access your private repository.


Prompt:
Complete this yaml code:

apiVersion: batch/v1
kind: Job
metadata:
  name: job-wq-2
spec:
  parallelism: 2
  template:

Response:
    metadata:
      name: job-wq-2
    spec:
      containers:
      - name: c
        image: gcr.io/myproject/job-wq-2
      restartPolicy: OnFailure

Context: 3 - Fine Parallel Processing Using a Work Queue | In this example, each pod works on several items from the queue and then exits when there are no more items. Since the workers themselves detect when the workqueue is empty, and the Job controller doe


Prompt:
Explain this yaml code:

apiVersion: batch/v1
kind: Job
metadata:
  name: job-wq-2
spec:
  parallelism: 2
  template:
    metadata:
      name: job-wq-2
    spec:
      containers:
      - name: c
        image: gcr.io/myproject/job-wq-2
      restartPolicy: OnFailure

Response: This yaml code 3 - Fine Parallel Processing Using a Work Queue | In this example, each pod works on several items from the queue and then exits when there are no more items. Since the workers themselves detect when the workqueue is empty, and the Job controller doe


Prompt:
Explain this shell code:

# this assumes you downloaded and then edited the manifest already
kubectl apply -f ./job.yaml

Response: This shell code 3 - Fine Parallel Processing Using a Work Queue | Now wait a bit, then check on the Job:

Context: 3 - Fine Parallel Processing Using a Work Queue | Now wait a bit, then check on the Job:


Prompt:
Complete this text code:

Name:             job-wq-2
Namespace:        default
Selector:         controller-uid=b1c7e4e3-92e1-11e7-b85e-fa163ee3c11f
Labels:           controller-uid=b1c7e4e3-92e1-11e7-b85e-fa163ee3c11f
                  job-name=job-wq-2
Annotations:      <none>
Parallelism:      2
Completions:      <unset>
Start Time:       Mon, 11 Jan 2022 17:07:59 +0000
Pods Statuses:    1 Running / 0 Succeeded / 0 Failed
Pod Template:
  Labels:       controller-uid=b1c7e4e3-92e1-11e7-b85e-fa163ee3c11f

Response:
                job-name=job-wq-2
  Containers:
   c:
    Image:              container-registry.example/exampleproject/job-wq-2
    Port:
    Environment:        <none>
    Mounts:             <none>
  Volumes:              <none>
Events:
  FirstSeen    LastSeen    Count    From            SubobjectPath    Type        Reason            Message
  ---------    --------    -----    ----            -------------    --------    ------            -------
  33s          33s         1        {job-controller }                Normal      SuccessfulCreate  Created pod: job-wq-2-lglf8

Context: 3 - Fine Parallel Processing Using a Work Queue | You can wait for the Job to succeed, with a timeout:


Prompt:
Explain this text code:

Name:             job-wq-2
Namespace:        default
Selector:         controller-uid=b1c7e4e3-92e1-11e7-b85e-fa163ee3c11f
Labels:           controller-uid=b1c7e4e3-92e1-11e7-b85e-fa163ee3c11f
                  job-name=job-wq-2
Annotations:      <none>
Parallelism:      2
Completions:      <unset>
Start Time:       Mon, 11 Jan 2022 17:07:59 +0000
Pods Statuses:    1 Running / 0 Succeeded / 0 Failed
Pod Template:
  Labels:       controller-uid=b1c7e4e3-92e1-11e7-b85e-fa163ee3c11f
                job-name=job-wq-2
  Containers:
   c:
    Image:              container-registry.example/exampleproject/job-wq-2
    Port:
    Environment:        <none>
    Mounts:             <none>
  Volumes:              <none>
Events:
  FirstSeen    LastSeen    Count    From            SubobjectPath    Type        Reason            Message
  ---------    --------    -----    ----            -------------    --------    ------            -------
  33s          33s         1        {job-controller }                Normal      SuccessfulCreate  Created pod: job-wq-2-lglf8

Response: This text code 3 - Fine Parallel Processing Using a Work Queue | You can wait for the Job to succeed, with a timeout:


Prompt:
Explain this shell code:

# The check for condition name is case insensitive
kubectl wait --for=condition=complete --timeout=300s job/job-wq-2

Response: This shell code 3 - Fine Parallel Processing Using a Work Queue | As you can see, one of the pods for this Job worked on several work units.

Context: 3 - Fine Parallel Processing Using a Work Queue | As you can see, one of the pods for this Job worked on several work units.


Prompt:
Complete this text code:

Worker with sessionID: bbd72d0a-9e5c-4dd6-abf6-416cc267991f
Initial queue state: empty=False

Response:
Working on banana
Working on date
Working on lemon


Prompt:
Explain this text code:

Worker with sessionID: bbd72d0a-9e5c-4dd6-abf6-416cc267991f
Initial queue state: empty=False
Working on banana
Working on date
Working on lemon

Response: This text code 3 - Fine Parallel Processing Using a Work Queue | As you can see, one of the pods for this Job worked on several work units.


Prompt:
Complete this yaml code:

apiVersion: batch/v1
kind: Job
metadata:
  name: 'indexed-job'
spec:
  completions: 5
  parallelism: 3
  completionMode: Indexed
  template:
    spec:
      restartPolicy: Never
      initContainers:
      - name: 'input'
        image: 'docker.io/library/bash'
        command:
        - "bash"
        - "-c"

Response:
        - |
          items=(foo bar baz qux xyz)
          echo ${items[$JOB_COMPLETION_INDEX]} > /input/data.txt
        volumeMounts:
        - mountPath: /input
          name: input
      containers:
      - name: 'worker'
        image: 'docker.io/library/busybox'
        command:
        - "rev"
        - "/input/data.txt"
        volumeMounts:
        - mountPath: /input
          name: input
      volumes:
      - name: input
        emptyDir: {}

Context: 4 - Indexed Job for Parallel Processing with Static Work Assignment | In the example above, you use the builtin JOB_COMPLETION_INDEX environment variable set by the Job controller for all containers. An init container maps the index to a static value and writes it to a


Prompt:
Explain this yaml code:

apiVersion: batch/v1
kind: Job
metadata:
  name: 'indexed-job'
spec:
  completions: 5
  parallelism: 3
  completionMode: Indexed
  template:
    spec:
      restartPolicy: Never
      initContainers:
      - name: 'input'
        image: 'docker.io/library/bash'
        command:
        - "bash"
        - "-c"
        - |
          items=(foo bar baz qux xyz)
          echo ${items[$JOB_COMPLETION_INDEX]} > /input/data.txt
        volumeMounts:
        - mountPath: /input
          name: input
      containers:
      - name: 'worker'
        image: 'docker.io/library/busybox'
        command:
        - "rev"
        - "/input/data.txt"
        volumeMounts:
        - mountPath: /input
          name: input
      volumes:
      - name: input
        emptyDir: {}

Response: This yaml code 4 - Indexed Job for Parallel Processing with Static Work Assignment | In the example above, you use the builtin JOB_COMPLETION_INDEX environment variable set by the Job controller for all containers. An init container maps the index to a static value and writes it to a


Prompt:
Complete this yaml code:

apiVersion: batch/v1
kind: Job
metadata:
  name: 'indexed-job'
spec:
  completions: 5
  parallelism: 3
  completionMode: Indexed
  template:
    spec:
      restartPolicy: Never
      containers:
      - name: 'worker'

Response:
        image: 'docker.io/library/busybox'
        command:
        - "rev"
        - "/input/data.txt"
        volumeMounts:
        - mountPath: /input
          name: input
      volumes:
      - name: input
        downwardAPI:
          items:
          - path: "data.txt"
            fieldRef:
              fieldPath: metadata.annotations['batch.kubernetes.io/job-completion-index']

Context: 4 - Indexed Job for Parallel Processing with Static Work Assignment | Now run the Job:


Prompt:
Explain this yaml code:

apiVersion: batch/v1
kind: Job
metadata:
  name: 'indexed-job'
spec:
  completions: 5
  parallelism: 3
  completionMode: Indexed
  template:
    spec:
      restartPolicy: Never
      containers:
      - name: 'worker'
        image: 'docker.io/library/busybox'
        command:
        - "rev"
        - "/input/data.txt"
        volumeMounts:
        - mountPath: /input
          name: input
      volumes:
      - name: input
        downwardAPI:
          items:
          - path: "data.txt"
            fieldRef:
              fieldPath: metadata.annotations['batch.kubernetes.io/job-completion-index']

Response: This yaml code 4 - Indexed Job for Parallel Processing with Static Work Assignment | Now run the Job:


Prompt:
Explain this shell code:

# This uses the first approach (relying on $JOB_COMPLETION_INDEX)
kubectl apply -f https://kubernetes.io/examples/application/job/indexed-job.yaml

Response: This shell code 4 - Indexed Job for Parallel Processing with Static Work Assignment | When you create this Job, the control plane creates a series of Pods, one for each index you specified. The value of .spec.parallelism determines how many can run at once whereas .spec.completions det

Context: 4 - Indexed Job for Parallel Processing with Static Work Assignment | When you create this Job, the control plane creates a series of Pods, one for each index you specified. The value of .spec.parallelism determines how many can run at once whereas .spec.completions det


Prompt:
Explain this shell code:

# The check for condition name is case insensitive
kubectl wait --for=condition=complete --timeout=300s job/indexed-job

Response: This shell code 4 - Indexed Job for Parallel Processing with Static Work Assignment | Now, describe the Job and check that it was successful.

Context: 4 - Indexed Job for Parallel Processing with Static Work Assignment | Now, describe the Job and check that it was successful.


Prompt:
Complete this text code:

Name:              indexed-job
Namespace:         default
Selector:          controller-uid=bf865e04-0b67-483b-9a90-74cfc4c3e756
Labels:            controller-uid=bf865e04-0b67-483b-9a90-74cfc4c3e756
                   job-name=indexed-job
Annotations:       <none>
Parallelism:       3
Completions:       5
Start Time:        Thu, 11 Mar 2021 15:47:34 +0000
Pods Statuses:     2 Running / 3 Succeeded / 0 Failed
Completed Indexes: 0-2
Pod Template:
  Labels:  controller-uid=bf865e04-0b67-483b-9a90-74cfc4c3e756
           job-name=indexed-job
  Init Containers:
   input:
    Image:      docker.io/library/bash
    Port:       <none>
    Host Port:  <none>
    Command:
      bash
      -c
      items=(foo bar baz qux xyz)
      echo ${items[$JOB_COMPLETION_INDEX]} > /input/data.txt

    Environment:  <none>

Response:
    Mounts:
      /input from input (rw)
  Containers:
   worker:
    Image:      docker.io/library/busybox
    Port:       <none>
    Host Port:  <none>
    Command:
      rev
      /input/data.txt
    Environment:  <none>
    Mounts:
      /input from input (rw)
  Volumes:
   input:
    Type:       EmptyDir (a temporary directory that shares a pod's lifetime)
    Medium:
    SizeLimit:  <unset>
Events:
  Type    Reason            Age   From            Message
  ----    ------            ----  ----            -------
  Normal  SuccessfulCreate  4s    job-controller  Created pod: indexed-job-njkjj
  Normal  SuccessfulCreate  4s    job-controller  Created pod: indexed-job-9kd4h
  Normal  SuccessfulCreate  4s    job-controller  Created pod: indexed-job-qjwsz
  Normal  SuccessfulCreate  1s    job-controller  Created pod: indexed-job-fdhq5
  Normal  SuccessfulCreate  1s    job-controller  Created pod: indexed-job-ncslj

Context: 4 - Indexed Job for Parallel Processing with Static Work Assignment | In this example, you run the Job with custom values for each index. You can inspect the output of one of the pods:


Prompt:
Explain this text code:

Name:              indexed-job
Namespace:         default
Selector:          controller-uid=bf865e04-0b67-483b-9a90-74cfc4c3e756
Labels:            controller-uid=bf865e04-0b67-483b-9a90-74cfc4c3e756
                   job-name=indexed-job
Annotations:       <none>
Parallelism:       3
Completions:       5
Start Time:        Thu, 11 Mar 2021 15:47:34 +0000
Pods Statuses:     2 Running / 3 Succeeded / 0 Failed
Completed Indexes: 0-2
Pod Template:
  Labels:  controller-uid=bf865e04-0b67-483b-9a90-74cfc4c3e756
           job-name=indexed-job
  Init Containers:
   input:
    Image:      docker.io/library/bash
    Port:       <none>
    Host Port:  <none>
    Command:
      bash
      -c
      items=(foo bar baz qux xyz)
      echo ${items[$JOB_COMPLETION_INDEX]} > /input/data.txt

    Environment:  <none>
    Mounts:
      /input from input (rw)
  Containers:
   worker:
    Image:      docker.io/library/busybox
    Port:       <none>
    Host Port:  <none>
    Command:
      rev
      /input/data.txt
    Environment:  <none>
    Mounts:
      /input from input (rw)
  Volumes:
   input:
    Type:       EmptyDir (a temporary directory that shares a pod's lifetime)
    Medium:
    SizeLimit:  <unset>
Events:
  Type    Reason            Age   From            Message
  ----    ------            ----  ----            -------
  Normal  SuccessfulCreate  4s    job-controller  Created pod: indexed-job-njkjj
  Normal  SuccessfulCreate  4s    job-controller  Created pod: indexed-job-9kd4h
  Normal  SuccessfulCreate  4s    job-controller  Created pod: indexed-job-qjwsz
  Normal  SuccessfulCreate  1s    job-controller  Created pod: indexed-job-fdhq5
  Normal  SuccessfulCreate  1s    job-controller  Created pod: indexed-job-ncslj

Response: This text code 4 - Indexed Job for Parallel Processing with Static Work Assignment | In this example, you run the Job with custom values for each index. You can inspect the output of one of the pods:


Prompt:
Explain this shell code:

kubectl logs indexed-job-fdhq5 # Change this to match the name of a Pod from that Job

Response: This shell code 4 - Indexed Job for Parallel Processing with Static Work Assignment | The output is similar to:

Context: 4 - Indexed Job for Parallel Processing with Static Work Assignment | The output is similar to:


Prompt:
Complete this yaml code:

apiVersion: v1
kind: Service
metadata:
  name: headless-svc
spec:
  clusterIP: None # clusterIP must be None to create a headless service
  selector:
    job-name: example-job # must match Job name
---
apiVersion: batch/v1
kind: Job
metadata:
  name: example-job
spec:
  completions: 3
  parallelism: 3
  completionMode: Indexed
  template:
    spec:
      subdomain: headless-svc # has to match Service name
      restartPolicy: Never

Response:
      containers:
      - name: example-workload
        image: bash:latest
        command:
        - bash
        - -c
        - |
          for i in 0 1 2
          do
            gotStatus="-1"
            wantStatus="0"
            while [ $gotStatus -ne $wantStatus ]
            do
              ping -c 1 example-job-${i}.headless-svc > /dev/null 2>&1
              gotStatus=$?
              if [ $gotStatus -ne $wantStatus ]; then
                echo "Failed to ping pod example-job-${i}.headless-svc, retrying in 1 second..."
                sleep 1
              fi
            done
            echo "Successfully pinged pod: example-job-${i}.headless-svc"
          done

Context: 5 - Job with Pod-to-Pod Communication | After applying the example above, reach each other over the network using: <pod-hostname>.<headless-service-name>. You should see output similar to the following:


Prompt:
Explain this yaml code:

apiVersion: v1
kind: Service
metadata:
  name: headless-svc
spec:
  clusterIP: None # clusterIP must be None to create a headless service
  selector:
    job-name: example-job # must match Job name
---
apiVersion: batch/v1
kind: Job
metadata:
  name: example-job
spec:
  completions: 3
  parallelism: 3
  completionMode: Indexed
  template:
    spec:
      subdomain: headless-svc # has to match Service name
      restartPolicy: Never
      containers:
      - name: example-workload
        image: bash:latest
        command:
        - bash
        - -c
        - |
          for i in 0 1 2
          do
            gotStatus="-1"
            wantStatus="0"
            while [ $gotStatus -ne $wantStatus ]
            do
              ping -c 1 example-job-${i}.headless-svc > /dev/null 2>&1
              gotStatus=$?
              if [ $gotStatus -ne $wantStatus ]; then
                echo "Failed to ping pod example-job-${i}.headless-svc, retrying in 1 second..."
                sleep 1
              fi
            done
            echo "Successfully pinged pod: example-job-${i}.headless-svc"
          done

Response: This yaml code 5 - Job with Pod-to-Pod Communication | After applying the example above, reach each other over the network using: <pod-hostname>.<headless-service-name>. You should see output similar to the following:


Prompt:
Complete this text code:

Failed to ping pod example-job-0.headless-svc, retrying in 1 second...
Successfully pinged pod: example-job-0.headless-svc

Response:
Successfully pinged pod: example-job-1.headless-svc
Successfully pinged pod: example-job-2.headless-svc

Context: 5 - Job with Pod-to-Pod Communication | This task demonstrates running multiple Jobs based on a common template. You can use this approach to process batches of work in parallel.


Prompt:
Explain this text code:

Failed to ping pod example-job-0.headless-svc, retrying in 1 second...
Successfully pinged pod: example-job-0.headless-svc
Successfully pinged pod: example-job-1.headless-svc
Successfully pinged pod: example-job-2.headless-svc

Response: This text code 5 - Job with Pod-to-Pod Communication | This task demonstrates running multiple Jobs based on a common template. You can use this approach to process batches of work in parallel.


Prompt:
Complete this yaml code:

apiVersion: batch/v1
kind: Job
metadata:
  name: process-item-$ITEM
  labels:
    jobgroup: jobexample
spec:
  template:
    metadata:

Response:
      name: jobexample
      labels:
        jobgroup: jobexample
    spec:
      containers:
      - name: c
        image: busybox:1.28
        command: ["sh", "-c", "echo Processing item $ITEM && sleep 5"]
      restartPolicy: Never

Context: 6 - Parallel Processing using Expansions | The file you downloaded is not yet a valid Kubernetes manifest. Instead that template is a YAML representation of a Job object with some placeholders that need to be filled in before it can be used. T


Prompt:
Explain this yaml code:

apiVersion: batch/v1
kind: Job
metadata:
  name: process-item-$ITEM
  labels:
    jobgroup: jobexample
spec:
  template:
    metadata:
      name: jobexample
      labels:
        jobgroup: jobexample
    spec:
      containers:
      - name: c
        image: busybox:1.28
        command: ["sh", "-c", "echo Processing item $ITEM && sleep 5"]
      restartPolicy: Never

Response: This yaml code 6 - Parallel Processing using Expansions | The file you downloaded is not yet a valid Kubernetes manifest. Instead that template is a YAML representation of a Job object with some placeholders that need to be filled in before it can be used. T


Prompt:
Explain this shell code:

# Use curl to download job-tmpl.yaml
curl -L -s -O https://k8s.io/examples/application/job/job-tmpl.yaml

Response: This shell code 6 - Parallel Processing using Expansions | The file you downloaded is not yet a valid Kubernetes manifest. Instead that template is a YAML representation of a Job object with some placeholders that need to be filled in before it can be used. T


Prompt:
Complete this shell code:

# Expand the template into multiple files, one for each item to be processed.
mkdir ./jobs
for i in apple banana cherry

Response:
do
  cat job-tmpl.yaml | sed "s/\$ITEM/$i/" > ./jobs/job-$i.yaml
done

Context: 6 - Parallel Processing using Expansions | Check if it worked:


Prompt:
Explain this shell code:

# Expand the template into multiple files, one for each item to be processed.
mkdir ./jobs
for i in apple banana cherry
do
  cat job-tmpl.yaml | sed "s/\$ITEM/$i/" > ./jobs/job-$i.yaml
done

Response: This shell code 6 - Parallel Processing using Expansions | Check if it worked:


Prompt:
Explain this text code:

job.batch/process-item-apple created
job.batch/process-item-banana created
job.batch/process-item-cherry created

Response: This text code 6 - Parallel Processing using Expansions | Now, check on the jobs:

Context: 6 - Parallel Processing using Expansions | Now, check on the jobs:


Prompt:
Complete this text code:

NAME                  COMPLETIONS   DURATION   AGE
process-item-apple    1/1           14s        22s

Response:
process-item-banana   1/1           12s        21s
process-item-cherry   1/1           12s        20s

Context: 6 - Parallel Processing using Expansions | Using the -l option to kubectl selects only the Jobs that are part of this group of jobs (there might be other unrelated jobs in the system).


Prompt:
Explain this text code:

NAME                  COMPLETIONS   DURATION   AGE
process-item-apple    1/1           14s        22s
process-item-banana   1/1           12s        21s
process-item-cherry   1/1           12s        20s

Response: This text code 6 - Parallel Processing using Expansions | Using the -l option to kubectl selects only the Jobs that are part of this group of jobs (there might be other unrelated jobs in the system).


Prompt:
Complete this text code:

NAME                        READY     STATUS      RESTARTS   AGE
process-item-apple-kixwv    0/1       Completed   0          4m

Response:
process-item-banana-wrsf7   0/1       Completed   0          4m
process-item-cherry-dnfu9   0/1       Completed   0          4m

Context: 6 - Parallel Processing using Expansions | We can use this single command to check on the output of all jobs at once:


Prompt:
Explain this text code:

NAME                        READY     STATUS      RESTARTS   AGE
process-item-apple-kixwv    0/1       Completed   0          4m
process-item-banana-wrsf7   0/1       Completed   0          4m
process-item-cherry-dnfu9   0/1       Completed   0          4m

Response: This text code 6 - Parallel Processing using Expansions | We can use this single command to check on the output of all jobs at once:


Prompt:
Explain this text code:

Processing item apple
Processing item banana
Processing item cherry

Response: This text code 6 - Parallel Processing using Expansions | In the first example, each instance of the template had one parameter, and that parameter was also used in the Job's name. However, names are restricted to contain only certain characters.

Context: 6 - Parallel Processing using Expansions | In the first example, each instance of the template had one parameter, and that parameter was also used in the Job's name. However, names are restricted to contain only certain characters.


Prompt:
Explain this shell code:

# Remove the Jobs you created
# Your cluster automatically cleans up their Pods
kubectl delete job -l jobgroup=jobexample

Response: This shell code 6 - Parallel Processing using Expansions | In the first example, each instance of the template had one parameter, and that parameter was also used in the Job's name. However, names are restricted to contain only certain characters.


Prompt:
Complete this liquid code:

{% set params = [{ "name": "apple", "url": "http://dbpedia.org/resource/Apple", },
                  { "name": "banana", "url": "http://dbpedia.org/resource/Banana", },
                  { "name": "cherry", "url": "http://dbpedia.org/resource/Cherry" }]
%}
{% for p in params %}
{% set name = p["name"] %}
{% set url = p["url"] %}
---
apiVersion: batch/v1
kind: Job
metadata:
  name: jobexample-{{ name }}
  labels:

Response:
    jobgroup: jobexample
spec:
  template:
    metadata:
      name: jobexample
      labels:
        jobgroup: jobexample
    spec:
      containers:
      - name: c
        image: busybox:1.28
        command: ["sh", "-c", "echo Processing URL {{ url }} && sleep 5"]
      restartPolicy: Never
{% endfor %}

Context: 6 - Parallel Processing using Expansions | The above template defines two parameters for each Job object using a list of python dicts (lines 1-4). A for loop emits one Job manifest for each set of parameters (remaining lines).


Prompt:
Explain this liquid code:

{% set params = [{ "name": "apple", "url": "http://dbpedia.org/resource/Apple", },
                  { "name": "banana", "url": "http://dbpedia.org/resource/Banana", },
                  { "name": "cherry", "url": "http://dbpedia.org/resource/Cherry" }]
%}
{% for p in params %}
{% set name = p["name"] %}
{% set url = p["url"] %}
---
apiVersion: batch/v1
kind: Job
metadata:
  name: jobexample-{{ name }}
  labels:
    jobgroup: jobexample
spec:
  template:
    metadata:
      name: jobexample
      labels:
        jobgroup: jobexample
    spec:
      containers:
      - name: c
        image: busybox:1.28
        command: ["sh", "-c", "echo Processing URL {{ url }} && sleep 5"]
      restartPolicy: Never
{% endfor %}

Response: This liquid code 6 - Parallel Processing using Expansions | The above template defines two parameters for each Job object using a list of python dicts (lines 1-4). A for loop emits one Job manifest for each set of parameters (remaining lines).


Prompt:
Explain this shell code:

alias render_template='python -c "from jinja2 import Template; import sys; print(Template(sys.stdin.read()).render());"'

Response: This shell code 6 - Parallel Processing using Expansions | Use render_template to convert the parameters and template into a single YAML file containing Kubernetes manifests:

Context: 6 - Parallel Processing using Expansions | Use render_template to convert the parameters and template into a single YAML file containing Kubernetes manifests:


Prompt:
Explain this shell code:

# This requires the alias you defined earlier
cat job.yaml.jinja2 | render_template > jobs.yaml

Response: This shell code 6 - Parallel Processing using Expansions | You can view jobs.yaml to verify that the render_template script worked correctly.

Context: 6 - Parallel Processing using Expansions | You can view jobs.yaml to verify that the render_template script worked correctly.


Prompt:
Explain this shell code:

cat job.yaml.jinja2 | render_template | kubectl apply -f -

Response: This shell code 6 - Parallel Processing using Expansions | Kubernetes accepts and runs the Jobs you created.

Context: 6 - Parallel Processing using Expansions | Kubernetes accepts and runs the Jobs you created.


Prompt:
Explain this shell code:

# Remove the Jobs you created
# Your cluster automatically cleans up their Pods
kubectl delete job -l jobgroup=jobexample

Response: This shell code 6 - Parallel Processing using Expansions | In a real use case, each Job performs some substantial computation, such as rendering a frame of a movie, or processing a range of rows in a database. If you were rendering a movie you would set $ITEM

Context: 6 - Parallel Processing using Expansions | In a real use case, each Job performs some substantial computation, such as rendering a frame of a movie, or processing a range of rows in a database. If you were rendering a movie you would set $ITEM


Prompt:
Complete this yaml code:

apiVersion: batch/v1
kind: Job
metadata:
  name: job-pod-failure-policy-failjob
spec:
  completions: 8
  parallelism: 2
  template:
    spec:
      restartPolicy: Never
      containers:
      - name: main

Response:
        image: docker.io/library/bash:5
        command: ["bash"]
        args:
        - -c
        - echo "Hello world! I'm going to exit with 42 to simulate a software bug." && sleep 30 && exit 42
  backoffLimit: 6
  podFailurePolicy:
    rules:
    - action: FailJob
      onExitCodes:
        containerName: main
        operator: In
        values: [42]

Context: 7 - Handling retriable and non-retriable pod failures with Pod failure policy | Apply the manifest:


Prompt:
Explain this yaml code:

apiVersion: batch/v1
kind: Job
metadata:
  name: job-pod-failure-policy-failjob
spec:
  completions: 8
  parallelism: 2
  template:
    spec:
      restartPolicy: Never
      containers:
      - name: main
        image: docker.io/library/bash:5
        command: ["bash"]
        args:
        - -c
        - echo "Hello world! I'm going to exit with 42 to simulate a software bug." && sleep 30 && exit 42
  backoffLimit: 6
  podFailurePolicy:
    rules:
    - action: FailJob
      onExitCodes:
        containerName: main
        operator: In
        values: [42]

Response: This yaml code 7 - Handling retriable and non-retriable pod failures with Pod failure policy | Apply the manifest:


Prompt:
Explain this sh code:

kubectl create -f https://k8s.io/examples/controllers/job-pod-failure-policy-failjob.yaml

Response: This sh code 7 - Handling retriable and non-retriable pod failures with Pod failure policy | After around 30 seconds the entire Job should be terminated. Inspect the status of the Job by running:

Context: 7 - Handling retriable and non-retriable pod failures with Pod failure policy | After around 30 seconds the entire Job should be terminated. Inspect the status of the Job by running: