This page explains how to run Jobs in Google Kubernetes Engine (GKE).
Overview
In GKE, a Job is a controller object that represents afinite task. Jobs differ from other controller objects in that Jobs manage thetask as it runs to completion, rather than managing an ongoing desired state(such as the total number of running Pods).
Jobs are useful for large computation and batch-oriented tasks. Jobs can be usedto support parallel execution of Pods. You can use a Job to run independent butrelated work items in parallel: sending emails, rendering frames, transcodingfiles, scanning database keys, etc. However, Jobs are not designed forclosely-communicating parallel processes such as continuous streams ofbackground processes.
In GKE, there are two types of Jobs:
- Non-parallel Job: A Job which creates only one Pod (which is re-created ifthe Pod terminates unsuccessfully), and which is completed when the Podterminates successfully.
- Parallel jobs with a completion count: A Job that is completed when acertain number of Pods terminate successfully. You specify the desired numberof completions using the
completionsfield.
Jobs are represented by Kubernetes Job objects. When a Jobis created, the Job controller creates one or more Pods and ensures that itsPods terminate successfully. As its Pods terminate, a Job tracks how many Podscompleted their tasks successfully. Once the desired number of successfulcompletions is reached, the Job is complete.
Similar to other controllers, a Job controller creates a new Pod if one of itsPods fails or is deleted.
Before you begin
Before you start, make sure you have performed the following tasks:
- Enable the Google Kubernetes Engine API. Enable Google Kubernetes Engine API
- If you want to use the Google Cloud CLI for this task, install and then initialize the gcloud CLI.
Creating a Job
You can create a Job usingkubectl apply with a manifest file.
The following example shows a Job manifest:
apiVersion: batch/v1kind: Jobmetadata: # Unique key of the Job instance name: example-jobspec: template: metadata: name: example-job spec: containers: - name: pi image: perl command: ["perl"] args: ["-Mbignum=bpi", "-wle", "print bpi(2000)"] # Do not restart containers after they exit restartPolicy: Never # of retries before marking as failed. backoffLimit: 4Copy the manifest to a file named config.yaml, and create the Job:
kubectl apply -f config.yamlThis Job computes pi to 2000 places then prints it.
The only requirement for a Job object is that the Pod template field ismandatory.
Job completion count
A Job is completed when a specific number of Pods terminate successfully. Bydefault, a non-parallel Job with a single Pod completes as soon as the Podterminates successfully.
If you have a parallel Job, you can set a completion count using the optionalcompletions field. This field specifies how many Pods should terminatesuccessfully before the Job is complete. The completions field accepts anon-zero, positive value.
Omitting completions or specifying a zero value causes the success of anyPod to signal the success of all Pods.
Copy config.yaml from the preceding example to a file named config-2.yaml.In config-2.yaml, change name to example-job-2, and add completions: 8to the Job's spec field. This specifies that there should be eight successfulcompletions:
apiVersion: batch/v1kind: Jobmetadata: name: example-job-2spec: completions: 8 template: metadata: name: example-job-2 spec: ...Create the Job:
kubectl apply -f config-2.yamlThe default value of completions is 1. When completions is set, theparallelism field defaults to 1 unless set otherwise. If both fields are notset, their default values are 1.
Managing parallelism
By default, Job Pods do not run in parallel. The optional parallelism fieldspecifies the maximum desired number of Pods a Job should run concurrently atany given time.
The actual number of Pods running in a steady state might be less than theparallelism value if the remaining work is less than the parallelismvalue. If you have also set completions, the actual number of Pods running inparallel does not exceed the number of remaining completions. A Job maythrottle Pod creation in response to excessive Pod creation failure.
Copy config.yaml from the preceding example to a file named config-3.yaml.In config-3.yaml, change name to example-job-3, and add parallelism: 5to the Job's spec field. This specifies that there should be five concurrentPods running:
apiVersion: batch/v1kind: Jobmetadata: name: example-job-3spec: parallelism: 5 template: metadata: name: example-job-3 spec: ...Create the Job:
kubectl apply -f config-3.yamlThe default value of parallelism is 1 if the field if omitted or unless setotherwise. If the value is set to 0, the Job is paused until the value isincreased.
Specifying retries
By default, a Job runs uninterrupted unless there is a failure, at which pointthe Job defers to the backoffLimit. The backoffLimit field specifies thenumber of retries before marking the job as failed; the default value is 6. Thenumber of retries applies per Pod, not globally. This means that if multiplePods fail (when parallelism is greater than 1), the job continues to run untila single Pod fails backoffLimit of times. Once the backoffLimit has beenreached, the Job is marked as failed and any running Pods will beterminated.
For example, in our example job, we set the number of retries to 4:
apiVersion: batch/v1kind: Jobmetadata: name: example-jobspec: template: metadata: name: example-job spec: containers: ... backoffLimit: 4Pod replacement
Job recreates Pods honoring the backoffLimit when the current Pod isconsideredfailed in scenarios such as:
- The Pod container exits with a non-zero error code.
- When a Node is rebooted, the kubelet may mark the Pod as
Failedafter the reboot
Under certain scenarios a Job that has not completed replaces the Pod withoutconsidering the backoffLimit, such as:
- Manually killing a Pod would not set the Pod phase to
Failed. The replacement Pod may be created even before the current pod's termination grace period is completed. - When a Node is drained (manually or during auto-upgrade), the Pod is terminated honoring a drain grace period and is replaced.
- When a Node is deleted, the Pod is garbage collected (marked as deleted) and is replaced.
Specifying a deadline
By default, a Job creates new Pods forever if its Pods fail continuously. If youprefer not to have a Job retry forever, you can specify a deadline value usingthe optional .spec.activeDeadlineSeconds field of the Job.
A deadline grants a Job a specific amount of time, in seconds, to complete itstasks successfully before terminating. The activeDeadlineSeconds value isrelative to the startTime of the Job, and applies to the duration of the Job,no matter how many Pods are created.
To specify a deadline, add the activeDeadlineSeconds value to the Job'sspec field in the manifest file. For example, the followingconfiguration specifies that the Job has 100 seconds to complete successfully:
apiVersion: batch/v1kind: Jobmetadata: name: example-jobspec: activeDeadlineSeconds: 100 template: metadata: name: example-job spec: ...If a Job does not complete successfully before the deadline, the Job ends withthe status DeadlineExceeded. This causes the creation of Pods to stop and causesexisting Pods to be deleted.
Specifying a Pod selector
Manually specifying a selector is useful if you want to update a Job's Podtemplate, but you want the Job's current Pods to run under the updated Job.
A Job is instantiated with a selector field. The selector generates a uniqueidentifier for the Job's Pods. The generated ID does not overlap with any otherJobs. Generally, you would not set this field yourself: setting a selectorvalue which overlaps with another Job can cause issues with Pods in the otherJob. To set the field yourself, you must specify manualSelector: True in theJob's spec field.
For example, you can run kubectl get job my-job --output=yaml to see the Job'sspecification, which contains the selector generated for its Pods:
kind: Jobmetadata: name: my-job...spec: completions: 1 parallelism: 1 selector: matchLabels: controller-uid: a8f3d00d-c6d2-11e5-9f87-42010af00002...When you create a new Job, you can set the manualSelector value to True,then set the selector field's job-uid value like the following:
kind: Jobmetadata: name: my-new-job ...spec: manualSelector: true selector: matchLabels: controller-uid: a8f3d00d-c6d2-11e5-9f87-42010af00002 ...Pods created by my-new-job use the previous Pod UID.
Inspecting a Job
kubectl
To check a Job's status, run the following command:
kubectl describe job my-jobTo view all Pod resources in your cluster, including Pods created by the Jobwhich have completed, run:
kubectl get pods -aThe -a flag specifies that all resources of the type specified (in this case,Pods) should be shown.
Console
After creating a Job using kubectl, you can inspect it by performing thefollowing steps:
Go to the Workloads page in the Google Cloud console.
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In the workloads list, click the name of the Job you want to inspect.
(Video) Top 3 ways to run your containers on Google CloudOn the Job details page, do any of the following:
- Click the Revision History tab to see the Job's revision history.
- Click the Events tab to see all events related to the Job.
- Click the Logs tab to see all container logs related to the Job.
- Click the YAML tab to see, copy, and download the Job's live configuration.
Deleting a Job
When a Job completes, the Job stops creating Pods. The Job API object is notremoved when it completes, which allows you to view its status. Pods createdby the Job are not deleted, but they are terminated. Retention of the Podsallows you to view their logs and to interact with them.
kubectl
To delete a Job, run the following command:
kubectl delete job my-jobWhen you delete a Job, all of its Pods are also deleted.
To delete a Job but retain its Pods, specify the --cascade false flag:
kubectl delete jobs my-job --cascade falseConsole
To delete a Job, perform the following steps:
Go to the Workloads page in the Google Cloud console.
Go to Workloads
In the workloads list, select one or more Jobs you want to delete.
Click delete Delete.
(Video) Running Dedicated Game Servers in Google Kubernetes Engine || [GSP133] || solutionWhen prompted to confirm, click Delete.
What's next
FAQs
What is Google Kubernetes engine GKE select correct answer? ›
Google Kubernetes Engine (GKE) provides a managed environment for deploying, managing, and scaling your containerized applications using Google infrastructure. The GKE environment consists of multiple machines (specifically, Compute Engine instances) grouped together to form a cluster.
How do I manually run a Kubernetes job? ›To manually run a CronJob as a Job you run the kubectl create job command. You then specify the CronJob to base the job off of using the --from flag. Lastly, you specify a unique name for the job.
Which of the following is an advantage of running a Google Kubernetes engine cluster? ›It provides an environment where you can seamlessly interact with your container cluster. With Kubernetes flexible resources and commands, you can execute automated deployment and management of your applications, set policies, carry out administrative tasks, and closely monitor your deployed workload.
When you run a Kubernetes engine cluster on Google Cloud Platform you gain the benefit of advanced cluster management features that includes? ›Source: Google Cloud 2018a. When you use the GKE to setup a cluster, you also gain the benefit of advanced cluster management features that Google Cloud Platform provides. These include: Leverage CI / CD tools in GCP to help you build and serve application containers.
How do I deploy an application in Google Kubernetes engine? ›- Sign in to your Google Cloud account. ...
- In the Google Cloud console, on the project selector page, select or create a Google Cloud project. ...
- Make sure that billing is enabled for your Cloud project. ...
- Enable the Artifact Registry and Google Kubernetes Engine APIs.
Q10. What is Google Container Engine? Google Container Engine (GKE) is an open-source management platform for Docker containers and clusters. This Kubernetes based engine supports only those clusters which run within Google's public cloud services.
How do I run a batch job in Kubernetes? ›To execute and manage a batch task on your cluster, you can use a Kubernetes Job. You can specify the maximum number of Pods that should run in parallel as well as the number of Pods that should complete their tasks before the Job is finished. A Job can also be used to run multiple Pods at the same time.
How do you trigger a Kubernetes job? ›- Step 1 - Define the job. ...
- Step 2 - Working with CronJobs. ...
- Step 3 - Define the application that will run. ...
- Step 4 - Deploy the app on Kubernetes.
Setting up a local Kubernetes environment as your development environment is the recommended option, no matter your situation, because this setup can create a safe and agile application-deployment process.
What is the biggest disadvantage of Kubernetes? ›Thus, the complexity of Kubernetes can be a barrier to adoption for many startups. Kubernetes not only complicates the work of IT teams, but it is also rather expensive. Most startups do not need containerized application management – this is more about large developments of complex systems.
Is Kubernetes a valuable skill? ›
All in all, Kubernetes is one of those promising technologies which can boost your career prospects in the years to come. So, if you are someone who would like to get into a dynamic job with a hefty paycheck, then your best bet would be to add Kubernetes to your technology portfolio.
How many nodes can a cluster have in GKE? ›| Limits | GKE Standard cluster |
|---|---|
| Nodes per cluster | 15,000 Note: If you plan to run more than 2,000 nodes, use a regional cluster. Note: Running more than 5,000 nodes requires lifting a cluster size quota. Contact support for assistance. |
| Nodes per node pool zone | 1,000 |
GKE now offers two modes of operations: Autopilot and Standard. Autopilot mode is a hands-off, fully managed solution that manages your entire cluster's infrastructure without worrying about configuring and monitoring, while still delivering a complete Kubernetes experience.
Which service must you enable on your GKE cluster in order to use cloud run on GKE? ›Create a Google Cloud Platform (GCP) project, or use an existing one. Enable the Cloud Run API. Enable the Container Registry API. Enable the Kubernetes Engine API.
What is a difference between Google App Engine and Kubernetes engine? ›Kubernetes is a production grade open-source container orchestration service for automating deployment, scaling and managing containerized workloads and services. Google App Engine is a managed service by Google Cloud Platform for build and run applications in the form of containers.
Is Google Kubernetes engine IaaS or PaaS? ›Kubernetes is neither IaaS nor PaaS. It's a container orchestration engine which makes it more like a Container As A Service or CaaS. You need a IaaS layer below kubernetes to provide it VMs like for example AWS EC2 or bare metal servers.
How do I run an application in Kubernetes? ›To run an application in a cluster, you have to pack our app into a container, then create Docker image from the container and finally send it to the Docker registry. After that, you need to define which image should be installed on Kubernetes node. Kubernetes uses a mechanism called Pod to manage containers.
How is GKE different from Kubernetes? ›In short Kubernetes does the orchestration, the rest are services that would run on top of Kubernetes. GKE brings you all these components out-of-the-box, and you don't have to maintain them. They're setup for you, and they're more 'integrated' with the Google portal.
What is the difference between cloud run and GKE? ›GKE will give you complete control over orchestration of containers, from networking to storage. However, if your application doesn't need that control over orchestration of containers, then fully managed Cloud Run will be the correct solution for you. Cloud Run makes it easy to build serverless HTTP applications.
What does GKE stand for? ›Google Kubernetes Engine (GKE) is a management and orchestration system for Docker container and container clusters that run within Google's public cloud services.
How much do Kubernetes admins make? ›
How much does a Kubernetes Administrator make? As of Nov 29, 2022, the average annual pay for a Kubernetes Administrator in the United States is $130,287 a year. Just in case you need a simple salary calculator, that works out to be approximately $62.64 an hour. This is the equivalent of $2,505/week or $10,857/month.
Is Kubernetes good for batch processing? ›The differences between batch and microservice workloads mean that using Kubernetes for batch processing can be difficult and requires you to invest significant time in custom configuration and management to fine-tune a suitable solution.
How do I run a batch job manually? ›- To run the batch job manually, click. Run Now. .
- To run the batch job automatically, click. Run automatically. . CC360. disables the. Run Now. button and hides the schedule list and the. Update Schedule. buttons. ...
- To schedule the batch job, select a schedule from the list and click. Update Schedule. .
If you add in lab time, reading, and exploring different ways to utilize Kubernetes, around 20 hours is a good enough timeframe to expect you'll be able to start working with Kubernetes in a work environment.
How do I know if Kubernetes failed my job? ›...
One other approach:
- kubectl describe job $JOB.
- Pod name is shown under "Events"
- kubectl logs $POD.
DevOps Kubernetes jobs can actually be a great way to kickstart your career. As a DevOps engineer, you shall be responsible for the management and deployment of software changes using Kubernetes. Infact Civo Kubernetes Salary for DevOps engineers is greatly promising, making it one of the leading career prospects.
How much RAM do I need for Kubernetes? ›A minimum Kubernetes master node configuration is: 4 CPU cores (Intel VT-capable CPU) 16GB RAM.
Can we use Kubernetes without cloud? ›Kubernetes has achieved an unprecedented adoption rate, due in part to the fact that it substantially simplifies the deployment and management of microservices. Almost equally important is that it allows users who are unable to utilize the public cloud to operate in a “cloud-like” environment.
Why is K8s so hard? ›With many moving parts in terms of concepts, subsystems, processes, machines and code, Kubernetes is prone to mistakes. Plus, any change to the environment or mistake requires developers to refactor the code.
Is Kubernetes an in demand skill? ›There is high demand for Kubernetes skills
As more and more companies move to containerized environments, the demand for Kubernetes skills is skyrocketing. If you want to get ahead of the curve, pursuing a career in Kubernetes is a great way to do it.
Is there anything better than Kubernetes? ›
Lightweight container orchestrators—Kubernetes is the most popular container orchestrator, but is definitely not the only one. Docker Swarm and Nomad are two examples of capable, mature orchestrators, which are much less complex to use and maintain than Kubernetes.
Which platform is best for Kubernetes? ›- Google Cloud Platform. Whether you are new to the Google Cloud Platform, or an existing customer, Google will provide you with a $300 credit towards using the Google Kubernetes Engine for up to 90 days. ...
- IBM Cloud. ...
- MS Azure.
As of Nov 29, 2022, the average annual pay for a Kubernetes in the United States is $151,304 a year.
Is Kubernetes worth learning 2022? ›You need to learn Kubernetes if it is related to your work in any way, whether it's creating containerized applications, managing and deploying, or maintaining a containerized environment. If you are a practitioner, there is a high likelihood that you will encounter K8s in some form or another.
How many people are Kubernetes certified? ›In January 2020, the CNCF announced 5,300 individuals had registered for the CKAD exam and since its creation in May 2018. However, only 2,400 had achieved the certification - so about 45% - which is very few for a professional certification.
What skills are needed for Kubernetes? ›- AI-Driven Event & Incident Management. Intelligent Automation. Hybrid Observability.
- By Capabilities. Event & Incident Management. Remediation & Automation. Hybrid Observability. Platform. Integrations. Security.
- AIOps. Tools Consolidation and Modernization. Cloud Migration. ITOM as a Service.
Your business might be a small startup right now but you want it to grow. If so, you certainly fall into Kubernetes, the powerful container-orchestration system that is perfect for any project that needs to scale quickly.
Is Kubernetes easier than Docker? ›Docker Swarm typically requires less setup and configuration than Kubernetes if you're building and running your own infrastructure.
How many pods do you need for a host? ›About default maximum Pods per node. By default, GKE allows up to 110 Pods per node on Standard clusters, however Standard clusters can be configured to allow up to 256 Pods per node. Autopilot clusters have a maximum of 32 Pods per node.
How many Kubernetes pods do I need? ›More specifically, Kubernetes is designed to accommodate configurations that meet all of the following criteria: No more than 110 pods per node. No more than 5000 nodes.
How long does it take to create a GKE cluster? ›
Note, provisioning a new GKE cluster takes between 3-5 minutes.
How do I run cloud on GKE? ›Deploy to Cloud Run on GKE. To deploy a container to the cluster you just created, go to Navigation menu > Anthos > Cloud Run for Anthos. Click Create service.
How do I deploy an application on GKE? ›- Make sure your Kubernetes resource file is referring to the correct container image tag or digest.
- Add the gke-deploy step in your build configuration file: YAML JSON. ...
- Start your build:
While App Engine supports many different services within a single application, Cloud Functions support individualized services. It's an important detail when comparing Google App Engine vs Cloud Functions. If your requirements don't include multiple services then Cloud Functions is a great choice.
Why should I use GKE? ›GKE gives you complete control over every aspect of container orchestration, from networking, to storage, to how you set up observability—in addition to supporting stateful application use cases.
Should I use GKE? ›If you have a fair amount of experience managing the data plane of a Kubernetes environment and you would like to maintain control of resource consumption and maintain a certain level of stability in your system, then standard GKE would be a good choice.
What is the use of Google Kubernetes engine Mcq? ›Google Kubernetes Engine is based on Kubernetes, Google's open source container management system. Organizations typically use Google Kubernetes Engine to: Create or resize Docker container clusters. Create container pods, replication controllers, jobs, services or load balancers.
What is App Engine select the correct answer? ›An App Engine app is made up of a single application resource that consists of one or more services. Each service can be configured to use different runtimes and to operate with different performance settings. Within each service, you deploy versions of that service.
What type of service is Google Kubernetes engine? ›What is a Kubernetes Service? The idea of a Service is to group a set of Pod endpoints into a single resource. You can configure various ways to access the grouping. By default, you get a stable cluster IP address that clients inside the cluster can use to contact Pods in the Service.
What is the difference between Kubernetes and Google Kubernetes engine? ›Kubernetes is a production grade open-source container orchestration service for automating deployment, scaling and managing containerized workloads and services. Google App Engine is a managed service by Google Cloud Platform for build and run applications in the form of containers.
What is the difference between Kubernetes and GKE? ›
In short Kubernetes does the orchestration, the rest are services that would run on top of Kubernetes. GKE brings you all these components out-of-the-box, and you don't have to maintain them. They're setup for you, and they're more 'integrated' with the Google portal.
Is Kubernetes DevOps or cloud? ›Kubernetes is the most popular container orchestration platform, and has become an essential tool for DevOps teams. Application teams can now deploy containerized applications to Kubernetes clusters, which can run either on-premises or in a cloud environment.
Is Kubernetes AWS or Azure? ›Two of the biggest providers of managed Kubernetes services are Amazon Elastic Kubernetes Service (EKS) and Azure Kubernetes Services (AKS). Added to AWS in 2018, EKS is a managed Kubernetes service that simplifies running Kubernetes on AWS or on-premises by providing a control plane and nodes.
When should I use cloud or App Engine? ›While App Engine supports many different services within a single application, Cloud Functions support individualized services. It's an important detail when comparing Google App Engine vs Cloud Functions. If your requirements don't include multiple services then Cloud Functions is a great choice.
What are the disadvantages of Google App Engine? ›- Locked into Google App Engine ?
- Developers have read-only access to the filesystem on App Engine.
- App Engine can only execute code called from an HTTP request (except for scheduled background tasks).
- Users may upload arbitrary Python modules, but only if they are pure-Python; C and Pyrex modules are not supported.
Compute Engine delivers configurable virtual machines running in Google's data centers with access to high-performance networking infrastructure and block storage solutions. App Engine is a fully managed, serverless platform for developing and hosting web applications at scale.
Is Google App Engine a cloud service? ›App Engine is a fully managed, serverless platform for developing and hosting web applications at scale. You can choose from several popular languages, libraries, and frameworks to develop your apps, and then let App Engine take care of provisioning servers and scaling your app instances based on demand.
Is GKE PaaS or SAAS? ›Platform as a service (PaaS) layers like GKE fall somewhere in the middle, hence the ambiguity that arises.
Is Google Kubernetes engine free? ›The GKE free tier provides $74.40 in monthly credits per billing account that are applied to zonal and Autopilot clusters. If you only use a single Zonal or Autopilot cluster, this credit will at least cover the complete cost of that cluster each month.