Question: How does Image Policy API (v1alpha1) work?

Answer: Image Policy API (v1alpha1)Resource TypesImageReviewImageReviewImageReview checks if the set of images in a pod are allowed.FieldDescriptionapiVersionstringimagepolicy.k8s.io/v1alpha1kindstringImageReviewmetadatameta/v1.ObjectMetaStandard object's metadata. More info: https://git.k8s.io/community/contributors/devel/sig-architecture/api-conventions.md#metadataRefer to the Kubernetes API documentation for the fields of the metadata field.spec [Required]ImageReviewSpecSpec holds information about the pod being evaluatedstatusImageReviewStatusStatus is filled in by the backend and indicates whether the pod should be allowed.ImageReviewContainerSpecAppears in:ImageReviewSpecImageReviewContainerSpec is a description of a container within the pod creation request.FieldDescriptionimagestringThis can be in the form image:tag or image@SHA:012345679abcdef.ImageReviewSpecAppears in:ImageReviewImageReviewSpec is a description of the pod creation request.FieldDescriptioncontainers[]ImageReviewContainerSpecContainers is a list of a subset of the information in each container of the Pod being created.annotationsmap[string]stringAnnotations is a list of key-value pairs extracted from the Pod's annotations. It only includes keys which match the pattern *.image-policy.k8s.io/*. It is up to each webhook backend to determine how to interpret these annotations, if at all.namespacestringNamespace is the namespace the pod is being created in.ImageReviewStatusAppears in:ImageReviewImageReviewStatus is the result of the review for the pod creation request.FieldDescriptionallowed [Required]boolAllowed indicates that all images were allowed to be run.reasonstringReason should be empty unless Allowed is false in which case it may contain a short description of what is wrong. Kubernetes may truncate excessively long errors when displaying to the user.auditAnnotationsmap[string]stringAuditAnnotations will be added to the attributes object of the admission controller request using 'AddAnnotation'. The keys should be prefix-less (i.e., the admission controller will add an appropriate prefix).This page is automatically generated.If you plan to report an issue with this page, mention that the page is auto-generated in your issue description. The fix may need to happen elsewhere in the Kubernetes project.


Question: When would you use Image Policy API (v1alpha1)?

Answer: Image Policy API (v1alpha1)Resource TypesImageReviewImageReviewImageReview checks if the set of images in a pod are allowed.FieldDescriptionapiVersionstringimagepolicy.k8s.io/v1alpha1kindstringImageReviewmetadatameta/v1.ObjectMetaStandard object's metadata. More info: https://git.k8s.io/community/contributors/devel/sig-architecture/api-conventions.md#metadataRefer to the Kubernetes API documentation for the fields of the metadata field.spec [Required]ImageReviewSpecSpec holds information about the pod being evaluatedstatusImageReviewStatusStatus is filled in by the backend and indicates whether the pod should be allowed.ImageReviewContainerSpecAppears in:ImageReviewSpecImageReviewContainerSpec is a description of a container within the pod creation request.FieldDescriptionimagestringThis can be in the form image:tag or image@SHA:012345679abcdef.ImageReviewSpecAppears in:ImageReviewImageReviewSpec is a description of the pod creation request.FieldDescriptioncontainers[]ImageReviewContainerSpecContainers is a list of a subset of the information in each container of the Pod being created.annotationsmap[string]stringAnnotations is a list of key-value pairs extracted from the Pod's annotations. It only includes keys which match the pattern *.image-policy.k8s.io/*. It is up to each webhook backend to determine how to interpret these annotations, if at all.namespacestringNamespace is the namespace the pod is being created in.ImageReviewStatusAppears in:ImageReviewImageReviewStatus is the result of the review for the pod creation request.FieldDescriptionallowed [Required]boolAllowed indicates that all images were allowed to be run.reasonstringReason should be empty unless Allowed is false in which case it may contain a short description of what is wrong. Kubernetes may truncate excessively long errors when displaying to the user.auditAnnotationsmap[string]stringAuditAnnotations will be added to the attributes object of the admission controller request using 'AddAnnotation'. The keys should be prefix-less (i.e., the admission controller will add an appropriate prefix).This page is automatically generated.If you plan to report an issue with this page, mention that the page is auto-generated in your issue description. The fix may need to happen elsewhere in the Kubernetes project.


Question: What are the benefits of Image Policy API (v1alpha1)?

Answer: Image Policy API (v1alpha1)Resource TypesImageReviewImageReviewImageReview checks if the set of images in a pod are allowed.FieldDescriptionapiVersionstringimagepolicy.k8s.io/v1alpha1kindstringImageReviewmetadatameta/v1.ObjectMetaStandard object's metadata. More info: https://git.k8s.io/community/contributors/devel/sig-architecture/api-conventions.md#metadataRefer to the Kubernetes API documentation for the fields of the metadata field.spec [Required]ImageReviewSpecSpec holds information about the pod being evaluatedstatusImageReviewStatusStatus is filled in by the backend and indicates whether the pod should be allowed.ImageReviewContainerSpecAppears in:ImageReviewSpecImageReviewContainerSpec is a description of a container within the pod creation request.FieldDescriptionimagestringThis can be in the form image:tag or image@SHA:012345679abcdef.ImageReviewSpecAppears in:ImageReviewImageReviewSpec is a description of the pod creation request.FieldDescriptioncontainers[]ImageReviewContainerSpecContainers is a list of a subset of the information in each container of the Pod being created.annotationsmap[string]stringAnnotations is a list of key-value pairs extracted from the Pod's annotations. It only includes keys which match the pattern *.image-policy.k8s.io/*. It is up to each webhook backend to determine how to interpret these annotations, if at all.namespacestringNamespace is the namespace the pod is being created in.ImageReviewStatusAppears in:ImageReviewImageReviewStatus is the result of the review for the pod creation request.FieldDescriptionallowed [Required]boolAllowed indicates that all images were allowed to be run.reasonstringReason should be empty unless Allowed is false in which case it may contain a short description of what is wrong. Kubernetes may truncate excessively long errors when displaying to the user.auditAnnotationsmap[string]stringAuditAnnotations will be added to the attributes object of the admission controller request using 'AddAnnotation'. The keys should be prefix-less (i.e., the admission controller will add an appropriate prefix).This page is automatically generated.If you plan to report an issue with this page, mention that the page is auto-generated in your issue description. The fix may need to happen elsewhere in the Kubernetes project.


Question: What is Resource Types?

Answer: I m a g e R e v i e w


Question: What is ImageReview?

Answer: I m a g e R e v i e w   c h e c k s   i f   t h e   s e t   o f   i m a g e s   i n   a   p o d   a r e   a l l o w e d .   S t a n d a r d   o b j e c t ' s   m e t a d a t a .   M o r e   i n f o :   h t t p s : / / g i t . k 8 s . i o / c o m m u n i t y / c o n t r i b u t o r s / d e v e l / s i g - a r c h i t e c t u r e / a p i - c o n v e n t i o n s . m d # m e t a d a t a   S p e c   h o l d s   i n f o r m a t i o n   a b o u t   t h e   p o d   b e i n g   e v a l u a t e d   S t a t u s   i s   f i l l e d   i n   b y   t h e   b a c k e n d   a n d   i n d i c a t e s   w h e t h e r   t h e   p o d   s h o u l d   b e   a l l o w e d .


Question: What is ImageReviewContainerSpec?

Answer: A p p e a r s   i n :   I m a g e R e v i e w S p e c   I m a g e R e v i e w C o n t a i n e r S p e c   i s   a   d e s c r i p t i o n   o f   a   c o n t a i n e r   w i t h i n   t h e   p o d   c r e a t i o n   r e q u e s t .   T h i s   c a n   b e   i n   t h e   f o r m   i m a g e : t a g   o r   i m a g e @ S H A : 0 1 2 3 4 5 6 7 9 a b c d e f .


Question: What is ImageReviewSpec?

Answer: A p p e a r s   i n :   I m a g e R e v i e w   I m a g e R e v i e w S p e c   i s   a   d e s c r i p t i o n   o f   t h e   p o d   c r e a t i o n   r e q u e s t .   C o n t a i n e r s   i s   a   l i s t   o f   a   s u b s e t   o f   t h e   i n f o r m a t i o n   i n   e a c h   c o n t a i n e r   o f   t h e   P o d   b e i n g   c r e a t e d .   A n n o t a t i o n s   i s   a   l i s t   o f   k e y - v a l u e   p a i r s   e x t r a c t e d   f r o m   t h e   P o d ' s   a n n o t a t i o n s .   I t   o n l y   i n c l u d e s   k e y s   w h i c h   m a t c h   t h e   p a t t e r n   * . i m a g e - p o l i c y . k 8 s . i o / * .   I t   i s   u p   t o   e a c h   w e b h o o k   b a c k e n d   t o   d e t e r m i n e   h o w   t o   i n t e r p r e t   t h e s e   a n n o t a t i o n s ,   i f   a t   a l l .   N a m e s p a c e   i s   t h e   n a m e s p a c e   t h e   p o d   i s   b e i n g   c r e a t e d   i n .


Question: What is ImageReviewStatus?

Answer: A p p e a r s   i n :   I m a g e R e v i e w   I m a g e R e v i e w S t a t u s   i s   t h e   r e s u l t   o f   t h e   r e v i e w   f o r   t h e   p o d   c r e a t i o n   r e q u e s t .   A l l o w e d   i n d i c a t e s   t h a t   a l l   i m a g e s   w e r e   a l l o w e d   t o   b e   r u n .   R e a s o n   s h o u l d   b e   e m p t y   u n l e s s   A l l o w e d   i s   f a l s e   i n   w h i c h   c a s e   i t   m a y   c o n t a i n   a   s h o r t   d e s c r i p t i o n   o f   w h a t   i s   w r o n g .   K u b e r n e t e s   m a y   t r u n c a t e   e x c e s s i v e l y   l o n g   e r r o r s   w h e n   d i s p l a y i n g   t o   t h e   u s e r .   A u d i t A n n o t a t i o n s   w i l l   b e   a d d e d   t o   t h e   a t t r i b u t e s   o b j e c t   o f   t h e   a d m i s s i o n   c o n t r o l l e r   r e q u e s t   u s i n g   ' A d d A n n o t a t i o n ' .   T h e   k e y s   s h o u l d   b e   p r e f i x - l e s s   ( i . e . ,   t h e   a d m i s s i o n   c o n t r o l l e r   w i l l   a d d   a n   a p p r o p r i a t e   p r e f i x ) .   T h i s   p a g e   i s   a u t o m a t i c a l l y   g e n e r a t e d .   I f   y o u   p l a n   t o   r e p o r t   a n   i s s u e   w i t h   t h i s   p a g e ,   m e n t i o n   t h a t   t h e   p a g e   i s   a u t o - g e n e r a t e d   i n   y o u r   i s s u e   d e s c r i p t i o n .   T h e   f i x   m a y   n e e d   t o   h a p p e n   e l s e w h e r e   i n   t h e   K u b e r n e t e s   p r o j e c t .


Question: What is Workload Management?

Answer: Workload ManagementKubernetes provides several built-in APIs for declarative management of your workloads and the components of those workloads.Ultimately, your applications run as containers inside Pods; however, managing individual Pods would be a lot of effort. For example, if a Pod fails, you probably want to run a new Pod to replace it. Kubernetes can do that for you.You use the Kubernetes API to create a workload object that represents a higher abstraction level than a Pod, and then the Kubernetes control plane automatically manages Pod objects on your behalf, based on the specification for the workload object you defined.The built-in APIs for managing workloads are:Deployment (and, indirectly, ReplicaSet), the most common way to run an application on your cluster. Deployment is a good fit for managing a stateless application workload on your cluster, where any Pod in the Deployment is interchangeable and can be replaced if needed. (Deployments are a replacement for the legacy ReplicationController API).A StatefulSet lets you manage one or more Pods – all running the same application code – where the Pods rely on having a distinct identity. This is different from a Deployment where the Pods are expected to be interchangeable. The most common use for a StatefulSet is to be able to make a link between its Pods and their persistent storage. For example, you can run a StatefulSet that associates each Pod with a PersistentVolume. If one of the Pods in the StatefulSet fails, Kubernetes makes a replacement Pod that is connected to the same PersistentVolume.A DaemonSet defines Pods that provide facilities that are local to a specific node; for example, a driver that lets containers on that node access a storage system. You use a DaemonSet when the driver, or other node-level service, has to run on the node where it's useful. Each Pod in a DaemonSet performs a role similar to a system daemon on a classic Unix / POSIX server. A DaemonSet might be fundamental to the operation of your cluster, such as a plugin to let that node access cluster networking, it might help you to manage the node, or it could provide less essential facilities that enhance the container platform you are running. You can run DaemonSets (and their pods) across every node in your cluster, or across just a subset (for example, only install the GPU accelerator driver on nodes that have a GPU installed).You can use a Job and / or a CronJob to define tasks that run to completion and then stop. A Job represents a one-off task, whereas each CronJob repeats according to a schedule.Other topics in this section:Automatic Cleanup for Finished JobsReplicationController


Question: How does Workload Management work?

Answer: Workload ManagementKubernetes provides several built-in APIs for declarative management of your workloads and the components of those workloads.Ultimately, your applications run as containers inside Pods; however, managing individual Pods would be a lot of effort. For example, if a Pod fails, you probably want to run a new Pod to replace it. Kubernetes can do that for you.You use the Kubernetes API to create a workload object that represents a higher abstraction level than a Pod, and then the Kubernetes control plane automatically manages Pod objects on your behalf, based on the specification for the workload object you defined.The built-in APIs for managing workloads are:Deployment (and, indirectly, ReplicaSet), the most common way to run an application on your cluster. Deployment is a good fit for managing a stateless application workload on your cluster, where any Pod in the Deployment is interchangeable and can be replaced if needed. (Deployments are a replacement for the legacy ReplicationController API).A StatefulSet lets you manage one or more Pods – all running the same application code – where the Pods rely on having a distinct identity. This is different from a Deployment where the Pods are expected to be interchangeable. The most common use for a StatefulSet is to be able to make a link between its Pods and their persistent storage. For example, you can run a StatefulSet that associates each Pod with a PersistentVolume. If one of the Pods in the StatefulSet fails, Kubernetes makes a replacement Pod that is connected to the same PersistentVolume.A DaemonSet defines Pods that provide facilities that are local to a specific node; for example, a driver that lets containers on that node access a storage system. You use a DaemonSet when the driver, or other node-level service, has to run on the node where it's useful. Each Pod in a DaemonSet performs a role similar to a system daemon on a classic Unix / POSIX server. A DaemonSet might be fundamental to the operation of your cluster, such as a plugin to let that node access cluster networking, it might help you to manage the node, or it could provide less essential facilities that enhance the container platform you are running. You can run DaemonSets (and their pods) across every node in your cluster, or across just a subset (for example, only install the GPU accelerator driver on nodes that have a GPU installed).You can use a Job and / or a CronJob to define tasks that run to completion and then stop. A Job represents a one-off task, whereas each CronJob repeats according to a schedule.Other topics in this section:Automatic Cleanup for Finished JobsReplicationController


Question: When would you use Workload Management?

Answer: Workload ManagementKubernetes provides several built-in APIs for declarative management of your workloads and the components of those workloads.Ultimately, your applications run as containers inside Pods; however, managing individual Pods would be a lot of effort. For example, if a Pod fails, you probably want to run a new Pod to replace it. Kubernetes can do that for you.You use the Kubernetes API to create a workload object that represents a higher abstraction level than a Pod, and then the Kubernetes control plane automatically manages Pod objects on your behalf, based on the specification for the workload object you defined.The built-in APIs for managing workloads are:Deployment (and, indirectly, ReplicaSet), the most common way to run an application on your cluster. Deployment is a good fit for managing a stateless application workload on your cluster, where any Pod in the Deployment is interchangeable and can be replaced if needed. (Deployments are a replacement for the legacy ReplicationController API).A StatefulSet lets you manage one or more Pods – all running the same application code – where the Pods rely on having a distinct identity. This is different from a Deployment where the Pods are expected to be interchangeable. The most common use for a StatefulSet is to be able to make a link between its Pods and their persistent storage. For example, you can run a StatefulSet that associates each Pod with a PersistentVolume. If one of the Pods in the StatefulSet fails, Kubernetes makes a replacement Pod that is connected to the same PersistentVolume.A DaemonSet defines Pods that provide facilities that are local to a specific node; for example, a driver that lets containers on that node access a storage system. You use a DaemonSet when the driver, or other node-level service, has to run on the node where it's useful. Each Pod in a DaemonSet performs a role similar to a system daemon on a classic Unix / POSIX server. A DaemonSet might be fundamental to the operation of your cluster, such as a plugin to let that node access cluster networking, it might help you to manage the node, or it could provide less essential facilities that enhance the container platform you are running. You can run DaemonSets (and their pods) across every node in your cluster, or across just a subset (for example, only install the GPU accelerator driver on nodes that have a GPU installed).You can use a Job and / or a CronJob to define tasks that run to completion and then stop. A Job represents a one-off task, whereas each CronJob repeats according to a schedule.Other topics in this section:Automatic Cleanup for Finished JobsReplicationController


Question: What are the benefits of Workload Management?

Answer: Workload ManagementKubernetes provides several built-in APIs for declarative management of your workloads and the components of those workloads.Ultimately, your applications run as containers inside Pods; however, managing individual Pods would be a lot of effort. For example, if a Pod fails, you probably want to run a new Pod to replace it. Kubernetes can do that for you.You use the Kubernetes API to create a workload object that represents a higher abstraction level than a Pod, and then the Kubernetes control plane automatically manages Pod objects on your behalf, based on the specification for the workload object you defined.The built-in APIs for managing workloads are:Deployment (and, indirectly, ReplicaSet), the most common way to run an application on your cluster. Deployment is a good fit for managing a stateless application workload on your cluster, where any Pod in the Deployment is interchangeable and can be replaced if needed. (Deployments are a replacement for the legacy ReplicationController API).A StatefulSet lets you manage one or more Pods – all running the same application code – where the Pods rely on having a distinct identity. This is different from a Deployment where the Pods are expected to be interchangeable. The most common use for a StatefulSet is to be able to make a link between its Pods and their persistent storage. For example, you can run a StatefulSet that associates each Pod with a PersistentVolume. If one of the Pods in the StatefulSet fails, Kubernetes makes a replacement Pod that is connected to the same PersistentVolume.A DaemonSet defines Pods that provide facilities that are local to a specific node; for example, a driver that lets containers on that node access a storage system. You use a DaemonSet when the driver, or other node-level service, has to run on the node where it's useful. Each Pod in a DaemonSet performs a role similar to a system daemon on a classic Unix / POSIX server. A DaemonSet might be fundamental to the operation of your cluster, such as a plugin to let that node access cluster networking, it might help you to manage the node, or it could provide less essential facilities that enhance the container platform you are running. You can run DaemonSets (and their pods) across every node in your cluster, or across just a subset (for example, only install the GPU accelerator driver on nodes that have a GPU installed).You can use a Job and / or a CronJob to define tasks that run to completion and then stop. A Job represents a one-off task, whereas each CronJob repeats according to a schedule.Other topics in this section:Automatic Cleanup for Finished JobsReplicationController


Question: What is Workload Management?

Answer: K u b e r n e t e s   p r o v i d e s   s e v e r a l   b u i l t - i n   A P I s   f o r   d e c l a r a t i v e   m a n a g e m e n t   o f   y o u r   w o r k l o a d s   a n d   t h e   c o m p o n e n t s   o f   t h o s e   w o r k l o a d s .   U l t i m a t e l y ,   y o u r   a p p l i c a t i o n s   r u n   a s   c o n t a i n e r s   i n s i d e   P o d s ;   h o w e v e r ,   m a n a g i n g   i n d i v i d u a l   P o d s   w o u l d   b e   a   l o t   o f   e f f o r t .   F o r   e x a m p l e ,   i f   a   P o d   f a i l s ,   y o u   p r o b a b l y   w a n t   t o   r u n   a   n e w   P o d   t o   r e p l a c e   i t .   K u b e r n e t e s   c a n   d o   t h a t   f o r   y o u .   Y o u   u s e   t h e   K u b e r n e t e s   A P I   t o   c r e a t e   a   w o r k l o a d   o b j e c t   t h a t   r e p r e s e n t s   a   h i g h e r   a b s t r a c t i o n   l e v e l   t h a n   a   P o d ,   a n d   t h e n   t h e   K u b e r n e t e s   c o n t r o l   p l a n e   a u t o m a t i c a l l y   m a n a g e s   P o d   o b j e c t s   o n   y o u r   b e h a l f ,   b a s e d   o n   t h e   s p e c i f i c a t i o n   f o r   t h e   w o r k l o a d   o b j e c t   y o u   d e f i n e d .   T h e   b u i l t - i n   A P I s   f o r   m a n a g i n g   w o r k l o a d s   a r e :   D e p l o y m e n t   ( a n d ,   i n d i r e c t l y ,   R e p l i c a S e t ) ,   t h e   m o s t   c o m m o n   w a y   t o   r u n   a n   a p p l i c a t i o n   o n   y o u r   c l u s t e r .   D e p l o y m e n t   i s   a   g o o d   f i t   f o r   m a n a g i n g   a   s t a t e l e s s   a p p l i c a t i o n   w o r k l o a d   o n   y o u r   c l u s t e r ,   w h e r e   a n y   P o d   i n   t h e   D e p l o y m e n t   i s   i n t e r c h a n g e a b l e   a n d   c a n   b e   r e p l a c e d   i f   n e e d e d .   ( D e p l o y m e n t s   a r e   a   r e p l a c e m e n t   f o r   t h e   l e g a c y   R e p l i c a t i o n C o n t r o


Question: What is Organizing Cluster Access Using kubeconfig Files?

Answer: Organizing Cluster Access Using kubeconfig FilesUse kubeconfig files to organize information about clusters, users, namespaces, and authentication mechanisms. The kubectl command-line tool uses kubeconfig files to find the information it needs to choose a cluster and communicate with the API server of a cluster.Note:A file that is used to configure access to clusters is called a kubeconfig file. This is a generic way of referring to configuration files. It does not mean that there is a file named kubeconfig.Warning:Only use kubeconfig files from trusted sources. Using a specially-crafted kubeconfig file could result in malicious code execution or file exposure. If you must use an untrusted kubeconfig file, inspect it carefully first, much as you would a shell script.By default, kubectl looks for a file named config in the $HOME/.kube directory. You can specify other kubeconfig files by setting the KUBECONFIG environment variable or by setting the --kubeconfig flag.For step-by-step instructions on creating and specifying kubeconfig files, see Configure Access to Multiple Clusters.Supporting multiple clusters, users, and authentication mechanismsSuppose you have several clusters, and your users and components authenticate in a variety of ways. For example:A running kubelet might authenticate using certificates.A user might authenticate using tokens.Administrators might have sets of certificates that they provide to individual users.With kubeconfig files, you can organize your clusters, users, and namespaces. You can also define contexts to quickly and easily switch between clusters and namespaces.ContextA context element in a kubeconfig file is used to group access parameters under a convenient name. Each context has three parameters: cluster, namespace, and user. By default, the kubectl command-line tool uses parameters from the current context to communicate with the cluster.To choose the current context:kubectl config use-context The KUBECONFIG environment variableThe KUBECONFIG environment variable holds a list of kubeconfig files. For Linux and Mac, the list is colon-delimited. For Windows, the list is semicolon-delimited. The KUBECONFIG environment variable is not required. If the KUBECONFIG environment variable doesn't exist, kubectl uses the default kubeconfig file, $HOME/.kube/config.If the KUBECONFIG environment variable does exist, kubectl uses an effective configuration that is the result of merging the files listed in the KUBECONFIG environment variable.Merging kubeconfig filesTo see your configuration, enter this command:kubectl config view As described previously, the output might be from a single kubeconfig file, or it might be the result of merging several kubeconfig files.Here are the rules that kubectl uses when it merges kubeconfig files:If the --kubeconfig flag is set, use only the specified file. Do not merge. Only one instance of this flag is allowed.Otherwise, if the KUBECONFIG environment variable is set, use it as a list o


Question: How does Organizing Cluster Access Using kubeconfig Files work?

Answer: Organizing Cluster Access Using kubeconfig FilesUse kubeconfig files to organize information about clusters, users, namespaces, and authentication mechanisms. The kubectl command-line tool uses kubeconfig files to find the information it needs to choose a cluster and communicate with the API server of a cluster.Note:A file that is used to configure access to clusters is called a kubeconfig file. This is a generic way of referring to configuration files. It does not mean that there is a file named kubeconfig.Warning:Only use kubeconfig files from trusted sources. Using a specially-crafted kubeconfig file could result in malicious code execution or file exposure. If you must use an untrusted kubeconfig file, inspect it carefully first, much as you would a shell script.By default, kubectl looks for a file named config in the $HOME/.kube directory. You can specify other kubeconfig files by setting the KUBECONFIG environment variable or by setting the --kubeconfig flag.For step-by-step instructions on creating and specifying kubeconfig files, see Configure Access to Multiple Clusters.Supporting multiple clusters, users, and authentication mechanismsSuppose you have several clusters, and your users and components authenticate in a variety of ways. For example:A running kubelet might authenticate using certificates.A user might authenticate using tokens.Administrators might have sets of certificates that they provide to individual users.With kubeconfig files, you can organize your clusters, users, and namespaces. You can also define contexts to quickly and easily switch between clusters and namespaces.ContextA context element in a kubeconfig file is used to group access parameters under a convenient name. Each context has three parameters: cluster, namespace, and user. By default, the kubectl command-line tool uses parameters from the current context to communicate with the cluster.To choose the current context:kubectl config use-context The KUBECONFIG environment variableThe KUBECONFIG environment variable holds a list of kubeconfig files. For Linux and Mac, the list is colon-delimited. For Windows, the list is semicolon-delimited. The KUBECONFIG environment variable is not required. If the KUBECONFIG environment variable doesn't exist, kubectl uses the default kubeconfig file, $HOME/.kube/config.If the KUBECONFIG environment variable does exist, kubectl uses an effective configuration that is the result of merging the files listed in the KUBECONFIG environment variable.Merging kubeconfig filesTo see your configuration, enter this command:kubectl config view As described previously, the output might be from a single kubeconfig file, or it might be the result of merging several kubeconfig files.Here are the rules that kubectl uses when it merges kubeconfig files:If the --kubeconfig flag is set, use only the specified file. Do not merge. Only one instance of this flag is allowed.Otherwise, if the KUBECONFIG environment variable is set, use it as a list o


Question: When would you use Organizing Cluster Access Using kubeconfig Files?

Answer: Organizing Cluster Access Using kubeconfig FilesUse kubeconfig files to organize information about clusters, users, namespaces, and authentication mechanisms. The kubectl command-line tool uses kubeconfig files to find the information it needs to choose a cluster and communicate with the API server of a cluster.Note:A file that is used to configure access to clusters is called a kubeconfig file. This is a generic way of referring to configuration files. It does not mean that there is a file named kubeconfig.Warning:Only use kubeconfig files from trusted sources. Using a specially-crafted kubeconfig file could result in malicious code execution or file exposure. If you must use an untrusted kubeconfig file, inspect it carefully first, much as you would a shell script.By default, kubectl looks for a file named config in the $HOME/.kube directory. You can specify other kubeconfig files by setting the KUBECONFIG environment variable or by setting the --kubeconfig flag.For step-by-step instructions on creating and specifying kubeconfig files, see Configure Access to Multiple Clusters.Supporting multiple clusters, users, and authentication mechanismsSuppose you have several clusters, and your users and components authenticate in a variety of ways. For example:A running kubelet might authenticate using certificates.A user might authenticate using tokens.Administrators might have sets of certificates that they provide to individual users.With kubeconfig files, you can organize your clusters, users, and namespaces. You can also define contexts to quickly and easily switch between clusters and namespaces.ContextA context element in a kubeconfig file is used to group access parameters under a convenient name. Each context has three parameters: cluster, namespace, and user. By default, the kubectl command-line tool uses parameters from the current context to communicate with the cluster.To choose the current context:kubectl config use-context The KUBECONFIG environment variableThe KUBECONFIG environment variable holds a list of kubeconfig files. For Linux and Mac, the list is colon-delimited. For Windows, the list is semicolon-delimited. The KUBECONFIG environment variable is not required. If the KUBECONFIG environment variable doesn't exist, kubectl uses the default kubeconfig file, $HOME/.kube/config.If the KUBECONFIG environment variable does exist, kubectl uses an effective configuration that is the result of merging the files listed in the KUBECONFIG environment variable.Merging kubeconfig filesTo see your configuration, enter this command:kubectl config view As described previously, the output might be from a single kubeconfig file, or it might be the result of merging several kubeconfig files.Here are the rules that kubectl uses when it merges kubeconfig files:If the --kubeconfig flag is set, use only the specified file. Do not merge. Only one instance of this flag is allowed.Otherwise, if the KUBECONFIG environment variable is set, use it as a list o


Question: What are the benefits of Organizing Cluster Access Using kubeconfig Files?

Answer: Organizing Cluster Access Using kubeconfig FilesUse kubeconfig files to organize information about clusters, users, namespaces, and authentication mechanisms. The kubectl command-line tool uses kubeconfig files to find the information it needs to choose a cluster and communicate with the API server of a cluster.Note:A file that is used to configure access to clusters is called a kubeconfig file. This is a generic way of referring to configuration files. It does not mean that there is a file named kubeconfig.Warning:Only use kubeconfig files from trusted sources. Using a specially-crafted kubeconfig file could result in malicious code execution or file exposure. If you must use an untrusted kubeconfig file, inspect it carefully first, much as you would a shell script.By default, kubectl looks for a file named config in the $HOME/.kube directory. You can specify other kubeconfig files by setting the KUBECONFIG environment variable or by setting the --kubeconfig flag.For step-by-step instructions on creating and specifying kubeconfig files, see Configure Access to Multiple Clusters.Supporting multiple clusters, users, and authentication mechanismsSuppose you have several clusters, and your users and components authenticate in a variety of ways. For example:A running kubelet might authenticate using certificates.A user might authenticate using tokens.Administrators might have sets of certificates that they provide to individual users.With kubeconfig files, you can organize your clusters, users, and namespaces. You can also define contexts to quickly and easily switch between clusters and namespaces.ContextA context element in a kubeconfig file is used to group access parameters under a convenient name. Each context has three parameters: cluster, namespace, and user. By default, the kubectl command-line tool uses parameters from the current context to communicate with the cluster.To choose the current context:kubectl config use-context The KUBECONFIG environment variableThe KUBECONFIG environment variable holds a list of kubeconfig files. For Linux and Mac, the list is colon-delimited. For Windows, the list is semicolon-delimited. The KUBECONFIG environment variable is not required. If the KUBECONFIG environment variable doesn't exist, kubectl uses the default kubeconfig file, $HOME/.kube/config.If the KUBECONFIG environment variable does exist, kubectl uses an effective configuration that is the result of merging the files listed in the KUBECONFIG environment variable.Merging kubeconfig filesTo see your configuration, enter this command:kubectl config view As described previously, the output might be from a single kubeconfig file, or it might be the result of merging several kubeconfig files.Here are the rules that kubectl uses when it merges kubeconfig files:If the --kubeconfig flag is set, use only the specified file. Do not merge. Only one instance of this flag is allowed.Otherwise, if the KUBECONFIG environment variable is set, use it as a list o


Question: What is Organizing Cluster Access Using kubeconfig Files?

Answer: U s e   k u b e c o n f i g   f i l e s   t o   o r g a n i z e   i n f o r m a t i o n   a b o u t   c l u s t e r s ,   u s e r s ,   n a m e s p a c e s ,   a n d   a u t h e n t i c a t i o n   m e c h a n i s m s .   T h e   k u b e c t l   c o m m a n d - l i n e   t o o l   u s e s   k u b e c o n f i g   f i l e s   t o   f i n d   t h e   i n f o r m a t i o n   i t   n e e d s   t o   c h o o s e   a   c l u s t e r   a n d   c o m m u n i c a t e   w i t h   t h e   A P I   s e r v e r   o f   a   c l u s t e r .


Question: What is Warning:?

Answer: B y   d e f a u l t ,   k u b e c t l   l o o k s   f o r   a   f i l e   n a m e d   c o n f i g   i n   t h e   $ H O M E / . k u b e   d i r e c t o r y .   Y o u   c a n   s p e c i f y   o t h e r   k u b e c o n f i g   f i l e s   b y   s e t t i n g   t h e   K U B E C O N F I G   e n v i r o n m e n t   v a r i a b l e   o r   b y   s e t t i n g   t h e   - - k u b e c o n f i g   f l a g .   F o r   s t e p - b y - s t e p   i n s t r u c t i o n s   o n   c r e a t i n g   a n d   s p e c i f y i n g   k u b e c o n f i g   f i l e s ,   s e e   C o n f i g u r e   A c c e s s   t o   M u l t i p l e   C l u s t e r s .


Question: What is Supporting multiple clusters, users, and authentication mechanisms?

Answer: S u p p o s e   y o u   h a v e   s e v e r a l   c l u s t e r s ,   a n d   y o u r   u s e r s   a n d   c o m p o n e n t s   a u t h e n t i c a t e   i n   a   v a r i e t y   o f   w a y s .   F o r   e x a m p l e :   A   r u n n i n g   k u b e l e t   m i g h t   a u t h e n t i c a t e   u s i n g   c e r t i f i c a t e s . A   u s e r   m i g h t   a u t h e n t i c a t e   u s i n g   t o k e n s . A d m i n i s t r a t o r s   m i g h t   h a v e   s e t s   o f   c e r t i f i c a t e s   t h a t   t h e y   p r o v i d e   t o   i n d i v i d u a l   u s e r s .   W i t h   k u b e c o n f i g   f i l e s ,   y o u   c a n   o r g a n i z e   y o u r   c l u s t e r s ,   u s e r s ,   a n d   n a m e s p a c e s .   Y o u   c a n   a l s o   d e f i n e   c o n t e x t s   t o   q u i c k l y   a n d   e a s i l y   s w i t c h   b e t w e e n   c l u s t e r s   a n d   n a m e s p a c e s .


Question: What is Context?

Answer: A   c o n t e x t   e l e m e n t   i n   a   k u b e c o n f i g   f i l e   i s   u s e d   t o   g r o u p   a c c e s s   p a r a m e t e r s   u n d e r   a   c o n v e n i e n t   n a m e .   E a c h   c o n t e x t   h a s   t h r e e   p a r a m e t e r s :   c l u s t e r ,   n a m e s p a c e ,   a n d   u s e r .   B y   d e f a u l t ,   t h e   k u b e c t l   c o m m a n d - l i n e   t o o l   u s e s   p a r a m e t e r s   f r o m   t h e   c u r r e n t   c o n t e x t   t o   c o m m u n i c a t e   w i t h   t h e   c l u s t e r .   T o   c h o o s e   t h e   c u r r e n t   c o n t e x t :   k u b e c t l   c o n f i g   u s e - c o n t e x t


Question: What is The KUBECONFIG environment variable?

Answer: T h e   K U B E C O N F I G   e n v i r o n m e n t   v a r i a b l e   h o l d s   a   l i s t   o f   k u b e c o n f i g   f i l e s .   F o r   L i n u x   a n d   M a c ,   t h e   l i s t   i s   c o l o n - d e l i m i t e d .   F o r   W i n d o w s ,   t h e   l i s t   i s   s e m i c o l o n - d e l i m i t e d .   T h e   K U B E C O N F I G   e n v i r o n m e n t   v a r i a b l e   i s   n o t   r e q u i r e d .   I f   t h e   K U B E C O N F I G   e n v i r o n m e n t   v a r i a b l e   d o e s n ' t   e x i s t ,   k u b e c t l   u s e s   t h e   d e f a u l t   k u b e c o n f i g   f i l e ,   $ H O M E / . k u b e / c o n f i g .   I f   t h e   K U B E C O N F I G   e n v i r o n m e n t   v a r i a b l e   d o e s   e x i s t ,   k u b e c t l   u s e s   a n   e f f e c t i v e   c o n f i g u r a t i o n   t h a t   i s   t h e   r e s u l t   o f   m e r g i n g   t h e   f i l e s   l i s t e d   i n   t h e   K U B E C O N F I G   e n v i r o n m e n t   v a r i a b l e .


Question: What is Merging kubeconfig files?

Answer: T o   s e e   y o u r   c o n f i g u r a t i o n ,   e n t e r   t h i s   c o m m a n d :   k u b e c t l   c o n f i g   v i e w   A s   d e s c r i b e d   p r e v i o u s l y ,   t h e   o u t p u t   m i g h t   b e   f r o m   a   s i n g l e   k u b e c o n f i g   f i l e ,   o r   i t   m i g h t   b e   t h e   r e s u l t   o f   m e r g i n g   s e v e r a l   k u b e c o n f i g   f i l e s .   H e r e   a r e   t h e   r u l e s   t h a t   k u b e c t l   u s e s   w h e n   i t   m e r g e s   k u b e c o n f i g   f i l e s :   I f   t h e   - - k u b e c o n f i g   f l a g   i s   s e t ,   u s e   o n l y   t h e   s p e c i f i e d   f i l e .   D o   n o t   m e r g e .   O n l y   o n e   i n s t a n c e   o f   t h i s   f l a g   i s   a l l o w e d . O t h e r w i s e ,   i f   t h e   K U B E C O N F I G   e n v i r o n m e n t   v a r i a b l e   i s   s e t ,   u s e   i t   a s   a   l i s t   o f   f i l e s   t h a t   s h o u l d   b e   m e r g e d .   M e r g e   t h e   f i l e s   l i s t e d   i n   t h e   K U B E C O N F I G   e n v i r o n m e n t   v a r i a b l e   a c c o r d i n g   t o   t h e s e   r u l e s : I g n o r e   e m p t y   f i l e n a m e s . P r o d u c e   e r r o r s   f o r   f i l e s   w i t h   c o n t e n t   t h a t   c a n n o t   b e   d e s e r i a l i z e d . T h e   f i r s t   f i l e   t o   s e t   a   p a r t i c u l a r   v a l u e   o r   m a p   k e y   w i n s . N e v e r   c h a n g e   t h e   v a l u e   o r   m a p   k e y .   E x a m p l e :   P r e s e r v e   t h e   c o n t e x t   o f   t h e   f i r s t   f i l e   t o   s e t   c u r r e n t - c o n t e x t .   E x a m p l e :   I f   t w o   f i l e s   s p e c i f y   a   r e d - u s e r ,   u s e   o n l y   v a l u e s   f r o m   t h e   f i r s t   f i l e ' s   r e d - u s e r .   E v e n   i f   t h e   s e c o n d   f i l e   h a s   n o n - c o n f l i c t i n g   e n t r i e s   u n d e r   r e d - u s e r ,   d


Question: What is File references?

Answer: F i l e   a n d   p a t h   r e f e r e n c e s   i n   a   k u b e c o n f i g   f i l e   a r e   r e l a t i v e   t o   t h e   l o c a t i o n   o f   t h e   k u b e c o n f i g   f i l e .   F i l e   r e f e r e n c e s   o n   t h e   c o m m a n d   l i n e   a r e   r e l a t i v e   t o   t h e   c u r r e n t   w o r k i n g   d i r e c t o r y .   I n   $ H O M E / . k u b e / c o n f i g ,   r e l a t i v e   p a t h s   a r e   s t o r e d   r e l a t i v e l y ,   a n d   a b s o l u t e   p a t h s   a r e   s t o r e d   a b s o l u t e l y .


Question: What is Proxy?

Answer: Y o u   c a n   c o n f i g u r e   k u b e c t l   t o   u s e   a   p r o x y   p e r   c l u s t e r   u s i n g   p r o x y - u r l   i n   y o u r   k u b e c o n f i g   f i l e ,   l i k e   t h i s :   a p i V e r s i o n :   v 1   k i n d :   C o n f i g   c l u s t e r s :   -   c l u s t e r :   p r o x y - u r l :   h t t p : / / p r o x y . e x a m p l e . o r g : 3 1 2 8   s e r v e r :   h t t p s : / / k 8 s . e x a m p l e . o r g / k 8 s / c l u s t e r s / c - x x y y z z   n a m e :   d e v e l o p m e n t   u s e r s :   -   n a m e :   d e v e l o p e r   c o n t e x t s :   -   c o n t e x t :   n a m e :   d e v e l o p m e n t


Question: What is What's next?

Answer: C o n f i g u r e   A c c e s s   t o   M u l t i p l e   C l u s t e r s k u b e c t l   c o n f i g


Question: What is Resource Management for Windows nodes?

Answer: Resource Management for Windows nodesThis page outlines the differences in how resources are managed between Linux and Windows.On Linux nodes, cgroups are used as a pod boundary for resource control. Containers are created within that boundary for network, process and file system isolation. The Linux cgroup APIs can be used to gather CPU, I/O, and memory use statistics.In contrast, Windows uses a job object per container with a system namespace filter to contain all processes in a container and provide logical isolation from the host. (Job objects are a Windows process isolation mechanism and are different from what Kubernetes refers to as a Job).There is no way to run a Windows container without the namespace filtering in place. This means that system privileges cannot be asserted in the context of the host, and thus privileged containers are not available on Windows. Containers cannot assume an identity from the host because the Security Account Manager (SAM) is separate.Memory managementWindows does not have an out-of-memory process killer as Linux does. Windows always treats all user-mode memory allocations as virtual, and pagefiles are mandatory.Windows nodes do not overcommit memory for processes. The net effect is that Windows won't reach out of memory conditions the same way Linux does, and processes page to disk instead of being subject to out of memory (OOM) termination. If memory is over-provisioned and all physical memory is exhausted, then paging can slow down performance.CPU managementWindows can limit the amount of CPU time allocated for different processes but cannot guarantee a minimum amount of CPU time.On Windows, the kubelet supports a command-line flag to set the scheduling priority of the kubelet process: --windows-priorityclass. This flag allows the kubelet process to get more CPU time slices when compared to other processes running on the Windows host. More information on the allowable values and their meaning is available at Windows Priority Classes. To ensure that running Pods do not starve the kubelet of CPU cycles, set this flag to ABOVE_NORMAL_PRIORITY_CLASS or above.Resource reservationTo account for memory and CPU used by the operating system, the container runtime, and by Kubernetes host processes such as the kubelet, you can (and should) reserve memory and CPU resources with the --kube-reserved and/or --system-reserved kubelet flags. On Windows these values are only used to calculate the node's allocatable resources.Caution:As you deploy workloads, set resource memory and CPU limits on containers. This also subtracts from NodeAllocatable and helps the cluster-wide scheduler in determining which pods to place on which nodes.Scheduling pods without limits may over-provision the Windows nodes and in extreme cases can cause the nodes to become unhealthy.On Windows, a good practice is to reserve at least 2GiB of memory.To determine how much CPU to reserve, identify the maximum pod density for each node and monitor the


Question: How does Resource Management for Windows nodes work?

Answer: Resource Management for Windows nodesThis page outlines the differences in how resources are managed between Linux and Windows.On Linux nodes, cgroups are used as a pod boundary for resource control. Containers are created within that boundary for network, process and file system isolation. The Linux cgroup APIs can be used to gather CPU, I/O, and memory use statistics.In contrast, Windows uses a job object per container with a system namespace filter to contain all processes in a container and provide logical isolation from the host. (Job objects are a Windows process isolation mechanism and are different from what Kubernetes refers to as a Job).There is no way to run a Windows container without the namespace filtering in place. This means that system privileges cannot be asserted in the context of the host, and thus privileged containers are not available on Windows. Containers cannot assume an identity from the host because the Security Account Manager (SAM) is separate.Memory managementWindows does not have an out-of-memory process killer as Linux does. Windows always treats all user-mode memory allocations as virtual, and pagefiles are mandatory.Windows nodes do not overcommit memory for processes. The net effect is that Windows won't reach out of memory conditions the same way Linux does, and processes page to disk instead of being subject to out of memory (OOM) termination. If memory is over-provisioned and all physical memory is exhausted, then paging can slow down performance.CPU managementWindows can limit the amount of CPU time allocated for different processes but cannot guarantee a minimum amount of CPU time.On Windows, the kubelet supports a command-line flag to set the scheduling priority of the kubelet process: --windows-priorityclass. This flag allows the kubelet process to get more CPU time slices when compared to other processes running on the Windows host. More information on the allowable values and their meaning is available at Windows Priority Classes. To ensure that running Pods do not starve the kubelet of CPU cycles, set this flag to ABOVE_NORMAL_PRIORITY_CLASS or above.Resource reservationTo account for memory and CPU used by the operating system, the container runtime, and by Kubernetes host processes such as the kubelet, you can (and should) reserve memory and CPU resources with the --kube-reserved and/or --system-reserved kubelet flags. On Windows these values are only used to calculate the node's allocatable resources.Caution:As you deploy workloads, set resource memory and CPU limits on containers. This also subtracts from NodeAllocatable and helps the cluster-wide scheduler in determining which pods to place on which nodes.Scheduling pods without limits may over-provision the Windows nodes and in extreme cases can cause the nodes to become unhealthy.On Windows, a good practice is to reserve at least 2GiB of memory.To determine how much CPU to reserve, identify the maximum pod density for each node and monitor the


Question: When would you use Resource Management for Windows nodes?

Answer: Resource Management for Windows nodesThis page outlines the differences in how resources are managed between Linux and Windows.On Linux nodes, cgroups are used as a pod boundary for resource control. Containers are created within that boundary for network, process and file system isolation. The Linux cgroup APIs can be used to gather CPU, I/O, and memory use statistics.In contrast, Windows uses a job object per container with a system namespace filter to contain all processes in a container and provide logical isolation from the host. (Job objects are a Windows process isolation mechanism and are different from what Kubernetes refers to as a Job).There is no way to run a Windows container without the namespace filtering in place. This means that system privileges cannot be asserted in the context of the host, and thus privileged containers are not available on Windows. Containers cannot assume an identity from the host because the Security Account Manager (SAM) is separate.Memory managementWindows does not have an out-of-memory process killer as Linux does. Windows always treats all user-mode memory allocations as virtual, and pagefiles are mandatory.Windows nodes do not overcommit memory for processes. The net effect is that Windows won't reach out of memory conditions the same way Linux does, and processes page to disk instead of being subject to out of memory (OOM) termination. If memory is over-provisioned and all physical memory is exhausted, then paging can slow down performance.CPU managementWindows can limit the amount of CPU time allocated for different processes but cannot guarantee a minimum amount of CPU time.On Windows, the kubelet supports a command-line flag to set the scheduling priority of the kubelet process: --windows-priorityclass. This flag allows the kubelet process to get more CPU time slices when compared to other processes running on the Windows host. More information on the allowable values and their meaning is available at Windows Priority Classes. To ensure that running Pods do not starve the kubelet of CPU cycles, set this flag to ABOVE_NORMAL_PRIORITY_CLASS or above.Resource reservationTo account for memory and CPU used by the operating system, the container runtime, and by Kubernetes host processes such as the kubelet, you can (and should) reserve memory and CPU resources with the --kube-reserved and/or --system-reserved kubelet flags. On Windows these values are only used to calculate the node's allocatable resources.Caution:As you deploy workloads, set resource memory and CPU limits on containers. This also subtracts from NodeAllocatable and helps the cluster-wide scheduler in determining which pods to place on which nodes.Scheduling pods without limits may over-provision the Windows nodes and in extreme cases can cause the nodes to become unhealthy.On Windows, a good practice is to reserve at least 2GiB of memory.To determine how much CPU to reserve, identify the maximum pod density for each node and monitor the


Question: What are the benefits of Resource Management for Windows nodes?

Answer: Resource Management for Windows nodesThis page outlines the differences in how resources are managed between Linux and Windows.On Linux nodes, cgroups are used as a pod boundary for resource control. Containers are created within that boundary for network, process and file system isolation. The Linux cgroup APIs can be used to gather CPU, I/O, and memory use statistics.In contrast, Windows uses a job object per container with a system namespace filter to contain all processes in a container and provide logical isolation from the host. (Job objects are a Windows process isolation mechanism and are different from what Kubernetes refers to as a Job).There is no way to run a Windows container without the namespace filtering in place. This means that system privileges cannot be asserted in the context of the host, and thus privileged containers are not available on Windows. Containers cannot assume an identity from the host because the Security Account Manager (SAM) is separate.Memory managementWindows does not have an out-of-memory process killer as Linux does. Windows always treats all user-mode memory allocations as virtual, and pagefiles are mandatory.Windows nodes do not overcommit memory for processes. The net effect is that Windows won't reach out of memory conditions the same way Linux does, and processes page to disk instead of being subject to out of memory (OOM) termination. If memory is over-provisioned and all physical memory is exhausted, then paging can slow down performance.CPU managementWindows can limit the amount of CPU time allocated for different processes but cannot guarantee a minimum amount of CPU time.On Windows, the kubelet supports a command-line flag to set the scheduling priority of the kubelet process: --windows-priorityclass. This flag allows the kubelet process to get more CPU time slices when compared to other processes running on the Windows host. More information on the allowable values and their meaning is available at Windows Priority Classes. To ensure that running Pods do not starve the kubelet of CPU cycles, set this flag to ABOVE_NORMAL_PRIORITY_CLASS or above.Resource reservationTo account for memory and CPU used by the operating system, the container runtime, and by Kubernetes host processes such as the kubelet, you can (and should) reserve memory and CPU resources with the --kube-reserved and/or --system-reserved kubelet flags. On Windows these values are only used to calculate the node's allocatable resources.Caution:As you deploy workloads, set resource memory and CPU limits on containers. This also subtracts from NodeAllocatable and helps the cluster-wide scheduler in determining which pods to place on which nodes.Scheduling pods without limits may over-provision the Windows nodes and in extreme cases can cause the nodes to become unhealthy.On Windows, a good practice is to reserve at least 2GiB of memory.To determine how much CPU to reserve, identify the maximum pod density for each node and monitor the


Question: What is Resource Management for Windows nodes?

Answer: T h i s   p a g e   o u t l i n e s   t h e   d i f f e r e n c e s   i n   h o w   r e s o u r c e s   a r e   m a n a g e d   b e t w e e n   L i n u x   a n d   W i n d o w s .   O n   L i n u x   n o d e s ,   c g r o u p s   a r e   u s e d   a s   a   p o d   b o u n d a r y   f o r   r e s o u r c e   c o n t r o l .   C o n t a i n e r s   a r e   c r e a t e d   w i t h i n   t h a t   b o u n d a r y   f o r   n e t w o r k ,   p r o c e s s   a n d   f i l e   s y s t e m   i s o l a t i o n .   T h e   L i n u x   c g r o u p   A P I s   c a n   b e   u s e d   t o   g a t h e r   C P U ,   I / O ,   a n d   m e m o r y   u s e   s t a t i s t i c s .   I n   c o n t r a s t ,   W i n d o w s   u s e s   a   j o b   o b j e c t   p e r   c o n t a i n e r   w i t h   a   s y s t e m   n a m e s p a c e   f i l t e r   t o   c o n t a i n   a l l   p r o c e s s e s   i n   a   c o n t a i n e r   a n d   p r o v i d e   l o g i c a l   i s o l a t i o n   f r o m   t h e   h o s t .   ( J o b   o b j e c t s   a r e   a   W i n d o w s   p r o c e s s   i s o l a t i o n   m e c h a n i s m   a n d   a r e   d i f f e r e n t   f r o m   w h a t   K u b e r n e t e s   r e f e r s   t o   a s   a   J o b ) .   T h e r e   i s   n o   w a y   t o   r u n   a   W i n d o w s   c o n t a i n e r   w i t h o u t   t h e   n a m e s p a c e   f i l t e r i n g   i n   p l a c e .   T h i s   m e a n s   t h a t   s y s t e m   p r i v i l e g e s   c a n n o t   b e   a s s e r t e d   i n   t h e   c o n t e x t   o f   t h e   h o s t ,   a n d   t h u s   p r i v i l e g e d   c o n t a i n e r s   a r e   n o t   a v a i l a b l e   o n   W i n d o w s .   C o n t a i n e r s   c a n n o t   a s s u m e   a n   i d e n t i t y   f r o m   t h e   h o s t   b e c a u s e   t h e   S e c u r i t y   A c c o u n t   M a n a g e r   ( S A M )   i s   s e p a r a t e .


Question: What is Memory management?

Answer: W i n d o w s   d o e s   n o t   h a v e   a n   o u t - o f - m e m o r y   p r o c e s s   k i l l e r   a s   L i n u x   d o e s .   W i n d o w s   a l w a y s   t r e a t s   a l l   u s e r - m o d e   m e m o r y   a l l o c a t i o n s   a s   v i r t u a l ,   a n d   p a g e f i l e s   a r e   m a n d a t o r y .   W i n d o w s   n o d e s   d o   n o t   o v e r c o m m i t   m e m o r y   f o r   p r o c e s s e s .   T h e   n e t   e f f e c t   i s   t h a t   W i n d o w s   w o n ' t   r e a c h   o u t   o f   m e m o r y   c o n d i t i o n s   t h e   s a m e   w a y   L i n u x   d o e s ,   a n d   p r o c e s s e s   p a g e   t o   d i s k   i n s t e a d   o f   b e i n g   s u b j e c t   t o   o u t   o f   m e m o r y   ( O O M )   t e r m i n a t i o n .   I f   m e m o r y   i s   o v e r - p r o v i s i o n e d   a n d   a l l   p h y s i c a l   m e m o r y   i s   e x h a u s t e d ,   t h e n   p a g i n g   c a n   s l o w   d o w n   p e r f o r m a n c e .


Question: What is CPU management?

Answer: W i n d o w s   c a n   l i m i t   t h e   a m o u n t   o f   C P U   t i m e   a l l o c a t e d   f o r   d i f f e r e n t   p r o c e s s e s   b u t   c a n n o t   g u a r a n t e e   a   m i n i m u m   a m o u n t   o f   C P U   t i m e .   O n   W i n d o w s ,   t h e   k u b e l e t   s u p p o r t s   a   c o m m a n d - l i n e   f l a g   t o   s e t   t h e   s c h e d u l i n g   p r i o r i t y   o f   t h e   k u b e l e t   p r o c e s s :   - - w i n d o w s - p r i o r i t y c l a s s .   T h i s   f l a g   a l l o w s   t h e   k u b e l e t   p r o c e s s   t o   g e t   m o r e   C P U   t i m e   s l i c e s   w h e n   c o m p a r e d   t o   o t h e r   p r o c e s s e s   r u n n i n g   o n   t h e   W i n d o w s   h o s t .   M o r e   i n f o r m a t i o n   o n   t h e   a l l o w a b l e   v a l u e s   a n d   t h e i r   m e a n i n g   i s   a v a i l a b l e   a t   W i n d o w s   P r i o r i t y   C l a s s e s .   T o   e n s u r e   t h a t   r u n n i n g   P o d s   d o   n o t   s t a r v e   t h e   k u b e l e t   o f   C P U   c y c l e s ,   s e t   t h i s   f l a g   t o   A B O V E _ N O R M A L _ P R I O R I T Y _ C L A S S   o r   a b o v e .


Question: What is Resource reservation?

Answer: T o   a c c o u n t   f o r   m e m o r y   a n d   C P U   u s e d   b y   t h e   o p e r a t i n g   s y s t e m ,   t h e   c o n t a i n e r   r u n t i m e ,   a n d   b y   K u b e r n e t e s   h o s t   p r o c e s s e s   s u c h   a s   t h e   k u b e l e t ,   y o u   c a n   ( a n d   s h o u l d )   r e s e r v e   m e m o r y   a n d   C P U   r e s o u r c e s   w i t h   t h e   - - k u b e - r e s e r v e d   a n d / o r   - - s y s t e m - r e s e r v e d   k u b e l e t   f l a g s .   O n   W i n d o w s   t h e s e   v a l u e s   a r e   o n l y   u s e d   t o   c a l c u l a t e   t h e   n o d e ' s   a l l o c a t a b l e   r e s o u r c e s .


Question: What is Caution:?

Answer: A s   y o u   d e p l o y   w o r k l o a d s ,   s e t   r e s o u r c e   m e m o r y   a n d   C P U   l i m i t s   o n   c o n t a i n e r s .   T h i s   a l s o   s u b t r a c t s   f r o m   N o d e A l l o c a t a b l e   a n d   h e l p s   t h e   c l u s t e r - w i d e   s c h e d u l e r   i n   d e t e r m i n i n g   w h i c h   p o d s   t o   p l a c e   o n   w h i c h   n o d e s .   S c h e d u l i n g   p o d s   w i t h o u t   l i m i t s   m a y   o v e r - p r o v i s i o n   t h e   W i n d o w s   n o d e s   a n d   i n   e x t r e m e   c a s e s   c a n   c a u s e   t h e   n o d e s   t o   b e c o m e   u n h e a l t h y .   O n   W i n d o w s ,   a   g o o d   p r a c t i c e   i s   t o   r e s e r v e   a t   l e a s t   2 G i B   o f   m e m o r y .   T o   d e t e r m i n e   h o w   m u c h   C P U   t o   r e s e r v e ,   i d e n t i f y   t h e   m a x i m u m   p o d   d e n s i t y   f o r   e a c h   n o d e   a n d   m o n i t o r   t h e   C P U   u s a g e   o f   t h e   s y s t e m   s e r v i c e s   r u n n i n g   t h e r e ,   t h e n   c h o o s e   a   v a l u e   t h a t   m e e t s   y o u r   w o r k l o a d   n e e d s .


Question: What is Tools for Monitoring Resources?

Answer: Tools for Monitoring ResourcesTo scale an application and provide a reliable service, you need to understand how the application behaves when it is deployed. You can examine application performance in a Kubernetes cluster by examining the containers, pods, services, and the characteristics of the overall cluster. Kubernetes provides detailed information about an application's resource usage at each of these levels. This information allows you to evaluate your application's performance and where bottlenecks can be removed to improve overall performance.In Kubernetes, application monitoring does not depend on a single monitoring solution. On new clusters, you can use resource metrics or full metrics pipelines to collect monitoring statistics.Resource metrics pipelineThe resource metrics pipeline provides a limited set of metrics related to cluster components such as the Horizontal Pod Autoscaler controller, as well as the kubectl top utility. These metrics are collected by the lightweight, short-term, in-memory metrics-server and are exposed via the metrics.k8s.io API.metrics-server discovers all nodes on the cluster and queries each node's kubelet for CPU and memory usage. The kubelet acts as a bridge between the Kubernetes master and the nodes, managing the pods and containers running on a machine. The kubelet translates each pod into its constituent containers and fetches individual container usage statistics from the container runtime through the container runtime interface. If you use a container runtime that uses Linux cgroups and namespaces to implement containers, and the container runtime does not publish usage statistics, then the kubelet can look up those statistics directly (using code from cAdvisor). No matter how those statistics arrive, the kubelet then exposes the aggregated pod resource usage statistics through the metrics-server Resource Metrics API. This API is served at /metrics/resource/v1beta1 on the kubelet's authenticated and read-only ports.Full metrics pipelineA full metrics pipeline gives you access to richer metrics. Kubernetes can respond to these metrics by automatically scaling or adapting the cluster based on its current state, using mechanisms such as the Horizontal Pod Autoscaler. The monitoring pipeline fetches metrics from the kubelet and then exposes them to Kubernetes via an adapter by implementing either the custom.metrics.k8s.io or external.metrics.k8s.io API.Kubernetes is designed to work with OpenMetrics, which is one of the CNCF Observability and Analysis - Monitoring Projects, built upon and carefully extending Prometheus exposition format in almost 100% backwards-compatible ways.If you glance over at the CNCF Landscape, you can see a number of monitoring projects that can work with Kubernetes by scraping metric data and using that to help you observe your cluster. It is up to you to select the tool or tools that suit your needs. The CNCF landscape for observability and analytics includes a mix of open-so


Question: How does Tools for Monitoring Resources work?

Answer: Tools for Monitoring ResourcesTo scale an application and provide a reliable service, you need to understand how the application behaves when it is deployed. You can examine application performance in a Kubernetes cluster by examining the containers, pods, services, and the characteristics of the overall cluster. Kubernetes provides detailed information about an application's resource usage at each of these levels. This information allows you to evaluate your application's performance and where bottlenecks can be removed to improve overall performance.In Kubernetes, application monitoring does not depend on a single monitoring solution. On new clusters, you can use resource metrics or full metrics pipelines to collect monitoring statistics.Resource metrics pipelineThe resource metrics pipeline provides a limited set of metrics related to cluster components such as the Horizontal Pod Autoscaler controller, as well as the kubectl top utility. These metrics are collected by the lightweight, short-term, in-memory metrics-server and are exposed via the metrics.k8s.io API.metrics-server discovers all nodes on the cluster and queries each node's kubelet for CPU and memory usage. The kubelet acts as a bridge between the Kubernetes master and the nodes, managing the pods and containers running on a machine. The kubelet translates each pod into its constituent containers and fetches individual container usage statistics from the container runtime through the container runtime interface. If you use a container runtime that uses Linux cgroups and namespaces to implement containers, and the container runtime does not publish usage statistics, then the kubelet can look up those statistics directly (using code from cAdvisor). No matter how those statistics arrive, the kubelet then exposes the aggregated pod resource usage statistics through the metrics-server Resource Metrics API. This API is served at /metrics/resource/v1beta1 on the kubelet's authenticated and read-only ports.Full metrics pipelineA full metrics pipeline gives you access to richer metrics. Kubernetes can respond to these metrics by automatically scaling or adapting the cluster based on its current state, using mechanisms such as the Horizontal Pod Autoscaler. The monitoring pipeline fetches metrics from the kubelet and then exposes them to Kubernetes via an adapter by implementing either the custom.metrics.k8s.io or external.metrics.k8s.io API.Kubernetes is designed to work with OpenMetrics, which is one of the CNCF Observability and Analysis - Monitoring Projects, built upon and carefully extending Prometheus exposition format in almost 100% backwards-compatible ways.If you glance over at the CNCF Landscape, you can see a number of monitoring projects that can work with Kubernetes by scraping metric data and using that to help you observe your cluster. It is up to you to select the tool or tools that suit your needs. The CNCF landscape for observability and analytics includes a mix of open-so


Question: When would you use Tools for Monitoring Resources?

Answer: Tools for Monitoring ResourcesTo scale an application and provide a reliable service, you need to understand how the application behaves when it is deployed. You can examine application performance in a Kubernetes cluster by examining the containers, pods, services, and the characteristics of the overall cluster. Kubernetes provides detailed information about an application's resource usage at each of these levels. This information allows you to evaluate your application's performance and where bottlenecks can be removed to improve overall performance.In Kubernetes, application monitoring does not depend on a single monitoring solution. On new clusters, you can use resource metrics or full metrics pipelines to collect monitoring statistics.Resource metrics pipelineThe resource metrics pipeline provides a limited set of metrics related to cluster components such as the Horizontal Pod Autoscaler controller, as well as the kubectl top utility. These metrics are collected by the lightweight, short-term, in-memory metrics-server and are exposed via the metrics.k8s.io API.metrics-server discovers all nodes on the cluster and queries each node's kubelet for CPU and memory usage. The kubelet acts as a bridge between the Kubernetes master and the nodes, managing the pods and containers running on a machine. The kubelet translates each pod into its constituent containers and fetches individual container usage statistics from the container runtime through the container runtime interface. If you use a container runtime that uses Linux cgroups and namespaces to implement containers, and the container runtime does not publish usage statistics, then the kubelet can look up those statistics directly (using code from cAdvisor). No matter how those statistics arrive, the kubelet then exposes the aggregated pod resource usage statistics through the metrics-server Resource Metrics API. This API is served at /metrics/resource/v1beta1 on the kubelet's authenticated and read-only ports.Full metrics pipelineA full metrics pipeline gives you access to richer metrics. Kubernetes can respond to these metrics by automatically scaling or adapting the cluster based on its current state, using mechanisms such as the Horizontal Pod Autoscaler. The monitoring pipeline fetches metrics from the kubelet and then exposes them to Kubernetes via an adapter by implementing either the custom.metrics.k8s.io or external.metrics.k8s.io API.Kubernetes is designed to work with OpenMetrics, which is one of the CNCF Observability and Analysis - Monitoring Projects, built upon and carefully extending Prometheus exposition format in almost 100% backwards-compatible ways.If you glance over at the CNCF Landscape, you can see a number of monitoring projects that can work with Kubernetes by scraping metric data and using that to help you observe your cluster. It is up to you to select the tool or tools that suit your needs. The CNCF landscape for observability and analytics includes a mix of open-so


Question: What are the benefits of Tools for Monitoring Resources?

Answer: Tools for Monitoring ResourcesTo scale an application and provide a reliable service, you need to understand how the application behaves when it is deployed. You can examine application performance in a Kubernetes cluster by examining the containers, pods, services, and the characteristics of the overall cluster. Kubernetes provides detailed information about an application's resource usage at each of these levels. This information allows you to evaluate your application's performance and where bottlenecks can be removed to improve overall performance.In Kubernetes, application monitoring does not depend on a single monitoring solution. On new clusters, you can use resource metrics or full metrics pipelines to collect monitoring statistics.Resource metrics pipelineThe resource metrics pipeline provides a limited set of metrics related to cluster components such as the Horizontal Pod Autoscaler controller, as well as the kubectl top utility. These metrics are collected by the lightweight, short-term, in-memory metrics-server and are exposed via the metrics.k8s.io API.metrics-server discovers all nodes on the cluster and queries each node's kubelet for CPU and memory usage. The kubelet acts as a bridge between the Kubernetes master and the nodes, managing the pods and containers running on a machine. The kubelet translates each pod into its constituent containers and fetches individual container usage statistics from the container runtime through the container runtime interface. If you use a container runtime that uses Linux cgroups and namespaces to implement containers, and the container runtime does not publish usage statistics, then the kubelet can look up those statistics directly (using code from cAdvisor). No matter how those statistics arrive, the kubelet then exposes the aggregated pod resource usage statistics through the metrics-server Resource Metrics API. This API is served at /metrics/resource/v1beta1 on the kubelet's authenticated and read-only ports.Full metrics pipelineA full metrics pipeline gives you access to richer metrics. Kubernetes can respond to these metrics by automatically scaling or adapting the cluster based on its current state, using mechanisms such as the Horizontal Pod Autoscaler. The monitoring pipeline fetches metrics from the kubelet and then exposes them to Kubernetes via an adapter by implementing either the custom.metrics.k8s.io or external.metrics.k8s.io API.Kubernetes is designed to work with OpenMetrics, which is one of the CNCF Observability and Analysis - Monitoring Projects, built upon and carefully extending Prometheus exposition format in almost 100% backwards-compatible ways.If you glance over at the CNCF Landscape, you can see a number of monitoring projects that can work with Kubernetes by scraping metric data and using that to help you observe your cluster. It is up to you to select the tool or tools that suit your needs. The CNCF landscape for observability and analytics includes a mix of open-so


Question: What is Tools for Monitoring Resources?

Answer: T o   s c a l e   a n   a p p l i c a t i o n   a n d   p r o v i d e   a   r e l i a b l e   s e r v i c e ,   y o u   n e e d   t o   u n d e r s t a n d   h o w   t h e   a p p l i c a t i o n   b e h a v e s   w h e n   i t   i s   d e p l o y e d .   Y o u   c a n   e x a m i n e   a p p l i c a t i o n   p e r f o r m a n c e   i n   a   K u b e r n e t e s   c l u s t e r   b y   e x a m i n i n g   t h e   c o n t a i n e r s ,   p o d s ,   s e r v i c e s ,   a n d   t h e   c h a r a c t e r i s t i c s   o f   t h e   o v e r a l l   c l u s t e r .   K u b e r n e t e s   p r o v i d e s   d e t a i l e d   i n f o r m a t i o n   a b o u t   a n   a p p l i c a t i o n ' s   r e s o u r c e   u s a g e   a t   e a c h   o f   t h e s e   l e v e l s .   T h i s   i n f o r m a t i o n   a l l o w s   y o u   t o   e v a l u a t e   y o u r   a p p l i c a t i o n ' s   p e r f o r m a n c e   a n d   w h e r e   b o t t l e n e c k s   c a n   b e   r e m o v e d   t o   i m p r o v e   o v e r a l l   p e r f o r m a n c e .   I n   K u b e r n e t e s ,   a p p l i c a t i o n   m o n i t o r i n g   d o e s   n o t   d e p e n d   o n   a   s i n g l e   m o n i t o r i n g   s o l u t i o n .   O n   n e w   c l u s t e r s ,   y o u   c a n   u s e   r e s o u r c e   m e t r i c s   o r   f u l l   m e t r i c s   p i p e l i n e s   t o   c o l l e c t   m o n i t o r i n g   s t a t i s t i c s .


Question: What is Resource metrics pipeline?

Answer: T h e   r e s o u r c e   m e t r i c s   p i p e l i n e   p r o v i d e s   a   l i m i t e d   s e t   o f   m e t r i c s   r e l a t e d   t o   c l u s t e r   c o m p o n e n t s   s u c h   a s   t h e   H o r i z o n t a l   P o d   A u t o s c a l e r   c o n t r o l l e r ,   a s   w e l l   a s   t h e   k u b e c t l   t o p   u t i l i t y .   T h e s e   m e t r i c s   a r e   c o l l e c t e d   b y   t h e   l i g h t w e i g h t ,   s h o r t - t e r m ,   i n - m e m o r y   m e t r i c s - s e r v e r   a n d   a r e   e x p o s e d   v i a   t h e   m e t r i c s . k 8 s . i o   A P I .   m e t r i c s - s e r v e r   d i s c o v e r s   a l l   n o d e s   o n   t h e   c l u s t e r   a n d   q u e r i e s   e a c h   n o d e ' s   k u b e l e t   f o r   C P U   a n d   m e m o r y   u s a g e .   T h e   k u b e l e t   a c t s   a s   a   b r i d g e   b e t w e e n   t h e   K u b e r n e t e s   m a s t e r   a n d   t h e   n o d e s ,   m a n a g i n g   t h e   p o d s   a n d   c o n t a i n e r s   r u n n i n g   o n   a   m a c h i n e .   T h e   k u b e l e t   t r a n s l a t e s   e a c h   p o d   i n t o   i t s   c o n s t i t u e n t   c o n t a i n e r s   a n d   f e t c h e s   i n d i v i d u a l   c o n t a i n e r   u s a g e   s t a t i s t i c s   f r o m   t h e   c o n t a i n e r   r u n t i m e   t h r o u g h   t h e   c o n t a i n e r   r u n t i m e   i n t e r f a c e .   I f   y o u   u s e   a   c o n t a i n e r   r u n t i m e   t h a t   u s e s   L i n u x   c g r o u p s   a n d   n a m e s p a c e s   t o   i m p l e m e n t   c o n t a i n e r s ,   a n d   t h e   c o n t a i n e r   r u n t i m e   d o e s   n o t   p u b l i s h   u s a g e   s t a t i s t i c s ,   t h e n   t h e   k u b e l e t   c a n   l o o k   u p   t h o s e   s t a t i s t i c s   d i r e c t l y   ( u s i n g   c o d e   f r o m   c A d v i s o r ) .   N o   m a t t e r   h o w   t h o s e   s t a t i s t i c s   a r


Question: What is Full metrics pipeline?

Answer: A   f u l l   m e t r i c s   p i p e l i n e   g i v e s   y o u   a c c e s s   t o   r i c h e r   m e t r i c s .   K u b e r n e t e s   c a n   r e s p o n d   t o   t h e s e   m e t r i c s   b y   a u t o m a t i c a l l y   s c a l i n g   o r   a d a p t i n g   t h e   c l u s t e r   b a s e d   o n   i t s   c u r r e n t   s t a t e ,   u s i n g   m e c h a n i s m s   s u c h   a s   t h e   H o r i z o n t a l   P o d   A u t o s c a l e r .   T h e   m o n i t o r i n g   p i p e l i n e   f e t c h e s   m e t r i c s   f r o m   t h e   k u b e l e t   a n d   t h e n   e x p o s e s   t h e m   t o   K u b e r n e t e s   v i a   a n   a d a p t e r   b y   i m p l e m e n t i n g   e i t h e r   t h e   c u s t o m . m e t r i c s . k 8 s . i o   o r   e x t e r n a l . m e t r i c s . k 8 s . i o   A P I .   K u b e r n e t e s   i s   d e s i g n e d   t o   w o r k   w i t h   O p e n M e t r i c s ,   w h i c h   i s   o n e   o f   t h e   C N C F   O b s e r v a b i l i t y   a n d   A n a l y s i s   -   M o n i t o r i n g   P r o j e c t s ,   b u i l t   u p o n   a n d   c a r e f u l l y   e x t e n d i n g   P r o m e t h e u s   e x p o s i t i o n   f o r m a t   i n   a l m o s t   1 0 0 %   b a c k w a r d s - c o m p a t i b l e   w a y s .   I f   y o u   g l a n c e   o v e r   a t   t h e   C N C F   L a n d s c a p e ,   y o u   c a n   s e e   a   n u m b e r   o f   m o n i t o r i n g   p r o j e c t s   t h a t   c a n   w o r k   w i t h   K u b e r n e t e s   b y   s c r a p i n g   m e t r i c   d a t a   a n d   u s i n g   t h a t   t o   h e l p   y o u   o b s e r v e   y o u r   c l u s t e r .   I t   i s   u p   t o   y o u   t o   s e l e c t   t h e   t o o l   o r   t o o l s   t h a t   s u i t   y o u r   n e e d s .   T h e   C N C F   l a n d s c a p e   f o r   o b s e r v a b i l i t y   a n d   a n a l y t i c s   i n c l u d e s   a   m i x   o f   o p e n - s o u r c e   s o f t w a r e ,   p a


Question: What is What's next?

Answer: L e a r n   a b o u t   a d d i t i o n a l   d e b u g g i n g   t o o l s ,   i n c l u d i n g :   L o g g i n g G e t t i n g   i n t o   c o n t a i n e r s   v i a   e x e c C o n n e c t i n g   t o   c o n t a i n e r s   v i a   p r o x i e s C o n n e c t i n g   t o   c o n t a i n e r s   v i a   p o r t   f o r w a r d i n g I n s p e c t   K u b e r n e t e s   n o d e   w i t h   c r i c t l


Question: What is Garbage Collection?

Answer: Garbage CollectionGarbage collection is a collective term for the various mechanisms Kubernetes uses to clean up cluster resources. This allows the clean up of resources like the following:Terminated podsCompleted JobsObjects without owner referencesUnused containers and container imagesDynamically provisioned PersistentVolumes with a StorageClass reclaim policy of DeleteStale or expired CertificateSigningRequests (CSRs)Nodes deleted in the following scenarios:On a cloud when the cluster uses a cloud controller managerOn-premises when the cluster uses an addon similar to a cloud controller managerNode Lease objectsOwners and dependentsMany objects in Kubernetes link to each other through owner references. Owner references tell the control plane which objects are dependent on others. Kubernetes uses owner references to give the control plane, and other API clients, the opportunity to clean up related resources before deleting an object. In most cases, Kubernetes manages owner references automatically.Ownership is different from the labels and selectors mechanism that some resources also use. For example, consider a Service that creates EndpointSlice objects. The Service uses labels to allow the control plane to determine which EndpointSlice objects are used for that Service. In addition to the labels, each EndpointSlice that is managed on behalf of a Service has an owner reference. Owner references help different parts of Kubernetes avoid interfering with objects they don’t control.Note:Cross-namespace owner references are disallowed by design. Namespaced dependents can specify cluster-scoped or namespaced owners. A namespaced owner must exist in the same namespace as the dependent. If it does not, the owner reference is treated as absent, and the dependent is subject to deletion once all owners are verified absent.Cluster-scoped dependents can only specify cluster-scoped owners. In v1.20+, if a cluster-scoped dependent specifies a namespaced kind as an owner, it is treated as having an unresolvable owner reference, and is not able to be garbage collected.In v1.20+, if the garbage collector detects an invalid cross-namespace ownerReference, or a cluster-scoped dependent with an ownerReference referencing a namespaced kind, a warning Event with a reason of OwnerRefInvalidNamespace and an involvedObject of the invalid dependent is reported. You can check for that kind of Event by running kubectl get events -A --field-selector=reason=OwnerRefInvalidNamespace.Cascading deletionKubernetes checks for and deletes objects that no longer have owner references, like the pods left behind when you delete a ReplicaSet. When you delete an object, you can control whether Kubernetes deletes the object's dependents automatically, in a process called cascading deletion. There are two types of cascading deletion, as follows:Foreground cascading deletionBackground cascading deletionYou can also control how and when garbage collection deletes resources that have owner


Question: How does Garbage Collection work?

Answer: Garbage CollectionGarbage collection is a collective term for the various mechanisms Kubernetes uses to clean up cluster resources. This allows the clean up of resources like the following:Terminated podsCompleted JobsObjects without owner referencesUnused containers and container imagesDynamically provisioned PersistentVolumes with a StorageClass reclaim policy of DeleteStale or expired CertificateSigningRequests (CSRs)Nodes deleted in the following scenarios:On a cloud when the cluster uses a cloud controller managerOn-premises when the cluster uses an addon similar to a cloud controller managerNode Lease objectsOwners and dependentsMany objects in Kubernetes link to each other through owner references. Owner references tell the control plane which objects are dependent on others. Kubernetes uses owner references to give the control plane, and other API clients, the opportunity to clean up related resources before deleting an object. In most cases, Kubernetes manages owner references automatically.Ownership is different from the labels and selectors mechanism that some resources also use. For example, consider a Service that creates EndpointSlice objects. The Service uses labels to allow the control plane to determine which EndpointSlice objects are used for that Service. In addition to the labels, each EndpointSlice that is managed on behalf of a Service has an owner reference. Owner references help different parts of Kubernetes avoid interfering with objects they don’t control.Note:Cross-namespace owner references are disallowed by design. Namespaced dependents can specify cluster-scoped or namespaced owners. A namespaced owner must exist in the same namespace as the dependent. If it does not, the owner reference is treated as absent, and the dependent is subject to deletion once all owners are verified absent.Cluster-scoped dependents can only specify cluster-scoped owners. In v1.20+, if a cluster-scoped dependent specifies a namespaced kind as an owner, it is treated as having an unresolvable owner reference, and is not able to be garbage collected.In v1.20+, if the garbage collector detects an invalid cross-namespace ownerReference, or a cluster-scoped dependent with an ownerReference referencing a namespaced kind, a warning Event with a reason of OwnerRefInvalidNamespace and an involvedObject of the invalid dependent is reported. You can check for that kind of Event by running kubectl get events -A --field-selector=reason=OwnerRefInvalidNamespace.Cascading deletionKubernetes checks for and deletes objects that no longer have owner references, like the pods left behind when you delete a ReplicaSet. When you delete an object, you can control whether Kubernetes deletes the object's dependents automatically, in a process called cascading deletion. There are two types of cascading deletion, as follows:Foreground cascading deletionBackground cascading deletionYou can also control how and when garbage collection deletes resources that have owner


Question: When would you use Garbage Collection?

Answer: Garbage CollectionGarbage collection is a collective term for the various mechanisms Kubernetes uses to clean up cluster resources. This allows the clean up of resources like the following:Terminated podsCompleted JobsObjects without owner referencesUnused containers and container imagesDynamically provisioned PersistentVolumes with a StorageClass reclaim policy of DeleteStale or expired CertificateSigningRequests (CSRs)Nodes deleted in the following scenarios:On a cloud when the cluster uses a cloud controller managerOn-premises when the cluster uses an addon similar to a cloud controller managerNode Lease objectsOwners and dependentsMany objects in Kubernetes link to each other through owner references. Owner references tell the control plane which objects are dependent on others. Kubernetes uses owner references to give the control plane, and other API clients, the opportunity to clean up related resources before deleting an object. In most cases, Kubernetes manages owner references automatically.Ownership is different from the labels and selectors mechanism that some resources also use. For example, consider a Service that creates EndpointSlice objects. The Service uses labels to allow the control plane to determine which EndpointSlice objects are used for that Service. In addition to the labels, each EndpointSlice that is managed on behalf of a Service has an owner reference. Owner references help different parts of Kubernetes avoid interfering with objects they don’t control.Note:Cross-namespace owner references are disallowed by design. Namespaced dependents can specify cluster-scoped or namespaced owners. A namespaced owner must exist in the same namespace as the dependent. If it does not, the owner reference is treated as absent, and the dependent is subject to deletion once all owners are verified absent.Cluster-scoped dependents can only specify cluster-scoped owners. In v1.20+, if a cluster-scoped dependent specifies a namespaced kind as an owner, it is treated as having an unresolvable owner reference, and is not able to be garbage collected.In v1.20+, if the garbage collector detects an invalid cross-namespace ownerReference, or a cluster-scoped dependent with an ownerReference referencing a namespaced kind, a warning Event with a reason of OwnerRefInvalidNamespace and an involvedObject of the invalid dependent is reported. You can check for that kind of Event by running kubectl get events -A --field-selector=reason=OwnerRefInvalidNamespace.Cascading deletionKubernetes checks for and deletes objects that no longer have owner references, like the pods left behind when you delete a ReplicaSet. When you delete an object, you can control whether Kubernetes deletes the object's dependents automatically, in a process called cascading deletion. There are two types of cascading deletion, as follows:Foreground cascading deletionBackground cascading deletionYou can also control how and when garbage collection deletes resources that have owner


Question: What are the benefits of Garbage Collection?

Answer: Garbage CollectionGarbage collection is a collective term for the various mechanisms Kubernetes uses to clean up cluster resources. This allows the clean up of resources like the following:Terminated podsCompleted JobsObjects without owner referencesUnused containers and container imagesDynamically provisioned PersistentVolumes with a StorageClass reclaim policy of DeleteStale or expired CertificateSigningRequests (CSRs)Nodes deleted in the following scenarios:On a cloud when the cluster uses a cloud controller managerOn-premises when the cluster uses an addon similar to a cloud controller managerNode Lease objectsOwners and dependentsMany objects in Kubernetes link to each other through owner references. Owner references tell the control plane which objects are dependent on others. Kubernetes uses owner references to give the control plane, and other API clients, the opportunity to clean up related resources before deleting an object. In most cases, Kubernetes manages owner references automatically.Ownership is different from the labels and selectors mechanism that some resources also use. For example, consider a Service that creates EndpointSlice objects. The Service uses labels to allow the control plane to determine which EndpointSlice objects are used for that Service. In addition to the labels, each EndpointSlice that is managed on behalf of a Service has an owner reference. Owner references help different parts of Kubernetes avoid interfering with objects they don’t control.Note:Cross-namespace owner references are disallowed by design. Namespaced dependents can specify cluster-scoped or namespaced owners. A namespaced owner must exist in the same namespace as the dependent. If it does not, the owner reference is treated as absent, and the dependent is subject to deletion once all owners are verified absent.Cluster-scoped dependents can only specify cluster-scoped owners. In v1.20+, if a cluster-scoped dependent specifies a namespaced kind as an owner, it is treated as having an unresolvable owner reference, and is not able to be garbage collected.In v1.20+, if the garbage collector detects an invalid cross-namespace ownerReference, or a cluster-scoped dependent with an ownerReference referencing a namespaced kind, a warning Event with a reason of OwnerRefInvalidNamespace and an involvedObject of the invalid dependent is reported. You can check for that kind of Event by running kubectl get events -A --field-selector=reason=OwnerRefInvalidNamespace.Cascading deletionKubernetes checks for and deletes objects that no longer have owner references, like the pods left behind when you delete a ReplicaSet. When you delete an object, you can control whether Kubernetes deletes the object's dependents automatically, in a process called cascading deletion. There are two types of cascading deletion, as follows:Foreground cascading deletionBackground cascading deletionYou can also control how and when garbage collection deletes resources that have owner


Question: What is Garbage Collection?

Answer: G a r b a g e   c o l l e c t i o n   i s   a   c o l l e c t i v e   t e r m   f o r   t h e   v a r i o u s   m e c h a n i s m s   K u b e r n e t e s   u s e s   t o   c l e a n   u p   c l u s t e r   r e s o u r c e s .   T h i s   a l l o w s   t h e   c l e a n   u p   o f   r e s o u r c e s   l i k e   t h e   f o l l o w i n g :   T e r m i n a t e d   p o d s C o m p l e t e d   J o b s O b j e c t s   w i t h o u t   o w n e r   r e f e r e n c e s U n u s e d   c o n t a i n e r s   a n d   c o n t a i n e r   i m a g e s D y n a m i c a l l y   p r o v i s i o n e d   P e r s i s t e n t V o l u m e s   w i t h   a   S t o r a g e C l a s s   r e c l a i m   p o l i c y   o f   D e l e t e S t a l e   o r   e x p i r e d   C e r t i f i c a t e S i g n i n g R e q u e s t s   ( C S R s ) N o d e s   d e l e t e d   i n   t h e   f o l l o w i n g   s c e n a r i o s : O n   a   c l o u d   w h e n   t h e   c l u s t e r   u s e s   a   c l o u d   c o n t r o l l e r   m a n a g e r O n - p r e m i s e s   w h e n   t h e   c l u s t e r   u s e s   a n   a d d o n   s i m i l a r   t o   a   c l o u d   c o n t r o l l e r   m a n a g e r N o d e   L e a s e   o b j e c t s   O n   a   c l o u d   w h e n   t h e   c l u s t e r   u s e s   a   c l o u d   c o n t r o l l e r   m a n a g e r O n - p r e m i s e s   w h e n   t h e   c l u s t e r   u s e s   a n   a d d o n   s i m i l a r   t o   a   c l o u d   c o n t r o l l e r   m a n a g e r


Question: What is Owners and dependents?

Answer: M a n y   o b j e c t s   i n   K u b e r n e t e s   l i n k   t o   e a c h   o t h e r   t h r o u g h   o w n e r   r e f e r e n c e s .   O w n e r   r e f e r e n c e s   t e l l   t h e   c o n t r o l   p l a n e   w h i c h   o b j e c t s   a r e   d e p e n d e n t   o n   o t h e r s .   K u b e r n e t e s   u s e s   o w n e r   r e f e r e n c e s   t o   g i v e   t h e   c o n t r o l   p l a n e ,   a n d   o t h e r   A P I   c l i e n t s ,   t h e   o p p o r t u n i t y   t o   c l e a n   u p   r e l a t e d   r e s o u r c e s   b e f o r e   d e l e t i n g   a n   o b j e c t .   I n   m o s t   c a s e s ,   K u b e r n e t e s   m a n a g e s   o w n e r   r e f e r e n c e s   a u t o m a t i c a l l y .   O w n e r s h i p   i s   d i f f e r e n t   f r o m   t h e   l a b e l s   a n d   s e l e c t o r s   m e c h a n i s m   t h a t   s o m e   r e s o u r c e s   a l s o   u s e .   F o r   e x a m p l e ,   c o n s i d e r   a   S e r v i c e   t h a t   c r e a t e s   E n d p o i n t S l i c e   o b j e c t s .   T h e   S e r v i c e   u s e s   l a b e l s   t o   a l l o w   t h e   c o n t r o l   p l a n e   t o   d e t e r m i n e   w h i c h   E n d p o i n t S l i c e   o b j e c t s   a r e   u s e d   f o r   t h a t   S e r v i c e .   I n   a d d i t i o n   t o   t h e   l a b e l s ,   e a c h   E n d p o i n t S l i c e   t h a t   i s   m a n a g e d   o n   b e h a l f   o f   a   S e r v i c e   h a s   a n   o w n e r   r e f e r e n c e .   O w n e r   r e f e r e n c e s   h e l p   d i f f e r e n t   p a r t s   o f   K u b e r n e t e s   a v o i d   i n t e r f e r i n g   w i t h   o b j e c t s   t h e y   d o n ’ t   c o n t r o l .


Question: What is Note:?

Answer: C r o s s - n a m e s p a c e   o w n e r   r e f e r e n c e s   a r e   d i s a l l o w e d   b y   d e s i g n .   N a m e s p a c e d   d e p e n d e n t s   c a n   s p e c i f y   c l u s t e r - s c o p e d   o r   n a m e s p a c e d   o w n e r s .   A   n a m e s p a c e d   o w n e r   m u s t   e x i s t   i n   t h e   s a m e   n a m e s p a c e   a s   t h e   d e p e n d e n t .   I f   i t   d o e s   n o t ,   t h e   o w n e r   r e f e r e n c e   i s   t r e a t e d   a s   a b s e n t ,   a n d   t h e   d e p e n d e n t   i s   s u b j e c t   t o   d e l e t i o n   o n c e   a l l   o w n e r s   a r e   v e r i f i e d   a b s e n t .   C l u s t e r - s c o p e d   d e p e n d e n t s   c a n   o n l y   s p e c i f y   c l u s t e r - s c o p e d   o w n e r s .   I n   v 1 . 2 0 + ,   i f   a   c l u s t e r - s c o p e d   d e p e n d e n t   s p e c i f i e s   a   n a m e s p a c e d   k i n d   a s   a n   o w n e r ,   i t   i s   t r e a t e d   a s   h a v i n g   a n   u n r e s o l v a b l e   o w n e r   r e f e r e n c e ,   a n d   i s   n o t   a b l e   t o   b e   g a r b a g e   c o l l e c t e d .   I n   v 1 . 2 0 + ,   i f   t h e   g a r b a g e   c o l l e c t o r   d e t e c t s   a n   i n v a l i d   c r o s s - n a m e s p a c e   o w n e r R e f e r e n c e ,   o r   a   c l u s t e r - s c o p e d   d e p e n d e n t   w i t h   a n   o w n e r R e f e r e n c e   r e f e r e n c i n g   a   n a m e s p a c e d   k i n d ,   a   w a r n i n g   E v e n t   w i t h   a   r e a s o n   o f   O w n e r R e f I n v a l i d N a m e s p a c e   a n d   a n   i n v o l v e d O b j e c t   o f   t h e   i n v a l i d   d e p e n d e n t   i s   r e p o r t e d .   Y o u   c a n   c h e c k   f o r   t h a t   k i n d   o f   E v e n t   b y   r u n n i n g   k u b e c t l   g e t   e v e n t s   - A   - - f i e l d - s e l e c t o r = r e a s o n = O w n e r R e f I n v a l i d N a m e s p a c e .


Question: What is Cascading deletion?

Answer: K u b e r n e t e s   c h e c k s   f o r   a n d   d e l e t e s   o b j e c t s   t h a t   n o   l o n g e r   h a v e   o w n e r   r e f e r e n c e s ,   l i k e   t h e   p o d s   l e f t   b e h i n d   w h e n   y o u   d e l e t e   a   R e p l i c a S e t .   W h e n   y o u   d e l e t e   a n   o b j e c t ,   y o u   c a n   c o n t r o l   w h e t h e r   K u b e r n e t e s   d e l e t e s   t h e   o b j e c t ' s   d e p e n d e n t s   a u t o m a t i c a l l y ,   i n   a   p r o c e s s   c a l l e d   c a s c a d i n g   d e l e t i o n .   T h e r e   a r e   t w o   t y p e s   o f   c a s c a d i n g   d e l e t i o n ,   a s   f o l l o w s :   F o r e g r o u n d   c a s c a d i n g   d e l e t i o n B a c k g r o u n d   c a s c a d i n g   d e l e t i o n   Y o u   c a n   a l s o   c o n t r o l   h o w   a n d   w h e n   g a r b a g e   c o l l e c t i o n   d e l e t e s   r e s o u r c e s   t h a t   h a v e   o w n e r   r e f e r e n c e s   u s i n g   K u b e r n e t e s   f i n a l i z e r s .