Shoot

1 - Accessing Shoot Clusters

Accessing Shoot Clusters

After creation of a shoot cluster, end-users require a kubeconfig to access it. There are several options available to get to such kubeconfig.

shoots/adminkubeconfig Subresource

The shoots/adminkubeconfig subresource allows users to dynamically generate temporary kubeconfigs that can be used to access shoot cluster with cluster-admin privileges. The credentials associated with this kubeconfig are client certificates which have a very short validity and must be renewed before they expire (by calling the subresource endpoint again).

The username associated with such kubeconfig will be the same which is used for authenticating to the Gardener API. Apart from this advantage, the created kubeconfig will not be persisted anywhere.

In order to request such a kubeconfig, you can run the following commands (targeting the garden cluster):

export NAMESPACE=garden-my-namespace
export SHOOT_NAME=my-shoot
export KUBECONFIG=<kubeconfig for garden cluster>  # can be set using "gardenctl target --garden <landscape>"
kubectl create \
    -f <(printf '{"spec":{"expirationSeconds":600}}') \
    --raw /apis/core.gardener.cloud/v1beta1/namespaces/${NAMESPACE}/shoots/${SHOOT_NAME}/adminkubeconfig | \
    jq -r ".status.kubeconfig" | \
    base64 -d

You also can use controller-runtime client (>= v0.14.3) to create such a kubeconfig from your go code like so:

expiration := 10 * time.Minute
expirationSeconds := int64(expiration.Seconds())
adminKubeconfigRequest := &authenticationv1alpha1.AdminKubeconfigRequest{
  Spec: authenticationv1alpha1.AdminKubeconfigRequestSpec{
    ExpirationSeconds: &expirationSeconds,
  },
}
err := client.SubResource("adminkubeconfig").Create(ctx, shoot, adminKubeconfigRequest)
if err != nil {
  return err
}
config = adminKubeconfigRequest.Status.Kubeconfig

In Python, you can use the native kubernetes client to create such a kubeconfig like this:

# This script first loads an existing kubeconfig from your system, and then sends a request to the Gardener API to create a new kubeconfig for a shoot cluster. 
# The received kubeconfig is then decoded and a new API client is created for interacting with the shoot cluster.

import base64
import json
from kubernetes import client, config
import yaml

# Set configuration options
shoot_name="my-shoot" # Name of the shoot
project_namespace="garden-my-namespace" # Namespace of the project

# Load kubeconfig from default ~/.kube/config
config.load_kube_config()
api = client.ApiClient()

# Create kubeconfig request
kubeconfig_request = {
    'apiVersion': 'authentication.gardener.cloud/v1alpha1',
    'kind': 'AdminKubeconfigRequest',
    'spec': {
      'expirationSeconds': 600
    }
}

response = api.call_api(resource_path=f'/apis/core.gardener.cloud/v1beta1/namespaces/{project_namespace}/shoots/{shoot_name}/adminkubeconfig',
                        method='POST',
                        body=kubeconfig_request,
                        auth_settings=['BearerToken'],
                        _preload_content=False,
                        _return_http_data_only=True,
                       )

decoded_kubeconfig = base64.b64decode(json.loads(response.data)["status"]["kubeconfig"]).decode('utf-8')
print(decoded_kubeconfig)

# Create an API client to interact with the shoot cluster
shoot_api_client = config.new_client_from_config_dict(yaml.safe_load(decoded_kubeconfig))
v1 = client.CoreV1Api(shoot_api_client)

Note: The gardenctl-v2 tool simplifies targeting shoot clusters. It automatically downloads a kubeconfig that uses the gardenlogin kubectl auth plugin. This transparently manages authentication and certificate renewal without containing any credentials.

shoots/viewerkubeconfig Subresource

The shoots/viewerkubeconfig subresource works similar to the shoots/adminkubeconfig. The difference is that it returns a kubeconfig with read-only access for all APIs except the core/v1.Secret API and the resources which are specified in the spec.kubernetes.kubeAPIServer.encryptionConfig field in the Shoot (see this document).

In order to request such a kubeconfig, you can run follow almost the same code as above - the only difference is that you need to use the viewerkubeconfig subresource. For example, in bash this looks like this:

export NAMESPACE=garden-my-namespace
export SHOOT_NAME=my-shoot
kubectl create \
    -f <(printf '{"spec":{"expirationSeconds":600}}') \
    --raw /apis/core.gardener.cloud/v1beta1/namespaces/${NAMESPACE}/shoots/${SHOOT_NAME}/viewerkubeconfig | \
    jq -r ".status.kubeconfig" | \
    base64 -d

The examples for other programming languages are similar to the above and can be adapted accordingly.

OpenID Connect

The kube-apiserver of shoot clusters can be provided with OpenID Connect configuration via the Shoot spec:

apiVersion: core.gardener.cloud/v1beta1
kind: Shoot
...
spec:
  kubernetes:
    oidcConfig:
      ...

It is the end-user’s responsibility to incorporate the OpenID Connect configurations in the kubeconfig for accessing the cluster (i.e., Gardener will not automatically generate the kubeconfig based on these OIDC settings). The recommended way is using the kubectl plugin called kubectl oidc-login for OIDC authentication.

If you want to use the same OIDC configuration for all your shoots by default, then you can use the ClusterOpenIDConnectPreset and OpenIDConnectPreset API resources. They allow defaulting the .spec.kubernetes.kubeAPIServer.oidcConfig fields for newly created Shoots such that you don’t have to repeat yourself every time (similar to PodPreset resources in Kubernetes). ClusterOpenIDConnectPreset specified OIDC configuration applies to Projects and Shoots cluster-wide (hence, only available to Gardener operators), while OpenIDConnectPreset is Project-scoped. Shoots have to “opt-in” for such defaulting by using the oidc=enable label.

For further information on (Cluster)OpenIDConnectPreset, refer to ClusterOpenIDConnectPreset and OpenIDConnectPreset.

For shoots with Kubernetes version >= 1.30, which have StructuredAuthenticationConfiguration feature gate enabled (enabled by default), it is advised to use Structured Authentication instead of configuring .spec.kubernetes.kubeAPIServer.oidcConfig. If oidcConfig is configured, it is translated into an AuthenticationConfiguration file to use for Structured Authentication configuration

Structured Authentication

For shoots with Kubernetes version >= 1.30, which have StructuredAuthenticationConfiguration feature gate enabled (enabled by default), kube-apiserver of shoot clusters can be provided with Structured Authentication configuration via the Shoot spec:

apiVersion: core.gardener.cloud/v1beta1
kind: Shoot
...
spec:
  kubernetes:
    kubeAPIServer:
      structuredAuthentication:
        configMapName: name-of-configmap-containing-authentication-config

The configMapName references a user created ConfigMap in the project namespace containing the AuthenticationConfiguration in it’s config.yaml data field. Here is an example of such ConfigMap:

apiVersion: v1
kind: ConfigMap
metadata:
  name: name-of-configmap-containing-authentication-config
  namespace: garden-my-project
data:
  config.yaml: |
    apiVersion: apiserver.config.k8s.io/v1beta1
    kind: AuthenticationConfiguration
    jwt:
    - issuer:
        url: https://issuer1.example.com
        audiences:
        - audience1
        - audience2
      claimMappings:
        username:
          expression: 'claims.username'
        groups:
          expression: 'claims.groups'
        uid:
          expression: 'claims.uid'
      claimValidationRules:
        expression: 'claims.hd == "example.com"'
        message: "the hosted domain name must be example.com"    

The user is responsible for the validity of the configured JWTAuthenticators.

Static Token kubeconfig

Note: Static token kubeconfig is not available for Shoot clusters using Kubernetes version >= 1.27. The shoots/adminkubeconfig subresource should be used instead.

This kubeconfig contains a static token and provides cluster-admin privileges. It is created by default and persisted in the <shoot-name>.kubeconfig secret in the project namespace in the garden cluster.

apiVersion: core.gardener.cloud/v1beta1
kind: Shoot
...
spec:
  kubernetes:
    enableStaticTokenKubeconfig: true
...

It is not the recommended method to access the shoot cluster, as the static token kubeconfig has some security flaws associated with it:

• The static token in the kubeconfig doesn’t have any expiration date. Read Credentials Rotation for Shoot Clusters to learn how to rotate the static token.
• The static token doesn’t have any user identity associated with it. The user in that token will always be system:cluster-admin, irrespective of the person accessing the cluster. Hence, it is impossible to audit the events in cluster.

When the enableStaticTokenKubeconfig field is not explicitly set in the Shoot spec:

• for Shoot clusters using Kubernetes version < 1.26, the field is defaulted to true.
• for Shoot clusters using Kubernetes version >= 1.26, the field is defaulted to false.

Note: Starting with Kubernetes 1.27, the enableStaticTokenKubeconfig field will be locked to false.

2 - Shoot Cluster Purposes

Shoot Cluster Purpose

The Shoot resource contains a .spec.purpose field indicating how the shoot is used, whose allowed values are as follows:

• evaluation (default): Indicates that the shoot cluster is for evaluation scenarios.
• development: Indicates that the shoot cluster is for development scenarios.
• testing: Indicates that the shoot cluster is for testing scenarios.
• production: Indicates that the shoot cluster is for production scenarios.
• infrastructure: Indicates that the shoot cluster is for infrastructure scenarios (only allowed for shoots in the garden namespace).

Behavioral Differences

The following enlists the differences in the way the shoot clusters are set up based on the selected purpose:

• testing shoot clusters do not get a monitoring or a logging stack as part of their control planes.
• for production and infrastructure shoot clusters auto-scaling scale down of the main ETCD is disabled.

There are also differences with respect to how testing shoots are scheduled after creation, please consult the Scheduler documentation.

Future Steps

We might introduce more behavioral difference depending on the shoot purpose in the future. As of today, there are no plans yet.

3 - Shoot Hibernation

Shoot Hibernation

Clusters are only needed 24 hours a day if they run productive workload. So whenever you do development in a cluster, or just use it for tests or demo purposes, you can save a lot of money if you scale-down your Kubernetes resources whenever you don’t need them. However, scaling them down manually can become time-consuming the more resources you have.

Gardener offers a clever way to automatically scale-down all resources to zero: cluster hibernation. You can either hibernate a cluster by pushing a button, or by defining a hibernation schedule.

To save costs, it’s recommended to define a hibernation schedule before the creation of a cluster. You can hibernate your cluster or wake up your cluster manually even if there’s a schedule for its hibernation.

• Hibernate a Cluster
  • What Is Hibernation?
  • What Isn’t Affected by the Hibernation?
  • Hibernate Your Cluster Manually
  • Wake Up Your Cluster Manually
  • Create a Schedule to Hibernate Your Cluster

What Is Hibernation?

When a cluster is hibernated, Gardener scales down the worker nodes and the cluster’s control plane to free resources at the IaaS provider. This affects:

• Your workload, for example, pods, deployments, custom resources.
• The virtual machines running your workload.
• The resources of the control plane of your cluster.

What Isn’t Affected by the Hibernation?

To scale up everything where it was before hibernation, Gardener doesn’t delete state-related information, that is, information stored in persistent volumes. The cluster state as persistent in etcd is also preserved.

Hibernate Your Cluster Manually

The .spec.hibernation.enabled field specifies whether the cluster needs to be hibernated or not. If the field is set to true, the cluster’s desired state is to be hibernated. If it is set to false or not specified at all, the cluster’s desired state is to be awakened.

To hibernate your cluster, you can run the following kubectl command:

$ kubectl patch shoot -n $NAMESPACE $SHOOT_NAME -p '{"spec":{"hibernation":{"enabled": true}}}'

Wake Up Your Cluster Manually

To wake up your cluster, you can run the following kubectl command:

$ kubectl patch shoot -n $NAMESPACE $SHOOT_NAME -p '{"spec":{"hibernation":{"enabled": false}}}'

Create a Schedule to Hibernate Your Cluster

You can specify a hibernation schedule to automatically hibernate/wake up a cluster.

Let’s have a look into the following example:

  hibernation:
    enabled: false
    schedules:
    - start: "0 20 * * *" # Start hibernation every day at 8PM
      end: "0 6 * * *"    # Stop hibernation every day at 6AM
      location: "America/Los_Angeles" # Specify a location for the cron to run in

The above section configures a hibernation schedule that hibernates the cluster every day at 08:00 PM and wakes it up at 06:00 AM. The start or end fields can be omitted, though at least one of them has to be specified. Hence, it is possible to configure a hibernation schedule that only hibernates or wakes up a cluster. The location field is the time location used to evaluate the cron expressions.

4 - Shoot Info Configmap

Shoot Info ConfigMap

Overview

The gardenlet maintains a ConfigMap inside the Shoot cluster that contains information about the cluster itself. The ConfigMap is named shoot-info and located in the kube-system namespace.

Fields

The following fields are provided:

apiVersion: v1
kind: ConfigMap
metadata:
  name: shoot-info
  namespace: kube-system
data:
  domain: crazy-botany.core.my-custom-domain.com     # .spec.dns.domain field from the Shoot resource
  extensions: foobar,foobaz                          # List of extensions that are enabled
  kubernetesVersion: 1.25.4                          # .spec.kubernetes.version field from the Shoot resource
  maintenanceBegin: 220000+0100                      # .spec.maintenance.timeWindow.begin field from the Shoot resource
  maintenanceEnd: 230000+0100                        # .spec.maintenance.timeWindow.end field from the Shoot resource
  nodeNetwork: 10.250.0.0/16                         # .spec.networking.nodes field from the Shoot resource
  podNetwork: 100.96.0.0/11                          # .spec.networking.pods field from the Shoot resource
  projectName: dev                                   # .metadata.name of the Project
  provider: <some-provider-name>                     # .spec.provider.type field from the Shoot resource
  region: europe-central-1                           # .spec.region field from the Shoot resource
  serviceNetwork: 100.64.0.0/13                      # .spec.networking.services field from the Shoot resource
  shootName: crazy-botany                            # .metadata.name from the Shoot resource

5 - Shoot Maintenance

Shoot Maintenance

Shoots configure a maintenance time window in which Gardener performs certain operations that may restart the control plane, roll out the nodes, result in higher network traffic, etc. A summary of what was changed in the last maintenance time window in shoot specification is kept in the shoot status .status.lastMaintenance field.

This document outlines what happens during a shoot maintenance.

Time Window

Via the .spec.maintenance.timeWindow field in the shoot specification, end-users can configure the time window in which maintenance operations are executed. Gardener runs one maintenance operation per day in this time window:

spec:
  maintenance:
    timeWindow:
      begin: 220000+0100
      end: 230000+0100

The offset (+0100) is considered with respect to UTC time. The minimum time window is 30m and the maximum is 6h.

⚠️ Please note that there is no guarantee that a maintenance operation that, e.g., starts a node roll-out will finish within the time window. Especially for large clusters, it may take several hours until a graceful rolling update of the worker nodes succeeds (also depending on the workload and the configured pod disruption budgets/termination grace periods).

Internally, Gardener is subtracting 15m from the end of the time window to (best-effort) try to finish the maintenance until the end is reached, however, this might not work in all cases.

If you don’t specify a time window, then Gardener will randomly compute it. You can change it later, of course.

Automatic Version Updates

The .spec.maintenance.autoUpdate field in the shoot specification allows you to control how/whether automatic updates of Kubernetes patch and machine image versions are performed. Machine image versions are updated per worker pool.

spec:
  maintenance:
    autoUpdate:
      kubernetesVersion: true
      machineImageVersion: true

During the daily maintenance, the Gardener Controller Manager updates the Shoot’s Kubernetes and machine image version if any of the following criteria applies:

• There is a higher version available and the Shoot opted-in for automatic version updates.
• The currently used version is expired.

The target version for machine image upgrades is controlled by the updateStrategy field for the machine image in the CloudProfile. Allowed update strategies are patch, minor and major.

Gardener (gardener-controller-manager) populates the lastMaintenance field in the Shoot status with the maintenance results.

Last Maintenance:
    Description:     "All maintenance operations successful. Control Plane: Updated Kubernetes version from 1.26.4 to 1.27.1. Reason: Kubernetes version expired - force update required"
    State:           Succeeded
    Triggered Time:  2023-07-28T09:07:27Z

Additionally, Gardener creates events with the type MachineImageVersionMaintenance or KubernetesVersionMaintenance on the Shoot describing the action performed during maintenance, including the reason why an update has been triggered.

LAST SEEN   TYPE      REASON                           OBJECT          MESSAGE
30m         Normal    MachineImageVersionMaintenance   shoot/local     Worker pool "local": Updated image from 'gardenlinux' version 'xy' to version 'abc'. Reason: Automatic update of the machine image version is configured (image update strategy: major).

30m         Normal    KubernetesVersionMaintenance     shoot/local     Control Plane: Updated Kubernetes version from "1.26.4" to "1.27.1". Reason: Kubernetes version expired - force update required.

15m         Normal    KubernetesVersionMaintenance     shoot/local     Worker pool "local": Updated Kubernetes version '1.26.3' to version '1.27.1'. Reason: Kubernetes version expired - force update required.

If at least one maintenance operation fails, the lastMaintenance field in the Shoot status is set to Failed:

Last Maintenance:
  Description:     "(1/2) maintenance operations successful: Control Plane: Updated Kubernetes version from 1.26.4 to 1.27.1. Reason: Kubernetes version expired - force update required, Worker pool x: 'gardenlinux' machine image version maintenance failed. Reason for update: machine image version expired"
  FailureReason:   "Worker pool x: either the machine image 'gardenlinux' is reaching end of life and migration to another machine image is required or there is a misconfiguration in the CloudProfile."
  State:           Failed
  Triggered Time:  2023-07-28T09:07:27Z

Please refer to the Shoot Kubernetes and Operating System Versioning in Gardener topic for more information about Kubernetes and machine image versions in Gardener.

Cluster Reconciliation

Gardener administrators/operators can configure the gardenlet in a way that it only reconciles shoot clusters during their maintenance time windows. This behaviour is not controllable by end-users but might make sense for large Gardener installations. Concretely, your shoot will be reconciled regularly during its maintenance time window. Outside of the maintenance time window it will only reconcile if you change the specification or if you explicitly trigger it, see also Trigger Shoot Operations.

Confine Specification Changes/Updates Roll Out

Via the .spec.maintenance.confineSpecUpdateRollout field you can control whether you want to make Gardener roll out changes/updates to your shoot specification only during the maintenance time window. It is false by default, i.e., any change to your shoot specification triggers a reconciliation (even outside of the maintenance time window). This is helpful if you want to update your shoot but don’t want the changes to be applied immediately. One example use-case would be a Kubernetes version upgrade that you want to roll out during the maintenance time window. Any update to the specification will not increase the .metadata.generation of the Shoot, which is something you should be aware of. Also, even if Gardener administrators/operators have not enabled the “reconciliation in maintenance time window only” configuration (as mentioned above), then your shoot will only reconcile in the maintenance time window. The reason is that Gardener cannot differentiate between create/update/reconcile operations.

⚠️ If confineSpecUpdateRollout=true, please note that if you change the maintenance time window itself, then it will only be effective after the upcoming maintenance.

⚠️ As exceptions to the above rules, manually triggered reconciliations and changes to the .spec.hibernation.enabled field trigger immediate rollouts. I.e., if you hibernate or wake-up your shoot, or you explicitly tell Gardener to reconcile your shoot, then Gardener gets active right away.

Shoot Operations

In case you would like to perform a shoot credential rotation or a reconcile operation during your maintenance time window, you can annotate the Shoot with

maintenance.gardener.cloud/operation=<operation>

This will execute the specified <operation> during the next maintenance reconciliation. Note that Gardener will remove this annotation after it has been performed in the maintenance reconciliation.

⚠️ This is skipped when the Shoot’s .status.lastOperation.state=Failed. Make sure to retry your shoot reconciliation beforehand.

Special Operations During Maintenance

The shoot maintenance controller triggers special operations that are performed as part of the shoot reconciliation.

Infrastructure and DNSRecord Reconciliation

The reconciliation of the Infrastructure and DNSRecord extension resources is only demanded during the shoot’s maintenance time window. The rationale behind it is to prevent sending too many requests against the cloud provider APIs, especially on large landscapes or if a user has many shoot clusters in the same cloud provider account.

Restart Control Plane Controllers

Gardener operators can make Gardener restart/delete certain control plane pods during a shoot maintenance. This feature helps to automatically solve service denials of controllers due to stale caches, dead-locks or starving routines.

Please note that these are exceptional cases but they are observed from time to time. Gardener, for example, takes this precautionary measure for kube-controller-manager pods.

See Shoot Maintenance to see how extension developers can extend this behaviour.

Restart Some Core Addons

Gardener operators can make Gardener restart some core addons (at the moment only CoreDNS) during a shoot maintenance.

CoreDNS benefits from this feature as it automatically solve problems with clients stuck to single replica of the deployment and thus overloading it. Please note that these are exceptional cases but they are observed from time to time.

6 - Shoot Scheduling Profiles

Shoot Scheduling Profiles

This guide describes the available scheduling profiles and how they can be configured in the Shoot cluster. It also clarifies how a custom scheduling profile can be configured.

Scheduling Profiles

The scheduling process in the kube-scheduler happens in a series of stages. A scheduling profile allows configuring the different stages of the scheduling.

As of today, Gardener supports two predefined scheduling profiles:

• balanced (default)

  Overview

  The balanced profile attempts to spread Pods evenly across Nodes to obtain a more balanced resource usage. This profile provides the default kube-scheduler behavior.

  How it works?

  The kube-scheduler is started without any profiles. In such case, by default, one profile with the scheduler name default-scheduler is created. This profile includes the default plugins. If a Pod doesn’t specify the .spec.schedulerName field, kube-apiserver sets it to default-scheduler. Then, the Pod gets scheduled by the default-scheduler accordingly.

• bin-packing

  Overview

  The bin-packing profile scores Nodes based on the allocation of resources. It prioritizes Nodes with the most allocated resources. By favoring the Nodes with the most allocation, some of the other Nodes become under-utilized over time (because new Pods keep being scheduled to the most allocated Nodes). Then, the cluster-autoscaler identifies such under-utilized Nodes and removes them from the cluster. In this way, this profile provides a greater overall resource utilization (compared to the balanced profile).

  Note: The decision of when to remove a Node is a trade-off between optimizing for utilization or the availability of resources. Removing under-utilized Nodes improves cluster utilization, but new workloads might have to wait for resources to be provisioned again before they can run.

  How it works?

  The kube-scheduler is configured with the following bin packing profile:

  apiVersion: kubescheduler.config.k8s.io/v1beta3
  kind: KubeSchedulerConfiguration
  profiles:
  - schedulerName: bin-packing-scheduler
    pluginConfig:
    - name: NodeResourcesFit
      args:
        scoringStrategy:
          type: MostAllocated
    plugins:
      score:
        disabled:
        - name: NodeResourcesBalancedAllocation
  

  To impose the new profile, a MutatingWebhookConfiguration is deployed in the Shoot cluster. The MutatingWebhookConfiguration intercepts CREATE operations for Pods and sets the .spec.schedulerName field to bin-packing-scheduler. Then, the Pod gets scheduled by the bin-packing-scheduler accordingly. Pods that specify a custom scheduler (i.e., having .spec.schedulerName different from default-scheduler and bin-packing-scheduler) are not affected.

Configuring the Scheduling Profile

The scheduling profile can be configured via the .spec.kubernetes.kubeScheduler.profile field in the Shoot:

spec:
  # ...
  kubernetes:
    kubeScheduler:
      profile: "balanced" # or "bin-packing"

Custom Scheduling Profiles

The kube-scheduler’s component configs allows configuring custom scheduling profiles to match the cluster needs. As of today, Gardener supports only two predefined scheduling profiles. The profile configuration in the component config is quite expressive and it is not possible to easily define profiles that would match the needs of every cluster. Because of these reasons, there are no plans to add support for new predefined scheduling profiles. If a cluster owner wants to use a custom scheduling profile, then they have to deploy (and maintain) a dedicated kube-scheduler deployment in the cluster itself.

7 - Shoot Status

Shoot Status

This document provides an overview of the ShootStatus.

Conditions

The Shoot status consists of a set of conditions. A Condition has the following fields:

Currently, the available Shoot condition types are:

• APIServerAvailable
• ControlPlaneHealthy
• EveryNodeReady
• ObservabilityComponentsHealthy
• SystemComponentsHealthy

The Shoot conditions are maintained by the shoot care reconciler of the gardenlet. Find more information in the gardelent documentation.

Sync Period

The condition checks are executed periodically at an interval which is configurable in the GardenletConfiguration (.controllers.shootCare.syncPeriod, defaults to 1m).

Condition Thresholds

The GardenletConfiguration also allows configuring condition thresholds (controllers.shootCare.conditionThresholds). A condition threshold is the amount of time to consider a condition as Processing on condition status changes.

Let’s check the following example to get a better understanding. Let’s say that the APIServerAvailable condition of our Shoot is with status True. If the next condition check fails (for example kube-apiserver becomes unreachable), then the condition first goes to Processing state. Only if this state remains for condition threshold amount of time, then the condition is finally updated to False.

Constraints

Constraints represent conditions of a Shoot’s current state that constraint some operations on it. The current constraints are:

HibernationPossible:

This constraint indicates whether a Shoot is allowed to be hibernated. The rationale behind this constraint is that a Shoot can have ValidatingWebhookConfigurations or MutatingWebhookConfigurations acting on resources that are critical for waking up a cluster. For example, if a webhook has rules for CREATE/UPDATE Pods or Nodes and failurePolicy=Fail, the webhook will block joining Nodes and creating critical system component Pods and thus block the entire wakeup operation, because the server backing the webhook is not running.

Even if the failurePolicy is set to Ignore, high timeouts (>15s) can lead to blocking requests of control plane components. That’s because most control-plane API calls are made with a client-side timeout of 30s, so if a webhook has timeoutSeconds=30 the overall request might still fail as there is overhead in communication with the API server and potential other webhooks.

Generally, it’s best practice to specify low timeouts in WebhookConfigs.

As an effort to correct this common problem, the webhook remediator has been created. This is enabled by setting .controllers.shootCare.webhookRemediatorEnabled=true in the gardenlet’s configuration. This feature simply checks whether webhook configurations in shoot clusters match a set of rules described here. If at least one of the rules matches, it will change set status=False for the .status.constraints of type HibernationPossible and MaintenancePreconditionsSatisfied in the Shoot resource. In addition, the failurePolicy in the affected webhook configurations will be set from Fail to Ignore. Gardenlet will also add an annotation to make it visible to end-users that their webhook configurations were mutated and should be fixed/adapted according to the rules and best practices.

In most cases, you can avoid this by simply excluding the kube-system namespace from your webhook via the namespaceSelector:

apiVersion: admissionregistration.k8s.io/v1
kind: MutatingWebhookConfiguration
webhooks:
  - name: my-webhook.example.com
    namespaceSelector:
      matchExpressions:
      - key: gardener.cloud/purpose
        operator: NotIn
        values:
          - kube-system
    rules:
      - operations: ["*"]
        apiGroups: [""]
        apiVersions: ["v1"]
        resources: ["pods"]
        scope: "Namespaced"

However, some other resources (some of them cluster-scoped) might still trigger the remediator, namely:

• endpoints
• nodes
• clusterroles
• clusterrolebindings
• customresourcedefinitions
• apiservices
• certificatesigningrequests
• priorityclasses

If one of the above resources triggers the remediator, the preferred solution is to remove that particular resource from your webhook’s rules. You can also use the objectSelector to reduce the scope of webhook’s rules. However, in special cases where a webhook is absolutely needed for the workload, it is possible to add the remediation.webhook.shoot.gardener.cloud/exclude=true label to your webhook so that the remediator ignores it. This label should not be used to silence an alert, but rather to confirm that a webhook won’t cause problems. Note that all of this is no perfect solution and just done on a best effort basis, and only the owner of the webhook can know whether it indeed is problematic and configured correctly.

In a special case, if a webhook has a rule for CREATE/UPDATE lease resources in kube-system namespace, its timeoutSeconds is updated to 3 seconds. This is required to ensure the proper functioning of the leader election of essential control plane controllers.

You can also find more help from the Kubernetes documentation

MaintenancePreconditionsSatisfied:

This constraint indicates whether all preconditions for a safe maintenance operation are satisfied (see Shoot Maintenance for more information about what happens during a shoot maintenance). As of today, the same checks as in the HibernationPossible constraint are being performed (user-deployed webhooks that might interfere with potential rolling updates of shoot worker nodes). There is no further action being performed on this constraint’s status (maintenance is still being performed). It is meant to make the user aware of potential problems that might occur due to his configurations.

CACertificateValiditiesAcceptable:

This constraint indicates that there is at least one CA certificate which expires in less than 1y. It will not be added to the .status.constraints if there is no such CA certificate. However, if it’s visible, then a credentials rotation operation should be considered.

CRDsWithProblematicConversionWebhooks:

This constraint indicates that there is at least one CustomResourceDefinition in the cluster which has multiple stored versions and a conversion webhook configured. This could break the reconciliation flow of a Shoot cluster in some cases. See https://github.com/gardener/gardener/issues/7471 for more details. It will not be added to the .status.constraints if there is no such CRD. However, if it’s visible, then you should consider upgrading the existing objects to the current stored version. See Upgrade existing objects to a new stored version for detailed steps.

Last Operation

The Shoot status holds information about the last operation that is performed on the Shoot. The last operation field reflects overall progress and the tasks that are currently being executed. Allowed operation types are Create, Reconcile, Delete, Migrate, and Restore. Allowed operation states are Processing, Succeeded, Error, Failed, Pending, and Aborted. An operation in Error state is an operation that will be retried for a configurable amount of time (controllers.shoot.retryDuration field in GardenletConfiguration, defaults to 12h). If the operation cannot complete successfully for the configured retry duration, it will be marked as Failed. An operation in Failed state is an operation that won’t be retried automatically (to retry such an operation, see Retry failed operation).

Last Errors

The Shoot status also contains information about the last occurred error(s) (if any) during an operation. A LastError consists of identifier of the task returned error, human-readable message of the error and error codes (if any) associated with the error.

Error Codes

Known error codes and their classification are:

Please note: Errors classified as User error: true do not require a Gardener operator to resolve but can be remediated by the user (e.g. by refreshing expired infrastructure credentials). Even though ERR_INFRA_RATE_LIMITS_EXCEEDED and ERR_RETRYABLE_INFRA_DEPENDENCIES is mentioned as User error: false` operator can’t provide any resolution because it is related to cloud provider issue.

Status Label

Shoots will be automatically labeled with the shoot.gardener.cloud/status label. Its value might either be healthy, progressing, unhealthy or unknown depending on the .status.conditions, .status.lastOperation, and status.lastErrors of the Shoot. This can be used as an easy filter method to find shoots based on their “health” status.

8 - Shoot Supported Architectures

Supported CPU Architectures for Shoot Worker Nodes

Users can create shoot clusters with worker groups having virtual machines of different architectures. CPU architecture of each worker pool can be specified in the Shoot specification as follows:

Example Usage in a Shoot

spec:
  provider:
    workers:
    - name: cpu-worker
      machine:
        architecture: <some-cpu-architecture> # optional

If no value is specified for the architecture field, it defaults to amd64. For a valid shoot object, a machine type should be present in the respective CloudProfile with the same CPU architecture as specified in the Shoot yaml. Also, a valid machine image should be present in the CloudProfile that supports the required architecture specified in the Shoot worker pool.

Example Usage in a CloudProfile

spec:
  machineImages:
  - name: test-image
    versions:
    - architectures: # optional
      - <architecture-1>
      - <architecture-2>
      version: 1.2.3
  machineTypes:
  - architecture: <some-cpu-architecture>
    cpu: "2"
    gpu: "0"
    memory: 8Gi
    name: test-machine

Currently, Gardener supports two of the most widely used CPU architectures:

• amd64
• arm64

9 - Shoot Worker Nodes Settings

Shoot Worker Nodes Settings

Users can configure settings affecting all worker nodes via .spec.provider.workersSettings in the Shoot resource.

SSH Access

SSHAccess indicates whether the sshd.service should be running on the worker nodes. This is ensured by a systemd service called sshd-ensurer.service which runs every 15 seconds on each worker node. When set to true, the systemd service ensures that the sshd.service is unmasked, enabled and running. If it is set to false, the systemd service ensures that sshd.service is disabled, masked and stopped. This also terminates all established SSH connections on the host. In addition, when this value is set to false, existing Bastion resources are deleted during Shoot reconciliation and new ones are prevented from being created, SSH keypairs are not created/rotated, SSH keypair secrets are deleted from the Garden cluster, and the gardener-user.service is not deployed to the worker nodes.

sshAccess.enabled is set to true by default.

Example Usage in a Shoot

spec:
  provider:
    workersSettings:
      sshAccess:
        enabled: false

10 - Workerless `Shoot`s

Workerless Shoots

Starting from v1.71, users can create a Shoot without any workers, known as a “workerless Shoot”. Previously, worker nodes had to always be included even if users only needed the Kubernetes control plane. With workerless Shoots, Gardener will not create any worker nodes or anything related to them.

Here’s an example manifest for a local workerless Shoot:

apiVersion: core.gardener.cloud/v1beta1
kind: Shoot
metadata:
  name: local
  namespace: garden-local
spec:
  cloudProfile:
    name: local
  region: local
  provider:
    type: local
  kubernetes:
    version: 1.26.0

⚠️ It’s important to note that a workerless Shoot cannot be converted to a Shoot with workers or vice versa.

As part of the control plane, the following components are deployed in the seed cluster for workerless Shoot:

• etcds
• kube-apiserver
• kube-controller-manager
• gardener-resource-manager
• logging and monitoring components
• extension components (if they support workerless Shoots, see here)