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Kubernetes

Commercial

This ZenPack is developed and supported by Zenoss Inc. Commercial ZenPacks are available to Zenoss commercial customers only. Contact Zenoss to request more information regarding this or any other ZenPacks. Click here to view all available Zenoss Commercial ZenPacks.

Kubernetes ZenPack

This ZenPack provides system monitoring of Kubernetes (K8s) clusters.

Support

This ZenPack is included with commercial versions of Zenoss and enterprise support for this ZenPack is provided to Zenoss customers with an active subscription.

Releases

Version 1.2.0-Download
Released on December 6, 2021
Requires PythonCollector ZenPackZenPackLib ZenPack
Compatible with Zenoss Resource Manager 6.2 and Zenoss Cloud
Version 1.1.0-Download
Released on January 13, 2020
Requires PythonCollector ZenPack, ZenPackLib ZenPack
Compatible with Zenoss Resource Manager 6.2 and Zenoss Cloud

Contents

Background

This ZenPack monitors Kubernetes (K8s) clusters deployed on Google Cloud Platform (GKE), Amazon Web Services (EKS), Microsoft Azure (AKS),as well as on locally-hosted environments. It uses RBAC authentication to access all data related to modeling and monitoring.

Support Requirements

Zenoss:

  • Zenoss 6.2+
  • ZenPackLib ZenPack 2.1.0+

Kubernetes:

  • Kubernetes versions 1.9.X - 1.21.X
  • Kubernetes versions 1.17.X - 1.21.X deployed on Google Cloud Platform, GKE
  • Kubernetes versions 1.18.X - 1.21.X deployed on Amazon Web Services, EKS
  • Kubernetes versions 1.20.X - 1.22.X deployed on Microsoft Azure, AKS
  • Kubernetes versions 1.16.X - 1.21.X deployed on Local environment

    

Features

ZenPack features include:

  • Overall Cluster Health Monitoring
  • Health Monitoring for Nodes, Services, Pods
  • Graphs for Kubernetes Cluster, Nodes, Deployments, StatefulSets, Pods, Containers
  • Dashboard Portlets for Pod CPU and Memory consumption
  • Service Impact and root cause analysis
  • Event Management

Upgrade Notes

Version 1.2.0

When updating to version 1.2.0 monitoring of a new component StatefulSet was added. Similar to Services, Deployments, Pods, and Containers, StatefulSets can be selected for modeling using zKubernetesNamespaceFilter. In addition, a new zProperty called zKubernetesPodFilter was added to select Pods and Containers for modeling.

Please note that the generation of identifiers for Pods and Containers has been changed due to the improvements, therefore, after updating to version 1.2.0, the old monitoring data for Pods and Containers, collected before the update, will no longer be displayed on the component graphs.

Version 1.1.0

When updating to version 1.1.0 or later (from versions prior to 1.1.0), a new zProperty was added, zKubernetesNamespaceFilter, to filter Deployments, Services, Pods, and Containers based upon the namespace to which they belong. These four components link together, hence they all rely on the same zProperty. Further, the default behavior for most Kubernetes consoles hid components under the 'kube-system' namespace while displaying everything else. This behavior has been adopted by the 1.1.0 Kubernetes ZenPack; the zProerties zKubernetesNamespaceFilter and zKubernetesContainerNamesModeled may be updated during the upgrade process to reflect the new default behavior.

If the zKubernetesContainerNamesModeled was changed from the default value then the new value will not be updated, even if the value is 'kube-system/.*/.*'. In this situation, the property zKubernetesNamespaceFilter will have to be updated to allow 'kube-system'.

Service Impact relations may become out of sync when upgrading to 1.1.0. This issue should only affect instances where Service Impact is running. Service Impact can be manually corrected (after installation is complete) by running this command:

zenimpactgraph run --update

Kubernetes Structure and Discovery

Objects are automatically discovered via the Kubernetes API. The ZenPack class structure can be visualized in the diagram on the right:

The Kubernetes model will be automatically updated as changes are detected on the cluster. New and deleted Services, Deployments, StatefulSets, Pods, and Clusters will be updated as part of the regular monitoring cycle. Changes detected to Namespaces, Nodes, and PersistentVolumes will also be automatically updated. Because incremental modeling is conjoined with the Zenoss monitoring cycle, (default 5 minutes cycles,) it may take several minutes before the Zenoss Kubernetes model synchronizes with the Kubernetes Cluster.

Incremental modeling makes use of the Kubernetes Watch API to monitor for changes to K8s clusters by tracking the resourceVersion for each API endpoint. When a zenpython instance starts, the resourceVersion is set to '0' and the first monitoring cycle will jump the resourceVersion to the latest version. Occasionally, the resourceVersion may become 'Gone' (indicating that the resourceVersion is too old and no longer in the K8s history). In this situation, the resourceVersion is set back to '0' so it can again jump forward to the latest version. Due to these factors, it may take two cycles to fully synchronize the K8s model.

The following Kubernetes zProperties also affect incremental modeling:

  • zKubernetesContainerNamesModeled
  • zKubernetesContainerLabelsModeled
  • zKubernetesNamespaceFilter
  • ZKubernetesPodFilter

Changes to these properties may not be pick-up and applied until the next modeling cycle.

Device (Cluster)

  • Description: The device represents a single Kubernetes cluster.
  • Attributes:
    • buildDate
    • cluster_ip
    • cpu_capacity
    • cpu_usage
    • gcp_cluster
    • memory_capacity
    • memory_usage
    • platform
    • version
  • Relationships:
    • k8sNamespace
    • k8sNode
    • k8sPersistentVolume
  • Datasource/Datapoints:
    • event
    • metrics
      • cpu
      • memory
  • Graphs:
    • CPU Utilization
    • Memory Utilization
  • Capacity Thresholds:
    • CPU Capacity
    • Memory Capacity

Namespace

  • Description: Namespaces for Kubernetes.
  • Attributes:
    • container_count
    • namespace_uid
    • status
  • Relationships:
    • k8sService
    • k8sPod
    • k8sDeployments
    • k8sStatefulSet

Node

  • Description: Compute nodes that Kubernetes is build from.
  • Attributes:
    • architecture
    • cpu_allocatable
    • cpu_capacity
    • cpu_usage
    • ephemeral_storage_allocatable
    • ephemeral_storage_capacity
    • externalIP
    • guest_device
    • internalIP
    • kubeletVersion
    • manageIP
    • memory_allocatable
    • memory_capacity
    • memory_usage
    • modeled_cpu_allocatable
    • modeled_cpu_capacity
    • modeled_memory_allocatable
    • modeled_memory_capacity
    • node_hostname
    • node_type
    • node_uid
    • operatingSystem
    • pods_allocatable
    • pods_capacity
    • region
    • status
  • Relationships:
    • k8sCluster
    • k8sPod
  • Datasource/Datapoints:
    • status
      • status
    • metrics
      • cpu
      • memory
    • allocatable
      • cpu
      • memory
    • capacity
      • cpu
      • memory
  • Graphs:
    • CPU Utilization
    • Memory Utilization
  • Thresholds:
    • High Memory (default: disabled)
    • High CPU Load (default: disabled)

Persistent Volume

  • Description: Storage volume abstraction.
  • Attributes:
    • capacity
    • pvc_uid
    • status
    • storageClassName
  • Relationships:
    • k8sNamespace
  • Datasource/Datapoints:
    • status:
      • status

Service

  • Description: Kubernetes Services represent virtual services that are realized by Pods and Containers.
  • Attributes:
    • cluster_ip
    • container_count
    • port_list
    • selector
    • service_type
    • service_uid
  • Relationships:
    • k8sNamespace
    • k8sPods

Deployments

  • Description: Kubernetes Deployments control automation for Pods and Containers.
  • Attributes:
    • labels
    • created
  • Relationships:
    • k8sNamespace
    • k8sPods
  • Datasource/Datapoints:
    • replicas
    • availableReplicas
    • readyReplicas
    • unavailableReplicas
    • updatedReplicas
    • collisionCount
  • Graphs:
    • Replica Set
    • Collision Count
  • Thresholds:
    • Replica Count

StatefulSet

  • Description: StatefulSet controller for Kubernetes.
  • Attributes:
    • labels
    • created
  • Relationships:
    • k8sPod
    • k8sNamespace
  • Datasource/Datapoints:
    • replicas
    • currentReplicas
    • readyReplicas
    • updatedReplicas
    • collisionCount
  • Graphs:
    • Replica Set
    • Collision Count
  • Thresholds:
    • Replica Count

Pod

  • Description: A group of one or more containers with shared storage/network, and a specification for how to run the containers.
  • Attributes:
    • labels
    • pod_uid
    • status
  • Relationships:
    • k8sNamespace
    • k8sNode
    • k8sContainer
    • k8sDeployments
    • k8sStatefulSet
  • Datasource/Datapoints:
    • metrics:
      • cpu
      • memory
    • status:
      • status
  • Graphs:
    • CPU Usage
    • Memory Usage

Container

  • Description: Lowest compute abstraction element for Pods.
  • Attributes:
    • cpu_limits
    • cpu_requests
    • image
    • labels
    • memory_limits
    • memory_requests
  • Relationships:
    • k8sPod
  • Datasource/Datapoints:
    • metrics:
      • cpu
      • memory
  • Graphs:
    • CPU Usage
    • Memory Usage
    • Note: It is common for some containers to have only partial data for cpu/memory so it is natural that some of those graphs will be missing data.
  • Thresholds:
    • High CPU Load
    • High Memory

Dashboard Portlets

This ZenPack adds portlets that provide at-a-glance views into Pod and Cluster memory and CPU utilization. Portlets are viewed on the first page upon login, and can be added or removed using the dashboard and portlet controls.

Kubernetes Portlets

The following are portlets specific to Kubernetes:

  • Top K8s Pods by Memory
  • Top K8s Pods CPU

These two portlets can be filtered by:

  • Cluster
  • Namespace
  • Service

Platform Portlets

In addition to Memory and CPU, the following platform portlets support Kubernetes events and issues:

  • Device Issues
  • Event View
  • Open Events
  • Open Events Chart

Usage

RBAC Authentication

You must expose the Kubernetes V2 and metrics.k8s.io APIs on your system. We exclusively use Role-based access control (RBAC) for cluster API access. For more information see Using RBAC Authorization.

You generally must do at least the following steps for both GCP and locally installed Kubernetes systems:

  1. Set MY_PREFIX and capture ACCOUNT_ID and API_SERVER:

    MY_PREFIX=zenoss
    API_SERVER=$(kubectl cluster-info | head -1 | cut -d' ' -f6 | sed 's/\x1b\[[0-9;]*m//g')

    A. If using GKE deployed on the Google Cloud Platform, first ensure you are connected to the correct project associated with your cluster. Now find your ACCOUNT_ID:
        ACCOUNT_ID=$(gcloud info --format='value(config.account)')
    B. If using EKS deployed on the Amazon Web Services, first ensure you are connected to the correct project associated with your cluster. Now find your ACCOUNT_ID:
            ACCOUNT_ID=$(aws sts get-caller-identity --output text --query 'Account')
    C. If using AKS deployed on the Microsoft Azure, first ensure you are connected to the correct project associated with your cluster. Now find your ACCOUNT_ID:
            ACCOUNT_ID=$(az account show --query id --output tsv)
    D. If using locally-hosted Kubernetes, determine the ACCOUNT_ID and prepare the credentials as per Kubernetes Getting started.
    E. Alternative, setup tutorials for Kubernetes Scratch can be found via an internet search.

  2. Setup RBAC Authorization:

    kubectl create clusterrolebinding $MY_PREFIX-cluster-admin-binding --clusterrole=cluster-admin --user=$ACCOUNT_ID
  3. Grab the YAML from Appendix: Kubernetes RBAC Setup and save it to the file zenoss_rbac.yaml and use it to create the SA for the role:

    kubectl apply -f zenoss_rbac.yaml
  4. Get the secret Token and save it (adjusting zenoss-secret if required):

    TOKEN=$(kubectl describe secret zenoss-secret | sed -n '/^token/p' | cut -d' ' -f7)
    echo $TOKEN
  5. $TOKEN will be set to the zKubernetesClusterToken in the token section

  6. From the Infrastructure Add pull-down select Add Kubernetes Cluster

  7. Fill in the following fields:

    • Device Name
    • IP of K8s API ($API_SERVER from above)
    • TCP Port of API
    • Service Account
    • Token for Service Account ($TOKEN from above)
  8. Select the correct Collector for your system

  9. Hit the Add button

Kubernetes Batch Configuration

If you use Zenoss Service Dynamics, you can also add your devices in batch for convenience and automation.

  • Attach to the Zope container:

        serviced service attach zope
  • Create a text file (filename: /tmp/batch.txt) and replace $TOKEN with your token from above:

        /Devices/Kubernetes
        kubernets101 zKubernetesClusterIP='10.20.30.40', \
           zKubernetesPort="443", \
           zKubernetesServiceAccount='zenoss', \
           zKubernetesClusterToken='$TOKEN'
  • Now run the zenbatchload command:

        zenbatchload  /tmp/batch.txt
  • The device should now load and model automatically

Adding a Custom Datasource to Metrics

In order to add a metrics datasource, you must be familiar with the API target you wish to call and the resulting JSON data response.

The metrics datasource provided requires three configuration parameters, which we describe below:

  1. api_target: The API target that gets appended to the metrics base API URL
  2. data_path: The path through the returned JSON that identifies the metric
  3. aggregator: Method to aggregate values returned by apt_target and data_path.

Together, the api_target and data_path provide the complete information for the datasource to acquire the requested data.
The aggregator provides the method to put that data together to form a single data value.

api_target

The api_target must be a valid path for the API. It must be in a plain REST GET format.

<string1>/<string2>/<string3>

where each <string*> must be a valid string defined in the API.
Examples:

api/v1/nodes
api/v1/pods
apis/metrics.k8s.io/v1beta1/nodes
apis/metrics.k8s.io/v1beta1/pods

These examples supply the entire API path beyond the base URL, and are required. More information can be found in Resource metrics pipeline.

data_path

The data_path string represents a path through the returned JSON data that loosely follows the jq style format which separates path elements (dictionary keys) by dots.
It can include the following items:

  • Plain jq strings. For example: a.b
  • Strings with square brackets with a jq-style identifier:

    items[metadata.name]

    This example will scan all list elements in items and select the meta.name element from those items.
    To clarify, this will match all items that have the JSON key metadata with sub-key name.
    Note that this element is not useful on its own unless items[metadata.name] filters items and selects out only those which have metadata.name structure.

  • Strings with square brackets with a value-qualified jq-styled identifier. This allows you to filter list items that match a dictionary key or value.
    Examples:

    items[metadata.name=server7]
    items[metadata.name=server7].usage
    items[metadata.name=${here/title}].usage
    items[metadata.name=${here/title}].status.capacity

    Note that the last two examples show that you can use dynamic TALES expressions instead of static strings to filter the items elements by value.
    Also note that the last three examples specify the path to the metric that matches the item list elements in square brackets.

aggregator

The required aggregator is selected from the drop-down. Choose from:

  • AVERAGE: Average all elements
  • FIRST: Choose the first element only
  • MAX: Select the maximum value
  • MIN: Select the minimum value
  • PERCENT_AVERAGE: Return average of the data multiplied by 100
  • PERCENT_SUM: Return sum of the data multiplied by 100
  • SUM_OR_ZERO: Sum the data, return zero if no data exists
  • SUM: Sum all the data

Installed Items

Installing this ZenPack will add the following items to your Zenoss system:

Configuration and zProperties

The zProperties and default settings are as follows:

  • zKubernetesClusterIP: The IP address of the Kubernetes Cluster API.
  • zKubernetesClusterName: Name of cluster used for association with related resources.
  • zKubernetesPort: The TCP port of the API.
    • Default value: 443
  • zKubernetesServiceAccount: The Kubernetes service account associated with the API account. See kubectl get serviceaccounts for more information.
  • zKubernetesClusterToken: The token associated with zKubernetesServiceAccount. See kubectl describe secrets for more information.
  • zKubernetesGuestUseExternalIP: Boolean to set the manageIp to the external IP for host monitoring. This property should be set to False If guest device of EC2 account is modeled by an internal IP in order to have links to Kubernetes Guest devices.
    • Default value: True
  • zKubernetesEventInterval: Polling interval for events.
    • Default value: 60
  • zKubernetesMonitoringInterval: Polling interval for metrics collection.
    • Default value: 300
  • zKubernetesStatusInterval: Polling interval for status updates.
    • Default value: 300
  • zKubernetesContainerNamesModeled: RegEx Pattern of Container names to model. Note that only Containers which are members of Pods that match the zKubernetesNamespaceFilter and zKubernetesPodFilter patterns may be captured. Containers that belong to Pods that are not modeled will also not be modeled. If kept blank, then no containers which satisfy zKubernetesContainerNamesModeled pattern will be modeled.
    • Format: regex
    • Default value: [".*"]
  • zKubernetesContainerLabelsModeled: Container labels to model. If both zKubernetesContainerLabelsModeled and zKubernetesContainerNamesModeled are set, then all containers that match at least one property will be listed, (i.e. Venn diagram union).
    • Format: key: value
    • Default value: [""]
  • zKubernetesPodFilter: Pattern for Pods to model and monitor. This affects the modeling and monitoring of Pods and Containers related to them. By default, all Pods and Containers are allowed to be modeled and monitored. If left blank, then no components will not be modeled.
    • Format: regex
    • Default value: [".*"]
  • zKubernetesNamespaceFilter: Pattern for namespaces to model and monitor. This affects the modeling and monitoring of Services, Deployments, StatefulSets, Pods and Containers. By default, only non-system (components not in namespace 'kube-system') will be watched. If left blank, then no components will not be modeled.
    • Format: regex
    • Default value: ["^((?!kube-system).)*$"]

Device Modeling Configuration

Some zProperties, noted above, can affect the application of other properties during modeling of a device, i.e.:

  • zKubernetesNamespaceFilter can affect:
    • zKubernetesPodFilter
    • zKubernetesContainerNamesModeled
    • zKubernetesContainerLabelsModeled
  • zKubernetesPodFilter can affect:
    • zKubernetesContainerNamesModeled
    • zKubernetesContainerLabelsModeled
  • zKubernetesContainerNamesModeled can affect:
    • zKubernetesContainerLabelsModeled
  • zKubernetesContainerLabelsModeled can affect:
    • zKubernetesContainerNamesModeled

To configure the modeling of Kubernetes Cluster components use the following combination of zProperties:

  1. zKubernetesNamespaceFilter: All Deployments, StatefulSets, and Services, which belong to Namespaces, that are not specified by `zKubernetesNamespaceFilter` pattern will not be modeled. All Pods and Containers that belong to Namespaces, which are not specified by `zKubernetesNamespaceFilter` pattern will not be modeled even if they are specified by `zKubernetesPodFilter`, `zKubernetesContainerNamesModeled`, and `zKubernetesContainerLabelsModeled`.

  2. zKubernetesPodFilter: All Pods which belong to Namespaces specified by zKubernetesNamespaceFilter pattern and are not specified by zKubernetesPodFilter will not be modeled. Containers related to Pods allowed to model by zKubernetesNamespaceFilter will not be modeled if these Pods are not allowed to model by zKubernetesPodFilter even if the corresponding Containers are specified by zKubernetesContainerNamesModeled and zKubernetesContainerLabelsModeled.

  3. zKubernetesContainerNamesModeled: All Containers allowed for modeling by zKubernetesNamespaceFilter and zKubernetesPodFilter will not be modeled if they are not allowed by zKubernetesContainerNamesModeled, however, if they are allowed by zKubernetesContainerLabelsModeled they will be modeled.

  4. zKubernetesContainerLabelsModeled: All Containers allowed for modeling by zKubernetesNamespaceFilter and zKubernetesPodFilter will not be modeled if they are not allowed by zKubernetesContainerLabelsModeled, however, if they are allowed by zKubernetesContainerNamesModeled they will be modeled.

  5. zKubernetesContainerNamesModeled + zKubernetesContainerLabelsModeled: All Containers allowed for modeling by zKubernetesNamespaceFilter and zKubernetesPodFilter will be modeled if they are allowed by zKubernetesContainerLabelsModeled and zKubernetesContainerNamesModeled. This option provides an opportunity to mix approaches for the selection of Containers, which should be modeled, using their names and labels.

Common values for filter zProperties

Common values for zKubernetesNamespaceFilter, zKubernetesPodFilter, and zKubernetesContainerNamesModeled:

  • [""] - no components will be selected for the modeling.
  • [".*"] - all available components will be selected for the modeling.
  • ["default|test"] - all components related to default and test will be selected for the modeling.
  • ["^((?!pod-1).)*$"] - all containers which do not relate to pod-1 will be selected for the modeling.

Common values for zKubernetesContainerLabelsModeled:

  • [""] - no components will be selected for the modeling.
  • ["app: mysql|app: redis"] - containers which have a label mysql or redis will be selected for the modeling.

Modeler Plugins

  • Kubernetes.Cluster

Service Impact and Root Cause Analysis

When combined with the Zenoss Service Dynamics product, this ZenPack adds built-in service impact and root cause analysis capabilities. The service impact relationships shown in the diagram (right) and described below are automatically added and maintained. These will be included in any services that contain one or more of the explicitly mentioned components.

The following objects types would typically be added to Impact services.

  • Kubernetes Containers
  • Linux device associated with a Kubernetes Node

Impact Relationships between Kubernetes Components

  • GuestCluster (external): impacts Cluster
  • GuestDevice (external): impacts Node
  • Cluster: impacts Node, Persistent Volume
  • Node: impacts Container
  • Container: impacts Pod
  • PersistentVolume: impacts Pod
  • Pod: impacts Deployment, StatefulSet, Service
  • Deployment: impacts Service
  • StatefulSet: impacts Service

Appendix: Kubernetes RBAC Setup

In order to properly enable the Core Metrics Service and provide RBAC access permissions to other components, the following YAML must be applied to the account in the following way:

kubectl apply -f zenoss_rbac.yaml

as references in Usage.

Save the following YAML as zenoss_rbac.yaml as references above. Make sure to preserve the proper YAML formatting:

apiVersion: v1
kind: ServiceAccount
metadata:
  name: zenoss
  namespace: default
secrets:
- name: zenoss-secret
---
apiVersion: v1
kind: Secret
metadata:
  name: zenoss-secret
  annotations:
    kubernetes.io/service-account.name: zenoss
type: kubernetes.io/service-account-token
---
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRole
metadata:
  name: zenoss-role
rules:
- apiGroups: [""]
  resources:
    - clusterrolebindings
    - componentstatus
    - configmaps
    - controllerrevisions
    - cronjobs
    - daemonsets
    - deployments
    - endpoints
    - events
    - horizontalpodautoscalers
    - ingress
    - jobs
    - limitranges
    - namespaces
    - networkpolicys
    - nodes
    - persistentvolumeclaims
    - persistentvolumes
    - pods
    - poddisruptionbudgets
    - podsecuritypolicys
    - podtemplates
    - replicasets
    - replicationcontroller rolebindings
    - secrets
    - services
    - serviceaccounts
    - statefulsets
    - status
    - storageclasses
    - nodemetrics
  verbs: ["get", "watch", "list"]
- apiGroups: ["metrics.k8s.io"]
  resources:
    - nodes
    - pods
  verbs: ["get", "watch", "list"]
- apiGroups: ["apps"]
resources:
- deployments
- statefulsets
verbs: ["get", "watch", "list"] --- apiVersion: rbac.authorization.k8s.io/v1 kind: ClusterRoleBinding metadata: name: zenoss-role-binding roleRef: kind: ClusterRole name: zenoss-role apiGroup: rbac.authorization.k8s.io subjects: - kind: ServiceAccount name: zenoss namespace: default

To validate added permissions run

kubectl api-resources -o wide

Appendix: Identifying Master Nodes

Master node primary is identified by having one of the three processes: kube-apiserver, kube-controller-manager and kube-scheduler.

Identifying master nodes can sometimes fail. We provide several ways to test for master using Kubernetes node labels:

  1. "node-role.kubernetes.io/master": ["master" | "true" | True]
  2. "master": ["true" | True]

Note that #2 can be a custom set label as described below.

If you have issues with your nodes being identified as non-master, you can set a label on your node metadata as:

master: "true"

In GCP, this is edited in the UI:

Kubernetes Engine -> Cluster -> Node -> YAML -> Edit

In kubectl, you can edit the node YAML directly:

kubectl edit node ${NODE_NAME}

You should see end up with something like this:

apiVersion: v1
kind: Node
metadata:
  annotations:
    node.alpha.kubernetes.io/ttl: "0"
    volumes.kubernetes.io/controller-managed-attach-detach: "true"
  creationTimestamp: 2018-06-25T20:55:33Z
  labels:
    beta.kubernetes.io/arch: amd64
    beta.kubernetes.io/fluentd-ds-ready: "true"
    beta.kubernetes.io/instance-type: g1-small
    beta.kubernetes.io/os: linux
    cloud.google.com/gke-nodepool: default-pool
    failure-domain.beta.kubernetes.io/region: us-central1
    failure-domain.beta.kubernetes.io/zone: us-central1-a
    kubernetes.io/hostname: gke-cluster-1-default-pool-fc3e27a3-2mmx
    master: "true"
spec:
  ... etc ...

Appendix: AWS EKS nodes

An Amazon EKS cluster consists of two components:

  • The Amazon EKS control plane
  • Amazon EKS worker nodes

The Amazon EKS control plane includes master nodes that run the Kubernetes software, such as the Kubernetes API server and etcd. The control plane runs in a separate account managed by AWS. Amazon EKS worker nodes run in customer's AWS account and connect to cluster's control plane. So, on AWS EKS we should see only worker nodes.

Appendix: AKS, Azure nodes

An Azure AKS cluster consists of two components:

Changes

1.2.0

  • Added monitoring of StatefulSet component (ZPS-6984)
  • Added zKubernetesPodFilter for filtering Pods and Containers (ZPS-7294)
  • Fixed Cluster, Container, and Node templates (ZPS-7409)
  • Fixed modeling of Pods with the same names (ZPS-7887)
  • Fixed namespace setting during modeling of Containers (ZPS-7888)
  • Tested with Zenoss Cloud, Zenoss 6.6.0 and Service Impact 5.5.5

1.1.0

  • Added support for incremental modeling
  • Added support for EKS (AWS) and AKS (Azure)
  • Add Deployment component and updated Impact relations (ZPS-4625)
  • Improved explanation in auth related errors (ZPS-5955)
  • Added Operating System Relationships (ZPS-5878)
  • Tested with Zenoss 6.4.1, Zenoss Cloud and Impact 5.5.1

1.0.1

  • Fix install issue with Zenoss 6.2.0 (ZPS-4674)
  • Tested with Zenoss 6.2.1, Zenoss Cloud and Impact 5.3.1

1.0.0

  • Initial Release
  • Tested with Zenoss 6.2.1, Zenoss Cloud and Impact 5.3.1