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Kubernetes Support

ยท 9 min read
Matthias Veit

Kubernetes is the de-facto standard for orchestrating containerized applications. It is the go-to solution no matter where your infrastructure is running. Resoto can already collect resources in Amazon Web Services, Google Cloud Platform, and DigitalOcean, all of which support Kubernetes.

I'm happy to announce that Resoto now has support for collecting Kubernetes resources!

Getting Startedโ€‹

To get started, configure Resoto to use your kubeconfig file or copy the relevant sections as described in Configure Kubernetes Access.

> config edit resoto.worker

In the text editor opened by config edit, modify the configuration and define the location of your kubeconfig file. By default, Resoto will collect all contexts that are found in the kubeconfig file. It is possible to restrict the contexts to be used by setting the contexts property and turning all_contexts off.

- k8s
- path: "/home/resoto/.kube/config"

Alternatively, you can also copy & paste the relevant fields directly to the configuration in case the ResotoWorker is running on a machine that does not have access to the file. An example configuration might look like this:

- k8s
- # The name of the kubernetes cluster.
name: 'dev'
# The url of the server to connect to.
server: ''
# The user access token to use to access this cluster.
token: '7632083ca514e919601bb1797caca80XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX'
# The optional CA certificate string.
certificate_authority_data: 'LS0tLS1CRUd...'

The Kubernetes collector can collect multiple Kubernetes clusters by defining multiple entries in the configs or config_files section.

Once this is done, Resoto will start collecting data from all configured clusters on the schedule configured in ResotoCore resotocore.workflows.collect_and_cleanup.schedule, which defaults to every hour. You can trigger a collection run manually by entering:

> workflows run collect_and_cleanup

Kubernetes Resource Data Modelโ€‹

Every resource found in Kubernetes is represented by a node in the graph. Available resource properties are captured and available to filter and automate.


Resoto has a common data model for resources that abstracts from the underlying provider. Every resource inherits the properties from the base resource, which defines properties like id, name, age, last_update, tags etc.

Every resource in Kubernetes is also of type kubernetes_resource, which brings in additional properties like a resource_version, labels, and an optional namespace property, which is defined for all namespaced resources. Annotations of a Kubernetes resource are available as tags and can be modified via the tag command.

Common abstractions apply as well. A PersistentVolume is of base type volume. So it shares the same kind and properties with other volumes of other cloud providers, e.g. an EBSVolume in AWS or a Disk in GCP. The same idea applies to a Kubernetes node which is of base type instance etc.

Kubernetes has its own way of describing a resource, which is available in Resoto as well. The three main sections metadata, spec, and status can be found in almost any resource. The data in the metadata section is basically covered by the base resource properties (id, name, tags, etc.). The spec section usually holds the desired state, while the status section holds the current state.

Both sections are unique to the resource type. Since Resoto allows searching on any resource property, we made the spec and status section unique to the resource type. So a Pod in Resoto has a pod_spec and pod_status section, while a Deployment has a deployment_spec and deployment_status section. The relevant spec and status sections have the same specific data model as the Kubernetes resource.

You can find a complete reference at Kubernetes Resources.

Searching the Graphโ€‹

Since all Kubernetes resources share the same base kind kubernetes_resource, we can filter the graph by this resource type. We will count the number of Kubernetes resources by its kind. This will print the kind of the resource and the number of occurrences in ascending order. This is the output for the 2 clusters we have configured:

> search is(kubernetes_resource) | count kind
kubernetes_job: 1
kubernetes_ingress: 1
kubernetes_ingress_class: 1
kubernetes_cluster: 2
kubernetes_csi_driver: 2
kubernetes_storage_class: 2
kubernetes_mutating_webhook_configuration: 3
kubernetes_validating_webhook_configuration: 4
kubernetes_priority_class: 4
kubernetes_pod_disruption_budget: 5
kubernetes_volume_attachment: 6
kubernetes_node: 6
kubernetes_csi_node: 6
kubernetes_persistent_volume_claim: 7
kubernetes_persistent_volume: 7
kubernetes_stateful_set: 7
kubernetes_daemon_set: 11
kubernetes_priority_level_configuration: 14
kubernetes_namespace: 14
kubernetes_flow_schema: 22
kubernetes_deployment: 25
kubernetes_role: 31
kubernetes_role_binding: 32
kubernetes_controller_revision: 37
kubernetes_endpoint_slice: 45
kubernetes_service: 45
kubernetes_endpoint: 47
kubernetes_replica_set: 63
kubernetes_pod: 70
kubernetes_config_map: 73
kubernetes_service_account: 122
kubernetes_secret: 160
kubernetes_cluster_role_binding: 166
kubernetes_cluster_role: 193
total matched: 1234
total unmatched: 0

Can we reveal general information about the Kubernetes clusters? This query shows all available clusters including version and server URL:

> search is(kubernetes_cluster) | list cluster_info
major=1, minor=21, platform=linux/amd64, server_url=
major=1, minor=21, platform=linux/amd64, server_url=

Now we can start asking questions about the state of our Kubernetes infrastructure. For example, how many pods are running on each node in the cluster?

> search is(kubernetes_pod) | count /
helm2-cjhg9: 7
analytics-u1wtx: 11
helm2-cjhgz: 11
analytics-u1wtj: 11
analytics-u1wto: 15
helm2-cjhg1: 15
total matched: 70
total unmatched: 0

You want to see details? Let's retrieve the information that has been collected about a Kubernetes service with name resotocore:

> search is(kubernetes_service) and name~resotocore | dump
id: AS-E-YjvAftQUcuUmNC52g
ctime: '2022-04-20T14:52:58Z'
id: df8f6c37-5542-4e17-b2f4-bb6caaa2ba17
labels: resoto Helm resoto 2.2.0 resoto-0.2.0
resoto: core
name: resoto-resotocore
namespace: resoto
resource_version: '51578078'
external_ips: []
external_traffic_policy: Cluster
- IPv4
ip_family_policy: SingleStack
load_balancer_source_ranges: []
- name: http
node_port: 32648
port: 8900
protocol: TCP
target_port: api
session_affinity: None
type: LoadBalancer
conditions: []
- ip:
ports: []
tags: 03d5ed66-fefe-41fb-a3f6-9a0e43560adb resoto resoto
kind: kubernetes_service
age: 1mo29d

Resoto ships with the ability to search for a value everywhere, no matter where this value is defined. We call this feature full-text search - you can read about all the details here full-text search Let us use this feature, to search an IP address that we found in the resoto core service. We expect it will find exactly the same ResotoCore service:

> search ""
kind=kubernetes_service, id=df8f6c37-5542-4e17-b2f4-bb6caaa2ba17, name=resoto-resotocore, age=2mo1d, cloud=k8s, account=dev, region=resoto

Let us find all secrets inside Kubernetes, that are shared between more than one pod. Such queries might be useful to find resources, that have a defined relationship in the graph:

> search is(kubernetes_secret) and namespace=resoto with(count>1, <-- is(kubernetes_pod))
kind=kubernetes_secret, id=af1495e4, name=resoto-psk, namespace=resoto, age=2mo1d, cloud=k8s, account=dev, region=resoto

There is more than one secret in this namespace, but only one is shared: the resoto-psk secret holds the private shared key. If we want to see the attached pods, we can use the same query again and list the resources. We will see that ResotoCore, ResotoWorker and ResotoMetrics use the secret resoto-psk. Please note: the secrets that are collected do not sensitive data fields.

> search is(kubernetes_secret) and namespace=resoto with(count>1, <-- is(kubernetes_pod)) <-- is(kubernetes_pod) | list name

Render a graph of all services that are deployed in the resoto namespace on the dev cluster. Please note: we are looking at a cluster where we have deployed resoto as a Helm chart as described in getting started.

search --with-edges is(kubernetes_service) and namespace=resoto <-[0:]-> | format --dot | write

This will output a Graphviz file that can be rendered with the dot command:

resoto services

You can see the list of services as successors of the namespace node. Each service has one or more pods attached to it, where the pods reference configmaps and secrets. The data in Resoto is persistent, so you can also find a persistent volume claim that is attached to the database pod. The claim then references the actual persistent volume.


All annotations in Kubernetes are available as tags. Resoto allows to update tags via ResotoShell, as well as delete tags.

Let's tag all pods with the name resoto in it with the tag owner. Please note: this tag will be temporary and goes away once the pod is deleted since a pod is only a template instance in Kubernetes. If we wanted a more permanent tag, we would need to adjust the related pod template - the deployment in this case.

> search is(kubernetes_pod) and name~resoto | tag update owner matthias | list name, tags
name=resoto-resotocore-67858dbc49-kzh7l, owner=matthias
name=resoto-resotoworker-dc6bd998f-tvhkw, owner=matthias
name=resoto-resotometrics-6c557bd666-m9qzm, owner=matthias

To make sure the existing resources in the cluster have changed:

$ kubectl get pods resoto-resotocore-67858dbc49-kzh7l -o json | jq .metadata.annotations
"owner": "matthias"

Tags can be updated and deleted again:

> search is(kubernetes_pod) and name~resoto | tag delete owner | list name, tags

Cleaning Upโ€‹

To delete resources, pipe search results to the clean command. Let us find volume claims that are not bound to any kubernetes pod and clean them up:

> search is(kubernetes_persistent_volume_claim) with(empty, <-- is(kubernetes_pod)) -[0:1]-> | clean
kind=kubernetes_persistent_volume_claim, id=079affbf, name=single-tvhrrqmm, age=6mo23d, cloud=k8s, account=dev, region=test
kind=kubernetes_persistent_volume, id=c299101c, name=pvc-079affbf, age=6mo23d, cloud=k8s, account=dev, region=test

This query selects all volume claims that have no pod attached and then also select the related volume. The clean command marks the resources for cleanup. The resources will be deleted once the collect_and_cleanup workflow runs (default: every hour).

Future Workโ€‹

We are currently working on the way to connect resources found in Kubernetes to resources found in the underlying cloud provider. Let's assume you have a Kubernetes cluster running on Amazon Web Services, Google Cloud Platform, or DigitalOcean and we want to show the underlying persistent volume provided by the related cloud provider. This would show which compute instance a pod runs on or which underlying volume is provided.

Further Readingโ€‹