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Access Applications in a Cluster
- 1: Deploy and Access the Kubernetes Dashboard
- 2: Accessing Clusters
- 3: Configure Access to Multiple Clusters
- 4: Use Port Forwarding to Access Applications in a Cluster
- 5: Use a Service to Access an Application in a Cluster
- 6: Connect a Frontend to a Backend Using Services
- 7: Create an External Load Balancer
- 8: List All Container Images Running in a Cluster
- 9: Set up Ingress on Minikube with the NGINX Ingress Controller
- 10: Communicate Between Containers in the Same Pod Using a Shared Volume
- 11: Configure DNS for a Cluster
1 - Deploy and Access the Kubernetes Dashboard
Dashboard is a web-based Kubernetes user interface. You can use Dashboard to deploy containerized applications to a Kubernetes cluster, troubleshoot your containerized application, and manage the cluster resources. You can use Dashboard to get an overview of applications running on your cluster, as well as for creating or modifying individual Kubernetes resources (such as Deployments, Jobs, DaemonSets, etc). For example, you can scale a Deployment, initiate a rolling update, restart a pod or deploy new applications using a deploy wizard.
Dashboard also provides information on the state of Kubernetes resources in your cluster and on any errors that may have occurred.
Deploying the Dashboard UI
The Dashboard UI is not deployed by default. To deploy it, run the following command:
kubectl apply -f https://raw.githubusercontent.com/kubernetes/dashboard/v2.4.0/aio/deploy/recommended.yaml
Accessing the Dashboard UI
To protect your cluster data, Dashboard deploys with a minimal RBAC configuration by default. Currently, Dashboard only supports logging in with a Bearer Token. To create a token for this demo, you can follow our guide on creating a sample user.
Command line proxy
You can enable access to the Dashboard using the kubectl
command-line tool,
by running the following command:
kubectl proxy
Kubectl will make Dashboard available at http://localhost:8001/api/v1/namespaces/kubernetes-dashboard/services/https:kubernetes-dashboard:/proxy/.
The UI can only be accessed from the machine where the command is executed. See kubectl proxy --help
for more options.
Welcome view
When you access Dashboard on an empty cluster, you'll see the welcome page.
This page contains a link to this document as well as a button to deploy your first application.
In addition, you can view which system applications are running by default in the kube-system
namespace of your cluster, for example the Dashboard itself.
Deploying containerized applications
Dashboard lets you create and deploy a containerized application as a Deployment and optional Service with a simple wizard. You can either manually specify application details, or upload a YAML or JSON manifest file containing application configuration.
Click the CREATE button in the upper right corner of any page to begin.
Specifying application details
The deploy wizard expects that you provide the following information:
-
App name (mandatory): Name for your application. A label with the name will be added to the Deployment and Service, if any, that will be deployed.
The application name must be unique within the selected Kubernetes namespace. It must start with a lowercase character, and end with a lowercase character or a number, and contain only lowercase letters, numbers and dashes (-). It is limited to 24 characters. Leading and trailing spaces are ignored.
-
Container image (mandatory): The URL of a public Docker container image on any registry, or a private image (commonly hosted on the Google Container Registry or Docker Hub). The container image specification must end with a colon.
-
Number of pods (mandatory): The target number of Pods you want your application to be deployed in. The value must be a positive integer.
A Deployment will be created to maintain the desired number of Pods across your cluster.
-
Service (optional): For some parts of your application (e.g. frontends) you may want to expose a Service onto an external, maybe public IP address outside of your cluster (external Service).
Note: For external Services, you may need to open up one or more ports to do so.Other Services that are only visible from inside the cluster are called internal Services.
Irrespective of the Service type, if you choose to create a Service and your container listens on a port (incoming), you need to specify two ports. The Service will be created mapping the port (incoming) to the target port seen by the container. This Service will route to your deployed Pods. Supported protocols are TCP and UDP. The internal DNS name for this Service will be the value you specified as application name above.
If needed, you can expand the Advanced options section where you can specify more settings:
-
Description: The text you enter here will be added as an annotation to the Deployment and displayed in the application's details.
-
Labels: Default labels to be used for your application are application name and version. You can specify additional labels to be applied to the Deployment, Service (if any), and Pods, such as release, environment, tier, partition, and release track.
Example:
release=1.0 tier=frontend environment=pod track=stable
-
Namespace: Kubernetes supports multiple virtual clusters backed by the same physical cluster. These virtual clusters are called namespaces. They let you partition resources into logically named groups.
Dashboard offers all available namespaces in a dropdown list, and allows you to create a new namespace. The namespace name may contain a maximum of 63 alphanumeric characters and dashes (-) but can not contain capital letters. Namespace names should not consist of only numbers. If the name is set as a number, such as 10, the pod will be put in the default namespace.
In case the creation of the namespace is successful, it is selected by default. If the creation fails, the first namespace is selected.
-
Image Pull Secret: In case the specified Docker container image is private, it may require pull secret credentials.
Dashboard offers all available secrets in a dropdown list, and allows you to create a new secret. The secret name must follow the DNS domain name syntax, for example
new.image-pull.secret
. The content of a secret must be base64-encoded and specified in a.dockercfg
file. The secret name may consist of a maximum of 253 characters.In case the creation of the image pull secret is successful, it is selected by default. If the creation fails, no secret is applied.
-
CPU requirement (cores) and Memory requirement (MiB): You can specify the minimum resource limits for the container. By default, Pods run with unbounded CPU and memory limits.
-
Run command and Run command arguments: By default, your containers run the specified Docker image's default entrypoint command. You can use the command options and arguments to override the default.
-
Run as privileged: This setting determines whether processes in privileged containers are equivalent to processes running as root on the host. Privileged containers can make use of capabilities like manipulating the network stack and accessing devices.
-
Environment variables: Kubernetes exposes Services through environment variables. You can compose environment variable or pass arguments to your commands using the values of environment variables. They can be used in applications to find a Service. Values can reference other variables using the
$(VAR_NAME)
syntax.
Uploading a YAML or JSON file
Kubernetes supports declarative configuration. In this style, all configuration is stored in manifests (YAML or JSON configuration files). The manifests use Kubernetes API resource schemas.
As an alternative to specifying application details in the deploy wizard, you can define your application in one or more manifests, and upload the files using Dashboard.
Using Dashboard
Following sections describe views of the Kubernetes Dashboard UI; what they provide and how can they be used.
Navigation
When there are Kubernetes objects defined in the cluster, Dashboard shows them in the initial view. By default only objects from the default namespace are shown and this can be changed using the namespace selector located in the navigation menu.
Dashboard shows most Kubernetes object kinds and groups them in a few menu categories.
Admin overview
For cluster and namespace administrators, Dashboard lists Nodes, Namespaces and PersistentVolumes and has detail views for them. Node list view contains CPU and memory usage metrics aggregated across all Nodes. The details view shows the metrics for a Node, its specification, status, allocated resources, events and pods running on the node.
Workloads
Shows all applications running in the selected namespace. The view lists applications by workload kind (for example: Deployments, ReplicaSets, StatefulSets). and each workload kind can be viewed separately. The lists summarize actionable information about the workloads, such as the number of ready pods for a ReplicaSet or current memory usage for a Pod.
Detail views for workloads show status and specification information and surface relationships between objects. For example, Pods that ReplicaSet is controlling or new ReplicaSets and HorizontalPodAutoscalers for Deployments.
Services
Shows Kubernetes resources that allow for exposing services to external world and discovering them within a cluster. For that reason, Service and Ingress views show Pods targeted by them, internal endpoints for cluster connections and external endpoints for external users.
Storage
Storage view shows PersistentVolumeClaim resources which are used by applications for storing data.
ConfigMaps and Secrets
Shows all Kubernetes resources that are used for live configuration of applications running in clusters. The view allows for editing and managing config objects and displays secrets hidden by default.
Logs viewer
Pod lists and detail pages link to a logs viewer that is built into Dashboard. The viewer allows for drilling down logs from containers belonging to a single Pod.
What's next
For more information, see the Kubernetes Dashboard project page.
2 - Accessing Clusters
This topic discusses multiple ways to interact with clusters.
Accessing for the first time with kubectl
When accessing the Kubernetes API for the first time, we suggest using the
Kubernetes CLI, kubectl
.
To access a cluster, you need to know the location of the cluster and have credentials to access it. Typically, this is automatically set-up when you work through a Getting started guide, or someone else setup the cluster and provided you with credentials and a location.
Check the location and credentials that kubectl knows about with this command:
kubectl config view
Many of the examples provide an introduction to using kubectl and complete documentation is found in the kubectl manual.
Directly accessing the REST API
Kubectl handles locating and authenticating to the apiserver. If you want to directly access the REST API with an http client like curl or wget, or a browser, there are several ways to locate and authenticate:
- Run kubectl in proxy mode.
- Recommended approach.
- Uses stored apiserver location.
- Verifies identity of apiserver using self-signed cert. No MITM possible.
- Authenticates to apiserver.
- In future, may do intelligent client-side load-balancing and failover.
- Provide the location and credentials directly to the http client.
- Alternate approach.
- Works with some types of client code that are confused by using a proxy.
- Need to import a root cert into your browser to protect against MITM.
Using kubectl proxy
The following command runs kubectl in a mode where it acts as a reverse proxy. It handles locating the apiserver and authenticating. Run it like this:
kubectl proxy --port=8080
See kubectl proxy for more details.
Then you can explore the API with curl, wget, or a browser, replacing localhost with [::1] for IPv6, like so:
curl http://localhost:8080/api/
The output is similar to this:
{
"kind": "APIVersions",
"versions": [
"v1"
],
"serverAddressByClientCIDRs": [
{
"clientCIDR": "0.0.0.0/0",
"serverAddress": "10.0.1.149:443"
}
]
}
Without kubectl proxy
Use kubectl describe secret...
to get the token for the default service account with grep/cut:
APISERVER=$(kubectl config view --minify | grep server | cut -f 2- -d ":" | tr -d " ")
SECRET_NAME=$(kubectl get secrets | grep ^default | cut -f1 -d ' ')
TOKEN=$(kubectl describe secret $SECRET_NAME | grep -E '^token' | cut -f2 -d':' | tr -d " ")
curl $APISERVER/api --header "Authorization: Bearer $TOKEN" --insecure
The output is similar to this:
{
"kind": "APIVersions",
"versions": [
"v1"
],
"serverAddressByClientCIDRs": [
{
"clientCIDR": "0.0.0.0/0",
"serverAddress": "10.0.1.149:443"
}
]
}
Using jsonpath
:
APISERVER=$(kubectl config view --minify -o jsonpath='{.clusters[0].cluster.server}')
SECRET_NAME=$(kubectl get serviceaccount default -o jsonpath='{.secrets[0].name}')
TOKEN=$(kubectl get secret $SECRET_NAME -o jsonpath='{.data.token}' | base64 --decode)
curl $APISERVER/api --header "Authorization: Bearer $TOKEN" --insecure
The output is similar to this:
{
"kind": "APIVersions",
"versions": [
"v1"
],
"serverAddressByClientCIDRs": [
{
"clientCIDR": "0.0.0.0/0",
"serverAddress": "10.0.1.149:443"
}
]
}
The above examples use the --insecure
flag. This leaves it subject to MITM
attacks. When kubectl accesses the cluster it uses a stored root certificate
and client certificates to access the server. (These are installed in the
~/.kube
directory). Since cluster certificates are typically self-signed, it
may take special configuration to get your http client to use root
certificate.
On some clusters, the apiserver does not require authentication; it may serve on localhost, or be protected by a firewall. There is not a standard for this. Controlling Access to the API describes how a cluster admin can configure this.
Programmatic access to the API
Kubernetes officially supports Go and Python client libraries.
Go client
- To get the library, run the following command:
go get k8s.io/client-go@kubernetes-<kubernetes-version-number>
, see INSTALL.md for detailed installation instructions. See https://github.com/kubernetes/client-go to see which versions are supported. - Write an application atop of the client-go clients. Note that client-go defines its own API objects, so if needed, please import API definitions from client-go rather than from the main repository, e.g.,
import "k8s.io/client-go/kubernetes"
is correct.
The Go client can use the same kubeconfig file as the kubectl CLI does to locate and authenticate to the apiserver. See this example.
If the application is deployed as a Pod in the cluster, please refer to the next section.
Python client
To use Python client, run the following command: pip install kubernetes
. See Python Client Library page for more installation options.
The Python client can use the same kubeconfig file as the kubectl CLI does to locate and authenticate to the apiserver. See this example.
Other languages
There are client libraries for accessing the API from other languages. See documentation for other libraries for how they authenticate.
Accessing the API from a Pod
When accessing the API from a pod, locating and authenticating to the apiserver are somewhat different.
The recommended way to locate the apiserver within the pod is with
the kubernetes.default.svc
DNS name, which resolves to a Service IP which in turn
will be routed to an apiserver.
The recommended way to authenticate to the apiserver is with a
service account credential. By kube-system, a pod
is associated with a service account, and a credential (token) for that
service account is placed into the filesystem tree of each container in that pod,
at /var/run/secrets/kubernetes.io/serviceaccount/token
.
If available, a certificate bundle is placed into the filesystem tree of each
container at /var/run/secrets/kubernetes.io/serviceaccount/ca.crt
, and should be
used to verify the serving certificate of the apiserver.
Finally, the default namespace to be used for namespaced API operations is placed in a file
at /var/run/secrets/kubernetes.io/serviceaccount/namespace
in each container.
From within a pod the recommended ways to connect to API are:
- Run
kubectl proxy
in a sidecar container in the pod, or as a background process within the container. This proxies the Kubernetes API to the localhost interface of the pod, so that other processes in any container of the pod can access it. - Use the Go client library, and create a client using the
rest.InClusterConfig()
andkubernetes.NewForConfig()
functions. They handle locating and authenticating to the apiserver. example
In each case, the credentials of the pod are used to communicate securely with the apiserver.
Accessing services running on the cluster
The previous section describes how to connect to the Kubernetes API server. For information about connecting to other services running on a Kubernetes cluster, see Access Cluster Services.
Requesting redirects
The redirect capabilities have been deprecated and removed. Please use a proxy (see below) instead.
So Many Proxies
There are several different proxies you may encounter when using Kubernetes:
-
The kubectl proxy:
- runs on a user's desktop or in a pod
- proxies from a localhost address to the Kubernetes apiserver
- client to proxy uses HTTP
- proxy to apiserver uses HTTPS
- locates apiserver
- adds authentication headers
-
The apiserver proxy:
- is a bastion built into the apiserver
- connects a user outside of the cluster to cluster IPs which otherwise might not be reachable
- runs in the apiserver processes
- client to proxy uses HTTPS (or http if apiserver so configured)
- proxy to target may use HTTP or HTTPS as chosen by proxy using available information
- can be used to reach a Node, Pod, or Service
- does load balancing when used to reach a Service
-
The kube proxy:
- runs on each node
- proxies UDP and TCP
- does not understand HTTP
- provides load balancing
- is only used to reach services
-
A Proxy/Load-balancer in front of apiserver(s):
- existence and implementation varies from cluster to cluster (e.g. nginx)
- sits between all clients and one or more apiservers
- acts as load balancer if there are several apiservers.
-
Cloud Load Balancers on external services:
- are provided by some cloud providers (e.g. AWS ELB, Google Cloud Load Balancer)
- are created automatically when the Kubernetes service has type
LoadBalancer
- use UDP/TCP only
- implementation varies by cloud provider.
Kubernetes users will typically not need to worry about anything other than the first two types. The cluster admin will typically ensure that the latter types are setup correctly.
3 - Configure Access to Multiple Clusters
This page shows how to configure access to multiple clusters by using
configuration files. After your clusters, users, and contexts are defined in
one or more configuration files, you can quickly switch between clusters by using the
kubectl config use-context
command.
kubeconfig
.
Before you begin
You need to have a Kubernetes cluster, and the kubectl command-line tool must be configured to communicate with your cluster. It is recommended to run this tutorial on a cluster with at least two nodes that are not acting as control plane hosts. If you do not already have a cluster, you can create one by using minikube or you can use one of these Kubernetes playgrounds:
To check that kubectl is installed,
run kubectl version --client
. The kubectl version should be
within one minor version of your
cluster's API server.
Define clusters, users, and contexts
Suppose you have two clusters, one for development work and one for scratch work.
In the development
cluster, your frontend developers work in a namespace called frontend
,
and your storage developers work in a namespace called storage
. In your scratch
cluster,
developers work in the default namespace, or they create auxiliary namespaces as they
see fit. Access to the development cluster requires authentication by certificate. Access
to the scratch cluster requires authentication by username and password.
Create a directory named config-exercise
. In your
config-exercise
directory, create a file named config-demo
with this content:
apiVersion: v1
kind: Config
preferences: {}
clusters:
- cluster:
name: development
- cluster:
name: scratch
users:
- name: developer
- name: experimenter
contexts:
- context:
name: dev-frontend
- context:
name: dev-storage
- context:
name: exp-scratch
A configuration file describes clusters, users, and contexts. Your config-demo
file
has the framework to describe two clusters, two users, and three contexts.
Go to your config-exercise
directory. Enter these commands to add cluster details to
your configuration file:
kubectl config --kubeconfig=config-demo set-cluster development --server=https://1.2.3.4 --certificate-authority=fake-ca-file
kubectl config --kubeconfig=config-demo set-cluster scratch --server=https://5.6.7.8 --insecure-skip-tls-verify
Add user details to your configuration file:
kubectl config --kubeconfig=config-demo set-credentials developer --client-certificate=fake-cert-file --client-key=fake-key-seefile
kubectl config --kubeconfig=config-demo set-credentials experimenter --username=exp --password=some-password
- To delete a user you can run
kubectl --kubeconfig=config-demo config unset users.<name>
- To remove a cluster, you can run
kubectl --kubeconfig=config-demo config unset clusters.<name>
- To remove a context, you can run
kubectl --kubeconfig=config-demo config unset contexts.<name>
Add context details to your configuration file:
kubectl config --kubeconfig=config-demo set-context dev-frontend --cluster=development --namespace=frontend --user=developer
kubectl config --kubeconfig=config-demo set-context dev-storage --cluster=development --namespace=storage --user=developer
kubectl config --kubeconfig=config-demo set-context exp-scratch --cluster=scratch --namespace=default --user=experimenter
Open your config-demo
file to see the added details. As an alternative to opening the
config-demo
file, you can use the config view
command.
kubectl config --kubeconfig=config-demo view
The output shows the two clusters, two users, and three contexts:
apiVersion: v1
clusters:
- cluster:
certificate-authority: fake-ca-file
server: https://1.2.3.4
name: development
- cluster:
insecure-skip-tls-verify: true
server: https://5.6.7.8
name: scratch
contexts:
- context:
cluster: development
namespace: frontend
user: developer
name: dev-frontend
- context:
cluster: development
namespace: storage
user: developer
name: dev-storage
- context:
cluster: scratch
namespace: default
user: experimenter
name: exp-scratch
current-context: ""
kind: Config
preferences: {}
users:
- name: developer
user:
client-certificate: fake-cert-file
client-key: fake-key-file
- name: experimenter
user:
password: some-password
username: exp
The fake-ca-file
, fake-cert-file
and fake-key-file
above are the placeholders
for the pathnames of the certificate files. You need to change these to the actual pathnames
of certificate files in your environment.
Sometimes you may want to use Base64-encoded data embedded here instead of separate
certificate files; in that case you need to add the suffix -data
to the keys, for example,
certificate-authority-data
, client-certificate-data
, client-key-data
.
Each context is a triple (cluster, user, namespace). For example, the
dev-frontend
context says, "Use the credentials of the developer
user to access the frontend
namespace of the development
cluster".
Set the current context:
kubectl config --kubeconfig=config-demo use-context dev-frontend
Now whenever you enter a kubectl
command, the action will apply to the cluster,
and namespace listed in the dev-frontend
context. And the command will use
the credentials of the user listed in the dev-frontend
context.
To see only the configuration information associated with
the current context, use the --minify
flag.
kubectl config --kubeconfig=config-demo view --minify
The output shows configuration information associated with the dev-frontend
context:
apiVersion: v1
clusters:
- cluster:
certificate-authority: fake-ca-file
server: https://1.2.3.4
name: development
contexts:
- context:
cluster: development
namespace: frontend
user: developer
name: dev-frontend
current-context: dev-frontend
kind: Config
preferences: {}
users:
- name: developer
user:
client-certificate: fake-cert-file
client-key: fake-key-file
Now suppose you want to work for a while in the scratch cluster.
Change the current context to exp-scratch
:
kubectl config --kubeconfig=config-demo use-context exp-scratch
Now any kubectl
command you give will apply to the default namespace of
the scratch
cluster. And the command will use the credentials of the user
listed in the exp-scratch
context.
View configuration associated with the new current context, exp-scratch
.
kubectl config --kubeconfig=config-demo view --minify
Finally, suppose you want to work for a while in the storage
namespace of the
development
cluster.
Change the current context to dev-storage
:
kubectl config --kubeconfig=config-demo use-context dev-storage
View configuration associated with the new current context, dev-storage
.
kubectl config --kubeconfig=config-demo view --minify
Create a second configuration file
In your config-exercise
directory, create a file named config-demo-2
with this content:
apiVersion: v1
kind: Config
preferences: {}
contexts:
- context:
cluster: development
namespace: ramp
user: developer
name: dev-ramp-up
The preceding configuration file defines a new context named dev-ramp-up
.
Set the KUBECONFIG environment variable
See whether you have an environment variable named KUBECONFIG
. If so, save the
current value of your KUBECONFIG
environment variable, so you can restore it later.
For example:
Linux
export KUBECONFIG_SAVED=$KUBECONFIG
Windows PowerShell
$Env:KUBECONFIG_SAVED=$ENV:KUBECONFIG
The KUBECONFIG
environment variable is a list of paths to configuration files. The list is
colon-delimited for Linux and Mac, and semicolon-delimited for Windows. If you have
a KUBECONFIG
environment variable, familiarize yourself with the configuration files
in the list.
Temporarily append two paths to your KUBECONFIG
environment variable. For example:
Linux
export KUBECONFIG=$KUBECONFIG:config-demo:config-demo-2
Windows PowerShell
$Env:KUBECONFIG=("config-demo;config-demo-2")
In your config-exercise
directory, enter this command:
kubectl config view
The output shows merged information from all the files listed in your KUBECONFIG
environment variable. In particular, notice that the merged information has the
dev-ramp-up
context from the config-demo-2
file and the three contexts from
the config-demo
file:
contexts:
- context:
cluster: development
namespace: frontend
user: developer
name: dev-frontend
- context:
cluster: development
namespace: ramp
user: developer
name: dev-ramp-up
- context:
cluster: development
namespace: storage
user: developer
name: dev-storage
- context:
cluster: scratch
namespace: default
user: experimenter
name: exp-scratch
For more information about how kubeconfig files are merged, see Organizing Cluster Access Using kubeconfig Files
Explore the $HOME/.kube directory
If you already have a cluster, and you can use kubectl
to interact with
the cluster, then you probably have a file named config
in the $HOME/.kube
directory.
Go to $HOME/.kube
, and see what files are there. Typically, there is a file named
config
. There might also be other configuration files in this directory. Briefly
familiarize yourself with the contents of these files.
Append $HOME/.kube/config to your KUBECONFIG environment variable
If you have a $HOME/.kube/config
file, and it's not already listed in your
KUBECONFIG
environment variable, append it to your KUBECONFIG
environment variable now.
For example:
Linux
export KUBECONFIG=$KUBECONFIG:$HOME/.kube/config
Windows Powershell
$Env:KUBECONFIG="$Env:KUBECONFIG;$HOME\.kube\config"
View configuration information merged from all the files that are now listed
in your KUBECONFIG
environment variable. In your config-exercise directory, enter:
kubectl config view
Clean up
Return your KUBECONFIG
environment variable to its original value. For example:
Linux
export KUBECONFIG=$KUBECONFIG_SAVED
Windows PowerShell
$Env:KUBECONFIG=$ENV:KUBECONFIG_SAVED
What's next
4 - Use Port Forwarding to Access Applications in a Cluster
This page shows how to use kubectl port-forward
to connect to a MongoDB
server running in a Kubernetes cluster. This type of connection can be useful
for database debugging.
Before you begin
-
You need to have a Kubernetes cluster, and the kubectl command-line tool must be configured to communicate with your cluster. It is recommended to run this tutorial on a cluster with at least two nodes that are not acting as control plane hosts. If you do not already have a cluster, you can create one by using minikube or you can use one of these Kubernetes playgrounds:
Your Kubernetes server must be at or later than version v1.10. To check the version, enterkubectl version
. -
Install MongoDB Shell.
Creating MongoDB deployment and service
-
Create a Deployment that runs MongoDB:
kubectl apply -f https://k8s.io/examples/application/mongodb/mongo-deployment.yaml
The output of a successful command verifies that the deployment was created:
deployment.apps/mongo created
View the pod status to check that it is ready:
kubectl get pods
The output displays the pod created:
NAME READY STATUS RESTARTS AGE mongo-75f59d57f4-4nd6q 1/1 Running 0 2m4s
View the Deployment's status:
kubectl get deployment
The output displays that the Deployment was created:
NAME READY UP-TO-DATE AVAILABLE AGE mongo 1/1 1 1 2m21s
The Deployment automatically manages a ReplicaSet. View the ReplicaSet status using:
kubectl get replicaset
The output displays that the ReplicaSet was created:
NAME DESIRED CURRENT READY AGE mongo-75f59d57f4 1 1 1 3m12s
-
Create a Service to expose MongoDB on the network:
kubectl apply -f https://k8s.io/examples/application/mongodb/mongo-service.yaml
The output of a successful command verifies that the Service was created:
service/mongo created
Check the Service created:
kubectl get service mongo
The output displays the service created:
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE mongo ClusterIP 10.96.41.183 <none> 27017/TCP 11s
-
Verify that the MongoDB server is running in the Pod, and listening on port 27017:
# Change mongo-75f59d57f4-4nd6q to the name of the Pod kubectl get pod mongo-75f59d57f4-4nd6q --template='{{(index (index .spec.containers 0).ports 0).containerPort}}{{"\n"}}'
The output displays the port for MongoDB in that Pod:
27017
(this is the TCP port allocated to MongoDB on the internet).
Forward a local port to a port on the Pod
-
kubectl port-forward
allows using resource name, such as a pod name, to select a matching pod to port forward to.# Change mongo-75f59d57f4-4nd6q to the name of the Pod kubectl port-forward mongo-75f59d57f4-4nd6q 28015:27017
which is the same as
kubectl port-forward pods/mongo-75f59d57f4-4nd6q 28015:27017
or
kubectl port-forward deployment/mongo 28015:27017
or
kubectl port-forward replicaset/mongo-75f59d57f4 28015:27017
or
kubectl port-forward service/mongo 28015:27017
Any of the above commands works. The output is similar to this:
Forwarding from 127.0.0.1:28015 -> 27017 Forwarding from [::1]:28015 -> 27017
kubectl port-forward
does not return. To continue with the exercises, you will need to open another terminal.
-
Start the MongoDB command line interface:
mongosh --port 28015
-
At the MongoDB command line prompt, enter the
ping
command:db.runCommand( { ping: 1 } )
A successful ping request returns:
{ ok: 1 }
Optionally let kubectl choose the local port
If you don't need a specific local port, you can let kubectl
choose and allocate
the local port and thus relieve you from having to manage local port conflicts, with
the slightly simpler syntax:
kubectl port-forward deployment/mongo :27017
The kubectl
tool finds a local port number that is not in use (avoiding low ports numbers,
because these might be used by other applications). The output is similar to:
Forwarding from 127.0.0.1:63753 -> 27017
Forwarding from [::1]:63753 -> 27017
Discussion
Connections made to local port 28015 are forwarded to port 27017 of the Pod that is running the MongoDB server. With this connection in place, you can use your local workstation to debug the database that is running in the Pod.
kubectl port-forward
is implemented for TCP ports only.
The support for UDP protocol is tracked in
issue 47862.
What's next
Learn more about kubectl port-forward.
5 - Use a Service to Access an Application in a Cluster
This page shows how to create a Kubernetes Service object that external clients can use to access an application running in a cluster. The Service provides load balancing for an application that has two running instances.
Before you begin
You need to have a Kubernetes cluster, and the kubectl command-line tool must be configured to communicate with your cluster. It is recommended to run this tutorial on a cluster with at least two nodes that are not acting as control plane hosts. If you do not already have a cluster, you can create one by using minikube or you can use one of these Kubernetes playgrounds:
To check the version, enterkubectl version
.
Objectives
- Run two instances of a Hello World application.
- Create a Service object that exposes a node port.
- Use the Service object to access the running application.
Creating a service for an application running in two pods
Here is the configuration file for the application Deployment:
apiVersion: apps/v1
kind: Deployment
metadata:
name: hello-world
spec:
selector:
matchLabels:
run: load-balancer-example
replicas: 2
template:
metadata:
labels:
run: load-balancer-example
spec:
containers:
- name: hello-world
image: gcr.io/google-samples/node-hello:1.0
ports:
- containerPort: 8080
protocol: TCP
-
Run a Hello World application in your cluster: Create the application Deployment using the file above:
kubectl apply -f https://k8s.io/examples/service/access/hello-application.yaml
The preceding command creates a Deployment and an associated ReplicaSet. The ReplicaSet has two Pods each of which runs the Hello World application.
-
Display information about the Deployment:
kubectl get deployments hello-world kubectl describe deployments hello-world
-
Display information about your ReplicaSet objects:
kubectl get replicasets kubectl describe replicasets
-
Create a Service object that exposes the deployment:
kubectl expose deployment hello-world --type=NodePort --name=example-service
-
Display information about the Service:
kubectl describe services example-service
The output is similar to this:
Name: example-service Namespace: default Labels: run=load-balancer-example Annotations: <none> Selector: run=load-balancer-example Type: NodePort IP: 10.32.0.16 Port: <unset> 8080/TCP TargetPort: 8080/TCP NodePort: <unset> 31496/TCP Endpoints: 10.200.1.4:8080,10.200.2.5:8080 Session Affinity: None Events: <none>
Make a note of the NodePort value for the service. For example, in the preceding output, the NodePort value is 31496.
-
List the pods that are running the Hello World application:
kubectl get pods --selector="run=load-balancer-example" --output=wide
The output is similar to this:
NAME READY STATUS ... IP NODE hello-world-2895499144-bsbk5 1/1 Running ... 10.200.1.4 worker1 hello-world-2895499144-m1pwt 1/1 Running ... 10.200.2.5 worker2
-
Get the public IP address of one of your nodes that is running a Hello World pod. How you get this address depends on how you set up your cluster. For example, if you are using Minikube, you can see the node address by running
kubectl cluster-info
. If you are using Google Compute Engine instances, you can use thegcloud compute instances list
command to see the public addresses of your nodes. -
On your chosen node, create a firewall rule that allows TCP traffic on your node port. For example, if your Service has a NodePort value of 31568, create a firewall rule that allows TCP traffic on port 31568. Different cloud providers offer different ways of configuring firewall rules.
-
Use the node address and node port to access the Hello World application:
curl http://<public-node-ip>:<node-port>
where
<public-node-ip>
is the public IP address of your node, and<node-port>
is the NodePort value for your service. The response to a successful request is a hello message:Hello Kubernetes!
Using a service configuration file
As an alternative to using kubectl expose
, you can use a
service configuration file
to create a Service.
Cleaning up
To delete the Service, enter this command:
kubectl delete services example-service
To delete the Deployment, the ReplicaSet, and the Pods that are running the Hello World application, enter this command:
kubectl delete deployment hello-world
What's next
Learn more about connecting applications with services.
6 - Connect a Frontend to a Backend Using Services
This task shows how to create a frontend and a backend microservice. The backend microservice is a hello greeter. The frontend exposes the backend using nginx and a Kubernetes Service object.
Objectives
- Create and run a sample
hello
backend microservice using a Deployment object. - Use a Service object to send traffic to the backend microservice's multiple replicas.
- Create and run a
nginx
frontend microservice, also using a Deployment object. - Configure the frontend microservice to send traffic to the backend microservice.
- Use a Service object of
type=LoadBalancer
to expose the frontend microservice outside the cluster.
Before you begin
You need to have a Kubernetes cluster, and the kubectl command-line tool must be configured to communicate with your cluster. It is recommended to run this tutorial on a cluster with at least two nodes that are not acting as control plane hosts. If you do not already have a cluster, you can create one by using minikube or you can use one of these Kubernetes playgrounds:
To check the version, enterkubectl version
.
This task uses Services with external load balancers, which require a supported environment. If your environment does not support this, you can use a Service of type NodePort instead.
Creating the backend using a Deployment
The backend is a simple hello greeter microservice. Here is the configuration file for the backend Deployment:
---
apiVersion: apps/v1
kind: Deployment
metadata:
name: backend
spec:
selector:
matchLabels:
app: hello
tier: backend
track: stable
replicas: 3
template:
metadata:
labels:
app: hello
tier: backend
track: stable
spec:
containers:
- name: hello
image: "gcr.io/google-samples/hello-go-gke:1.0"
ports:
- name: http
containerPort: 80
...
Create the backend Deployment:
kubectl apply -f https://k8s.io/examples/service/access/backend-deployment.yaml
View information about the backend Deployment:
kubectl describe deployment backend
The output is similar to this:
Name: backend
Namespace: default
CreationTimestamp: Mon, 24 Oct 2016 14:21:02 -0700
Labels: app=hello
tier=backend
track=stable
Annotations: deployment.kubernetes.io/revision=1
Selector: app=hello,tier=backend,track=stable
Replicas: 3 desired | 3 updated | 3 total | 3 available | 0 unavailable
StrategyType: RollingUpdate
MinReadySeconds: 0
RollingUpdateStrategy: 1 max unavailable, 1 max surge
Pod Template:
Labels: app=hello
tier=backend
track=stable
Containers:
hello:
Image: "gcr.io/google-samples/hello-go-gke:1.0"
Port: 80/TCP
Environment: <none>
Mounts: <none>
Volumes: <none>
Conditions:
Type Status Reason
---- ------ ------
Available True MinimumReplicasAvailable
Progressing True NewReplicaSetAvailable
OldReplicaSets: <none>
NewReplicaSet: hello-3621623197 (3/3 replicas created)
Events:
...
Creating the hello
Service object
The key to sending requests from a frontend to a backend is the backend Service. A Service creates a persistent IP address and DNS name entry so that the backend microservice can always be reached. A Service uses selectors to find the Pods that it routes traffic to.
First, explore the Service configuration file:
---
apiVersion: v1
kind: Service
metadata:
name: hello
spec:
selector:
app: hello
tier: backend
ports:
- protocol: TCP
port: 80
targetPort: http
...
In the configuration file, you can see that the Service, named hello
routes
traffic to Pods that have the labels app: hello
and tier: backend
.
Create the backend Service:
kubectl apply -f https://k8s.io/examples/service/access/backend-service.yaml
At this point, you have a backend
Deployment running three replicas of your hello
application, and you have a Service that can route traffic to them. However, this
service is neither available nor resolvable outside the cluster.
Creating the frontend
Now that you have your backend running, you can create a frontend that is accessible outside the cluster, and connects to the backend by proxying requests to it.
The frontend sends requests to the backend worker Pods by using the DNS name
given to the backend Service. The DNS name is hello
, which is the value
of the name
field in the examples/service/access/backend-service.yaml
configuration file.
The Pods in the frontend Deployment run a nginx image that is configured
to proxy requests to the hello
backend Service. Here is the nginx configuration file:
# The identifier Backend is internal to nginx, and used to name this specific upstream
upstream Backend {
# hello is the internal DNS name used by the backend Service inside Kubernetes
server hello;
}
server {
listen 80;
location / {
# The following statement will proxy traffic to the upstream named Backend
proxy_pass http://Backend;
}
}
Similar to the backend, the frontend has a Deployment and a Service. An important
difference to notice between the backend and frontend services, is that the
configuration for the frontend Service has type: LoadBalancer
, which means that
the Service uses a load balancer provisioned by your cloud provider and will be
accessible from outside the cluster.
---
apiVersion: v1
kind: Service
metadata:
name: frontend
spec:
selector:
app: hello
tier: frontend
ports:
- protocol: "TCP"
port: 80
targetPort: 80
type: LoadBalancer
...
---
apiVersion: apps/v1
kind: Deployment
metadata:
name: frontend
spec:
selector:
matchLabels:
app: hello
tier: frontend
track: stable
replicas: 1
template:
metadata:
labels:
app: hello
tier: frontend
track: stable
spec:
containers:
- name: nginx
image: "gcr.io/google-samples/hello-frontend:1.0"
lifecycle:
preStop:
exec:
command: ["/usr/sbin/nginx","-s","quit"]
...
Create the frontend Deployment and Service:
kubectl apply -f https://k8s.io/examples/service/access/frontend-deployment.yaml
kubectl apply -f https://k8s.io/examples/service/access/frontend-service.yaml
The output verifies that both resources were created:
deployment.apps/frontend created
service/frontend created
Interact with the frontend Service
Once you've created a Service of type LoadBalancer, you can use this command to find the external IP:
kubectl get service frontend --watch
This displays the configuration for the frontend
Service and watches for
changes. Initially, the external IP is listed as <pending>
:
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
frontend LoadBalancer 10.51.252.116 <pending> 80/TCP 10s
As soon as an external IP is provisioned, however, the configuration updates
to include the new IP under the EXTERNAL-IP
heading:
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
frontend LoadBalancer 10.51.252.116 XXX.XXX.XXX.XXX 80/TCP 1m
That IP can now be used to interact with the frontend
service from outside the
cluster.
Send traffic through the frontend
The frontend and backend are now connected. You can hit the endpoint by using the curl command on the external IP of your frontend Service.
curl http://${EXTERNAL_IP} # replace this with the EXTERNAL-IP you saw earlier
The output shows the message generated by the backend:
{"message":"Hello"}
Cleaning up
To delete the Services, enter this command:
kubectl delete services frontend backend
To delete the Deployments, the ReplicaSets and the Pods that are running the backend and frontend applications, enter this command:
kubectl delete deployment frontend backend
What's next
- Learn more about Services
- Learn more about ConfigMaps
- Learn more about DNS for Service and Pods
7 - Create an External Load Balancer
This page shows how to create an external load balancer.
When creating a Service, you have the option of automatically creating a cloud load balancer. This provides an externally-accessible IP address that sends traffic to the correct port on your cluster nodes, provided your cluster runs in a supported environment and is configured with the correct cloud load balancer provider package.
You can also use an Ingress in place of Service. For more information, check the Ingress documentation.
Before you begin
You need to have a Kubernetes cluster, and the kubectl command-line tool must be configured to communicate with your cluster. It is recommended to run this tutorial on a cluster with at least two nodes that are not acting as control plane hosts. If you do not already have a cluster, you can create one by using minikube or you can use one of these Kubernetes playgrounds:
Your cluster must be running in a cloud or other environment that already has support for configuring external load balancers.
Create a Service
Create a Service from a manifest
To create an external load balancer, add the following line to your Service manifest:
type: LoadBalancer
Your manifest might then look like:
apiVersion: v1
kind: Service
metadata:
name: example-service
spec:
selector:
app: example
ports:
- port: 8765
targetPort: 9376
type: LoadBalancer
Create a Service using kubectl
You can alternatively create the service with the kubectl expose
command and
its --type=LoadBalancer
flag:
kubectl expose deployment example --port=8765 --target-port=9376 \
--name=example-service --type=LoadBalancer
This command creates a new Service using the same selectors as the referenced
resource (in the case of the example above, a
Deployment named example
).
For more information, including optional flags, refer to the
kubectl expose
reference.
Finding your IP address
You can find the IP address created for your service by getting the service
information through kubectl
:
kubectl describe services example-service
which should produce output similar to:
Name: example-service
Namespace: default
Labels: app=example
Annotations: <none>
Selector: app=example
Type: LoadBalancer
IP Families: <none>
IP: 10.3.22.96
IPs: 10.3.22.96
LoadBalancer Ingress: 192.0.2.89
Port: <unset> 8765/TCP
TargetPort: 9376/TCP
NodePort: <unset> 30593/TCP
Endpoints: 172.17.0.3:9376
Session Affinity: None
External Traffic Policy: Cluster
Events: <none>
The load balancer's IP address is listed next to LoadBalancer Ingress
.
If you are running your service on Minikube, you can find the assigned IP address and port with:
minikube service example-service --url
Preserving the client source IP
By default, the source IP seen in the target container is not the original
source IP of the client. To enable preservation of the client IP, the following
fields can be configured in the .spec
of the Service:
.spec.externalTrafficPolicy
- denotes if this Service desires to route external traffic to node-local or cluster-wide endpoints. There are two available options:Cluster
(default) andLocal
.Cluster
obscures the client source IP and may cause a second hop to another node, but should have good overall load-spreading.Local
preserves the client source IP and avoids a second hop for LoadBalancer and NodePort type Services, but risks potentially imbalanced traffic spreading..spec.healthCheckNodePort
- specifies the health check node port (numeric port number) for the service. If you don't specifyhealthCheckNodePort
, the service controller allocates a port from your cluster's NodePort range.
You can configure that range by setting an API server command line option,--service-node-port-range
. The Service will use the user-specifiedhealthCheckNodePort
value if you specify it, provided that the Servicetype
is set to LoadBalancer andexternalTrafficPolicy
is set toLocal
.
Setting externalTrafficPolicy
to Local in the Service manifest
activates this feature. For example:
apiVersion: v1
kind: Service
metadata:
name: example-service
spec:
selector:
app: example
ports:
- port: 8765
targetPort: 9376
externalTrafficPolicy: Local
type: LoadBalancer
Caveats and limitations when preserving source IPs
Load balancing services from some cloud providers do not let you configure different weights for each target.
With each target weighted equally in terms of sending traffic to Nodes, external traffic is not equally load balanced across different Pods. The external load balancer is unaware of the number of Pods on each node that are used as a target.
Where NumServicePods << _NumNodes
or NumServicePods >> NumNodes
, a fairly close-to-equal
distribution will be seen, even without weights.
Internal pod to pod traffic should behave similar to ClusterIP services, with equal probability across all pods.
Garbage collecting load balancers
Kubernetes v1.17 [stable]
In usual case, the correlating load balancer resources in cloud provider should be cleaned up soon after a LoadBalancer type Service is deleted. But it is known that there are various corner cases where cloud resources are orphaned after the associated Service is deleted. Finalizer Protection for Service LoadBalancers was introduced to prevent this from happening. By using finalizers, a Service resource will never be deleted until the correlating load balancer resources are also deleted.
Specifically, if a Service has type
LoadBalancer, the service controller will attach
a finalizer named service.kubernetes.io/load-balancer-cleanup
.
The finalizer will only be removed after the load balancer resource is cleaned up.
This prevents dangling load balancer resources even in corner cases such as the
service controller crashing.
External load balancer providers
It is important to note that the datapath for this functionality is provided by a load balancer external to the Kubernetes cluster.
When the Service type
is set to LoadBalancer, Kubernetes provides functionality equivalent to type
equals ClusterIP to pods
within the cluster and extends it by programming the (external to Kubernetes) load balancer with entries for the nodes
hosting the relevant Kubernetes pods. The Kubernetes control plane automates the creation of the external load balancer,
health checks (if needed), and packet filtering rules (if needed). Once the cloud provider allocates an IP address for the load
balancer, the control plane looks up that external IP address and populates it into the Service object.
What's next
- Read about Service
- Read about Ingress
- Read Connecting Applications with Services
8 - List All Container Images Running in a Cluster
This page shows how to use kubectl to list all of the Container images for Pods running in a cluster.
Before you begin
You need to have a Kubernetes cluster, and the kubectl command-line tool must be configured to communicate with your cluster. It is recommended to run this tutorial on a cluster with at least two nodes that are not acting as control plane hosts. If you do not already have a cluster, you can create one by using minikube or you can use one of these Kubernetes playgrounds:
To check the version, enterkubectl version
.
In this exercise you will use kubectl to fetch all of the Pods running in a cluster, and format the output to pull out the list of Containers for each.
List all Container images in all namespaces
- Fetch all Pods in all namespaces using
kubectl get pods --all-namespaces
- Format the output to include only the list of Container image names
using
-o jsonpath={.items[*].spec.containers[*].image}
. This will recursively parse out theimage
field from the returned json.- See the jsonpath reference for further information on how to use jsonpath.
- Format the output using standard tools:
tr
,sort
,uniq
- Use
tr
to replace spaces with newlines - Use
sort
to sort the results - Use
uniq
to aggregate image counts
- Use
kubectl get pods --all-namespaces -o jsonpath="{.items[*].spec.containers[*].image}" |\
tr -s '[[:space:]]' '\n' |\
sort |\
uniq -c
The above command will recursively return all fields named image
for all items returned.
As an alternative, it is possible to use the absolute path to the image
field within the Pod. This ensures the correct field is retrieved
even when the field name is repeated,
e.g. many fields are called name
within a given item:
kubectl get pods --all-namespaces -o jsonpath="{.items[*].spec.containers[*].image}"
The jsonpath is interpreted as follows:
.items[*]
: for each returned value.spec
: get the spec.containers[*]
: for each container.image
: get the image
kubectl get pod nginx
,
the .items[*]
portion of the path should be omitted because a single
Pod is returned instead of a list of items.
List Container images by Pod
The formatting can be controlled further by using the range
operation to
iterate over elements individually.
kubectl get pods --all-namespaces -o jsonpath='{range .items[*]}{"\n"}{.metadata.name}{":\t"}{range .spec.containers[*]}{.image}{", "}{end}{end}' |\
sort
List Container images filtering by Pod label
To target only Pods matching a specific label, use the -l flag. The
following matches only Pods with labels matching app=nginx
.
kubectl get pods --all-namespaces -o jsonpath="{.items[*].spec.containers[*].image}" -l app=nginx
List Container images filtering by Pod namespace
To target only pods in a specific namespace, use the namespace flag. The
following matches only Pods in the kube-system
namespace.
kubectl get pods --namespace kube-system -o jsonpath="{.items[*].spec.containers[*].image}"
List Container images using a go-template instead of jsonpath
As an alternative to jsonpath, Kubectl supports using go-templates for formatting the output:
kubectl get pods --all-namespaces -o go-template --template="{{range .items}}{{range .spec.containers}}{{.image}} {{end}}{{end}}"
What's next
Reference
- Jsonpath reference guide
- Go template reference guide
9 - Set up Ingress on Minikube with the NGINX Ingress Controller
An Ingress is an API object that defines rules which allow external access to services in a cluster. An Ingress controller fulfills the rules set in the Ingress.
This page shows you how to set up a simple Ingress which routes requests to Service web or web2 depending on the HTTP URI.
Before you begin
You need to have a Kubernetes cluster, and the kubectl command-line tool must be configured to communicate with your cluster. It is recommended to run this tutorial on a cluster with at least two nodes that are not acting as control plane hosts. If you do not already have a cluster, you can create one by using minikube or you can use one of these Kubernetes playgrounds:
Your Kubernetes server must be at or later than version 1.19. To check the version, enterkubectl version
.
If you are using an older Kubernetes version, switch to the documentation
for that version.
Create a Minikube cluster
- Using Katacoda
- Locally
- If you already installed Minikube
locally, run
minikube start
to create a cluster.
Enable the Ingress controller
-
To enable the NGINX Ingress controller, run the following command:
minikube addons enable ingress
-
Verify that the NGINX Ingress controller is running
kubectl get pods -n ingress-nginx
Note: It can take up to a minute before you see these pods running OK.The output is similar to:
NAME READY STATUS RESTARTS AGE ingress-nginx-admission-create-g9g49 0/1 Completed 0 11m ingress-nginx-admission-patch-rqp78 0/1 Completed 1 11m ingress-nginx-controller-59b45fb494-26npt 1/1 Running 0 11m
kubectl get pods -n kube-system
Note: It can take up to a minute before you see these pods running OK.The output is similar to:
NAME READY STATUS RESTARTS AGE default-http-backend-59868b7dd6-xb8tq 1/1 Running 0 1m kube-addon-manager-minikube 1/1 Running 0 3m kube-dns-6dcb57bcc8-n4xd4 3/3 Running 0 2m kubernetes-dashboard-5498ccf677-b8p5h 1/1 Running 0 2m nginx-ingress-controller-5984b97644-rnkrg 1/1 Running 0 1m storage-provisioner 1/1 Running 0 2m
Make sure that you see a Pod with a name that starts with
nginx-ingress-controller-
.
Deploy a hello, world app
-
Create a Deployment using the following command:
kubectl create deployment web --image=gcr.io/google-samples/hello-app:1.0
The output should be:
deployment.apps/web created
-
Expose the Deployment:
kubectl expose deployment web --type=NodePort --port=8080
The output should be:
service/web exposed
-
Verify the Service is created and is available on a node port:
kubectl get service web
The output is similar to:
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE web NodePort 10.104.133.249 <none> 8080:31637/TCP 12m
-
Visit the Service via NodePort:
minikube service web --url
The output is similar to:
http://172.17.0.15:31637
Note: Katacoda environment only: at the top of the terminal panel, click the plus sign, and then click Select port to view on Host 1. Enter the NodePort, in this case31637
, and then click Display Port.The output is similar to:
Hello, world! Version: 1.0.0 Hostname: web-55b8c6998d-8k564
You can now access the sample app via the Minikube IP address and NodePort. The next step lets you access the app using the Ingress resource.
Create an Ingress
The following manifest defines an Ingress that sends traffic to your Service via hello-world.info.
-
Create
example-ingress.yaml
from the following file:apiVersion: networking.k8s.io/v1 kind: Ingress metadata: name: example-ingress annotations: nginx.ingress.kubernetes.io/rewrite-target: /$1 spec: rules: - host: hello-world.info http: paths: - path: / pathType: Prefix backend: service: name: web port: number: 8080
-
Create the Ingress object by running the following command:
kubectl apply -f https://k8s.io/examples/service/networking/example-ingress.yaml
The output should be:
ingress.networking.k8s.io/example-ingress created
-
Verify the IP address is set:
kubectl get ingress
Note: This can take a couple of minutes.You should see an IPv4 address in the ADDRESS column; for example:
NAME CLASS HOSTS ADDRESS PORTS AGE example-ingress <none> hello-world.info 172.17.0.15 80 38s
-
Add the following line to the bottom of the
/etc/hosts
file on your computer (you will need administrator access):172.17.0.15 hello-world.info
Note: If you are running Minikube locally, useminikube ip
to get the external IP. The IP address displayed within the ingress list will be the internal IP.After you make this change, your web browser sends requests for hello-world.info URLs to Minikube.
-
Verify that the Ingress controller is directing traffic:
curl hello-world.info
You should see:
Hello, world! Version: 1.0.0 Hostname: web-55b8c6998d-8k564
Note: If you are running Minikube locally, you can visit hello-world.info from your browser.
Create a second Deployment
-
Create another Deployment using the following command:
kubectl create deployment web2 --image=gcr.io/google-samples/hello-app:2.0
The output should be:
deployment.apps/web2 created
-
Expose the second Deployment:
kubectl expose deployment web2 --port=8080 --type=NodePort
The output should be:
service/web2 exposed
Edit the existing Ingress
-
Edit the existing
example-ingress.yaml
manifest, and add the following lines at the end:- path: /v2 pathType: Prefix backend: service: name: web2 port: number: 8080
-
Apply the changes:
kubectl apply -f example-ingress.yaml
You should see:
ingress.networking/example-ingress configured
Test your Ingress
-
Access the 1st version of the Hello World app.
curl hello-world.info
The output is similar to:
Hello, world! Version: 1.0.0 Hostname: web-55b8c6998d-8k564
-
Access the 2nd version of the Hello World app.
curl hello-world.info/v2
The output is similar to:
Hello, world! Version: 2.0.0 Hostname: web2-75cd47646f-t8cjk
Note: If you are running Minikube locally, you can visit hello-world.info and hello-world.info/v2 from your browser.
What's next
- Read more about Ingress
- Read more about Ingress Controllers
- Read more about Services
10 - Communicate Between Containers in the Same Pod Using a Shared Volume
This page shows how to use a Volume to communicate between two Containers running in the same Pod. See also how to allow processes to communicate by sharing process namespace between containers.
Before you begin
You need to have a Kubernetes cluster, and the kubectl command-line tool must be configured to communicate with your cluster. It is recommended to run this tutorial on a cluster with at least two nodes that are not acting as control plane hosts. If you do not already have a cluster, you can create one by using minikube or you can use one of these Kubernetes playgrounds:
To check the version, enterkubectl version
.
Creating a Pod that runs two Containers
In this exercise, you create a Pod that runs two Containers. The two containers share a Volume that they can use to communicate. Here is the configuration file for the Pod:
apiVersion: v1
kind: Pod
metadata:
name: two-containers
spec:
restartPolicy: Never
volumes:
- name: shared-data
emptyDir: {}
containers:
- name: nginx-container
image: nginx
volumeMounts:
- name: shared-data
mountPath: /usr/share/nginx/html
- name: debian-container
image: debian
volumeMounts:
- name: shared-data
mountPath: /pod-data
command: ["/bin/sh"]
args: ["-c", "echo Hello from the debian container > /pod-data/index.html"]
In the configuration file, you can see that the Pod has a Volume named
shared-data
.
The first container listed in the configuration file runs an nginx server. The
mount path for the shared Volume is /usr/share/nginx/html
.
The second container is based on the debian image, and has a mount path of
/pod-data
. The second container runs the following command and then terminates.
echo Hello from the debian container > /pod-data/index.html
Notice that the second container writes the index.html
file in the root
directory of the nginx server.
Create the Pod and the two Containers:
kubectl apply -f https://k8s.io/examples/pods/two-container-pod.yaml
View information about the Pod and the Containers:
kubectl get pod two-containers --output=yaml
Here is a portion of the output:
apiVersion: v1
kind: Pod
metadata:
...
name: two-containers
namespace: default
...
spec:
...
containerStatuses:
- containerID: docker://c1d8abd1 ...
image: debian
...
lastState:
terminated:
...
name: debian-container
...
- containerID: docker://96c1ff2c5bb ...
image: nginx
...
name: nginx-container
...
state:
running:
...
You can see that the debian Container has terminated, and the nginx Container is still running.
Get a shell to nginx Container:
kubectl exec -it two-containers -c nginx-container -- /bin/bash
In your shell, verify that nginx is running:
root@two-containers:/# apt-get update
root@two-containers:/# apt-get install curl procps
root@two-containers:/# ps aux
The output is similar to this:
USER PID ... STAT START TIME COMMAND
root 1 ... Ss 21:12 0:00 nginx: master process nginx -g daemon off;
Recall that the debian Container created the index.html
file in the nginx root
directory. Use curl
to send a GET request to the nginx server:
root@two-containers:/# curl localhost
The output shows that nginx serves a web page written by the debian container:
Hello from the debian container
Discussion
The primary reason that Pods can have multiple containers is to support helper applications that assist a primary application. Typical examples of helper applications are data pullers, data pushers, and proxies. Helper and primary applications often need to communicate with each other. Typically this is done through a shared filesystem, as shown in this exercise, or through the loopback network interface, localhost. An example of this pattern is a web server along with a helper program that polls a Git repository for new updates.
The Volume in this exercise provides a way for Containers to communicate during the life of the Pod. If the Pod is deleted and recreated, any data stored in the shared Volume is lost.
What's next
-
Learn more about patterns for composite containers.
-
Learn about composite containers for modular architecture.
-
See Configure a Pod to share process namespace between containers in a Pod
-
See Volume.
-
See Pod.
11 - Configure DNS for a Cluster
Kubernetes offers a DNS cluster addon, which most of the supported environments enable by default. In Kubernetes version 1.11 and later, CoreDNS is recommended and is installed by default with kubeadm.
For more information on how to configure CoreDNS for a Kubernetes cluster, see the Customizing DNS Service. An example demonstrating how to use Kubernetes DNS with kube-dns, see the Kubernetes DNS sample plugin.