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Configuration
- 1: Example: Configuring a Java Microservice
- 2: Updating Configuration via a ConfigMap
- 3: Configuring Redis using a ConfigMap
1 - Example: Configuring a Java Microservice
1.1 - Externalizing config using MicroProfile, ConfigMaps and Secrets
In this tutorial you will learn how and why to externalize your microservice’s configuration. Specifically, you will learn how to use Kubernetes ConfigMaps and Secrets to set environment variables and then consume them using MicroProfile Config.
Before you begin
Creating Kubernetes ConfigMaps & Secrets
There are several ways to set environment variables for a Docker container in Kubernetes, including: Dockerfile, kubernetes.yml, Kubernetes ConfigMaps, and Kubernetes Secrets. In the tutorial, you will learn how to use the latter two for setting your environment variables whose values will be injected into your microservices. One of the benefits for using ConfigMaps and Secrets is that they can be re-used across multiple containers, including being assigned to different environment variables for the different containers.
ConfigMaps are API Objects that store non-confidential key-value pairs. In the Interactive Tutorial you will learn how to use a ConfigMap to store the application's name. For more information regarding ConfigMaps, you can find the documentation here.
Although Secrets are also used to store key-value pairs, they differ from ConfigMaps in that they're intended for confidential/sensitive information and are stored using Base64 encoding. This makes secrets the appropriate choice for storing such things as credentials, keys, and tokens, the former of which you'll do in the Interactive Tutorial. For more information on Secrets, you can find the documentation here.
Externalizing Config from Code
Externalized application configuration is useful because configuration usually changes depending on your environment. In order to accomplish this, we'll use Java's Contexts and Dependency Injection (CDI) and MicroProfile Config. MicroProfile Config is a feature of MicroProfile, a set of open Java technologies for developing and deploying cloud-native microservices.
CDI provides a standard dependency injection capability enabling an application to be assembled from collaborating, loosely-coupled beans. MicroProfile Config provides apps and microservices a standard way to obtain config properties from various sources, including the application, runtime, and environment. Based on the source's defined priority, the properties are automatically combined into a single set of properties that the application can access via an API. Together, CDI & MicroProfile will be used in the Interactive Tutorial to retrieve the externally provided properties from the Kubernetes ConfigMaps and Secrets and get injected into your application code.
Many open source frameworks and runtimes implement and support MicroProfile Config. Throughout the interactive tutorial, you'll be using Open Liberty, a flexible open-source Java runtime for building and running cloud-native apps and microservices. However, any MicroProfile compatible runtime could be used instead.
Objectives
- Create a Kubernetes ConfigMap and Secret
- Inject microservice configuration using MicroProfile Config
Example: Externalizing config using MicroProfile, ConfigMaps and Secrets
2 - Updating Configuration via a ConfigMap
This page provides a step-by-step example of updating configuration within a Pod via a ConfigMap
and builds upon the Configure a Pod to Use a ConfigMap task.
At the end of this tutorial, you will understand how to change the configuration for a running application.
This tutorial uses the alpine
and nginx
images as examples.
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:
You need to have the curl command-line tool for making HTTP requests from
the terminal or command prompt. If you do not have curl
available, you can install it. Check the
documentation for your local operating system.
Objectives
- Update configuration via a ConfigMap mounted as a Volume
- Update environment variables of a Pod via a ConfigMap
- Update configuration via a ConfigMap in a multi-container Pod
- Update configuration via a ConfigMap in a Pod possessing a Sidecar Container
Update configuration via a ConfigMap mounted as a Volume
Use the kubectl create configmap
command to create a ConfigMap from
literal values:
kubectl create configmap sport --from-literal=sport=football
Below is an example of a Deployment manifest with the ConfigMap sport
mounted as a
volume into the Pod's only container.
apiVersion: apps/v1
kind: Deployment
metadata:
name: configmap-volume
labels:
app.kubernetes.io/name: configmap-volume
spec:
replicas: 3
selector:
matchLabels:
app.kubernetes.io/name: configmap-volume
template:
metadata:
labels:
app.kubernetes.io/name: configmap-volume
spec:
containers:
- name: alpine
image: alpine:3
command:
- /bin/sh
- -c
- while true; do echo "$(date) My preferred sport is $(cat /etc/config/sport)";
sleep 10; done;
ports:
- containerPort: 80
volumeMounts:
- name: config-volume
mountPath: /etc/config
volumes:
- name: config-volume
configMap:
name: sport
Create the Deployment:
kubectl apply -f https://k8s.io/examples/deployments/deployment-with-configmap-as-volume.yaml
Check the pods for this Deployment to ensure they are ready (matching by selector):
kubectl get pods --selector=app.kubernetes.io/name=configmap-volume
You should see an output similar to:
NAME READY STATUS RESTARTS AGE
configmap-volume-6b976dfdcf-qxvbm 1/1 Running 0 72s
configmap-volume-6b976dfdcf-skpvm 1/1 Running 0 72s
configmap-volume-6b976dfdcf-tbc6r 1/1 Running 0 72s
On each node where one of these Pods is running, the kubelet fetches the data for that ConfigMap and translates it to files in a local volume. The kubelet then mounts that volume into the container, as specified in the Pod template. The code running in that container loads the information from the file and uses it to print a report to stdout. You can check this report by viewing the logs for one of the Pods in that Deployment:
# Pick one Pod that belongs to the Deployment, and view its logs
kubectl logs deployments/configmap-volume
You should see an output similar to:
Found 3 pods, using pod/configmap-volume-76d9c5678f-x5rgj
Thu Jan 4 14:06:46 UTC 2024 My preferred sport is football
Thu Jan 4 14:06:56 UTC 2024 My preferred sport is football
Thu Jan 4 14:07:06 UTC 2024 My preferred sport is football
Thu Jan 4 14:07:16 UTC 2024 My preferred sport is football
Thu Jan 4 14:07:26 UTC 2024 My preferred sport is football
Edit the ConfigMap:
kubectl edit configmap sport
In the editor that appears, change the value of key sport
from football
to cricket
. Save your changes.
The kubectl tool updates the ConfigMap accordingly (if you see an error, try again).
Here's an example of how that manifest could look after you edit it:
apiVersion: v1
data:
sport: cricket
kind: ConfigMap
# You can leave the existing metadata as they are.
# The values you'll see won't exactly match these.
metadata:
creationTimestamp: "2024-01-04T14:05:06Z"
name: sport
namespace: default
resourceVersion: "1743935"
uid: 024ee001-fe72-487e-872e-34d6464a8a23
You should see the following output:
configmap/sport edited
Tail (follow the latest entries in) the logs of one of the pods that belongs to this Deployment:
kubectl logs deployments/configmap-volume --follow
After few seconds, you should see the log output change as follows:
Thu Jan 4 14:11:36 UTC 2024 My preferred sport is football
Thu Jan 4 14:11:46 UTC 2024 My preferred sport is football
Thu Jan 4 14:11:56 UTC 2024 My preferred sport is football
Thu Jan 4 14:12:06 UTC 2024 My preferred sport is cricket
Thu Jan 4 14:12:16 UTC 2024 My preferred sport is cricket
When you have a ConfigMap that is mapped into a running Pod using either a
configMap
volume or a projected
volume, and you update that ConfigMap,
the running Pod sees the update almost immediately.
However, your application only sees the change if it is written to either poll for changes,
or watch for file updates.
An application that loads its configuration once at startup will not notice a change.
Note:
The total delay from the moment when the ConfigMap is updated to the moment when new keys are projected to the Pod can be as long as kubelet sync period.Also check Mounted ConfigMaps are updated automatically.
Update environment variables of a Pod via a ConfigMap
Use the kubectl create configmap
command to create a ConfigMap from
literal values:
kubectl create configmap fruits --from-literal=fruits=apples
Below is an example of a Deployment manifest with an environment variable configured via the ConfigMap fruits
.
apiVersion: apps/v1
kind: Deployment
metadata:
name: configmap-env-var
labels:
app.kubernetes.io/name: configmap-env-var
spec:
replicas: 3
selector:
matchLabels:
app.kubernetes.io/name: configmap-env-var
template:
metadata:
labels:
app.kubernetes.io/name: configmap-env-var
spec:
containers:
- name: alpine
image: alpine:3
env:
- name: FRUITS
valueFrom:
configMapKeyRef:
key: fruits
name: fruits
command:
- /bin/sh
- -c
- while true; do echo "$(date) The basket is full of $FRUITS";
sleep 10; done;
ports:
- containerPort: 80
Create the Deployment:
kubectl apply -f https://k8s.io/examples/deployments/deployment-with-configmap-as-envvar.yaml
Check the pods for this Deployment to ensure they are ready (matching by selector):
kubectl get pods --selector=app.kubernetes.io/name=configmap-env-var
You should see an output similar to:
NAME READY STATUS RESTARTS AGE
configmap-env-var-59cfc64f7d-74d7z 1/1 Running 0 46s
configmap-env-var-59cfc64f7d-c4wmj 1/1 Running 0 46s
configmap-env-var-59cfc64f7d-dpr98 1/1 Running 0 46s
The key-value pair in the ConfigMap is configured as an environment variable in the container of the Pod. Check this by viewing the logs of one Pod that belongs to the Deployment.
kubectl logs deployment/configmap-env-var
You should see an output similar to:
Found 3 pods, using pod/configmap-env-var-7c994f7769-l74nq
Thu Jan 4 16:07:06 UTC 2024 The basket is full of apples
Thu Jan 4 16:07:16 UTC 2024 The basket is full of apples
Thu Jan 4 16:07:26 UTC 2024 The basket is full of apples
Edit the ConfigMap:
kubectl edit configmap fruits
In the editor that appears, change the value of key fruits
from apples
to mangoes
. Save your changes.
The kubectl tool updates the ConfigMap accordingly (if you see an error, try again).
Here's an example of how that manifest could look after you edit it:
apiVersion: v1
data:
fruits: mangoes
kind: ConfigMap
# You can leave the existing metadata as they are.
# The values you'll see won't exactly match these.
metadata:
creationTimestamp: "2024-01-04T16:04:19Z"
name: fruits
namespace: default
resourceVersion: "1749472"
You should see the following output:
configmap/fruits edited
Tail the logs of the Deployment and observe the output for few seconds:
# As the text explains, the output does NOT change
kubectl logs deployments/configmap-env-var --follow
Notice that the output remains unchanged, even though you edited the ConfigMap:
Thu Jan 4 16:12:56 UTC 2024 The basket is full of apples
Thu Jan 4 16:13:06 UTC 2024 The basket is full of apples
Thu Jan 4 16:13:16 UTC 2024 The basket is full of apples
Thu Jan 4 16:13:26 UTC 2024 The basket is full of apples
Note:
Although the value of the key inside the ConfigMap has changed, the environment variable in the Pod still shows the earlier value. This is because environment variables for a process running inside a Pod are not updated when the source data changes; if you wanted to force an update, you would need to have Kubernetes replace your existing Pods. The new Pods would then run with the updated information.You can trigger that replacement. Perform a rollout for the Deployment, using
kubectl rollout
:
# Trigger the rollout
kubectl rollout restart deployment configmap-env-var
# Wait for the rollout to complete
kubectl rollout status deployment configmap-env-var --watch=true
Next, check the Deployment:
kubectl get deployment configmap-env-var
You should see an output similar to:
NAME READY UP-TO-DATE AVAILABLE AGE
configmap-env-var 3/3 3 3 12m
Check the Pods:
kubectl get pods --selector=app.kubernetes.io/name=configmap-env-var
The rollout causes Kubernetes to make a new ReplicaSet for the Deployment; that means the existing Pods eventually terminate, and new ones are created. After few seconds, you should see an output similar to:
NAME READY STATUS RESTARTS AGE
configmap-env-var-6d94d89bf5-2ph2l 1/1 Running 0 13s
configmap-env-var-6d94d89bf5-74twx 1/1 Running 0 8s
configmap-env-var-6d94d89bf5-d5vx8 1/1 Running 0 11s
Note:
Please wait for the older Pods to fully terminate before proceeding with the next steps.View the logs for a Pod in this Deployment:
# Pick one Pod that belongs to the Deployment, and view its logs
kubectl logs deployment/configmap-env-var
You should see an output similar to the below:
Found 3 pods, using pod/configmap-env-var-6d9ff89fb6-bzcf6
Thu Jan 4 16:30:35 UTC 2024 The basket is full of mangoes
Thu Jan 4 16:30:45 UTC 2024 The basket is full of mangoes
Thu Jan 4 16:30:55 UTC 2024 The basket is full of mangoes
This demonstrates the scenario of updating environment variables in a Pod that are derived from a ConfigMap. Changes to the ConfigMap values are applied to the Pod during the subsequent rollout. If Pods get created for another reason, such as scaling up the Deployment, then the new Pods also use the latest configuration values; if you don't trigger a rollout, then you might find that your app is running with a mix of old and new environment variable values.
Update configuration via a ConfigMap in a multi-container Pod
Use the kubectl create configmap
command to create a ConfigMap from
literal values:
kubectl create configmap color --from-literal=color=red
Below is an example manifest for a Deployment that manages a set of Pods, each with two containers.
The two containers share an emptyDir
volume that they use to communicate.
The first container runs a web server (nginx
). The mount path for the shared volume in the
web server container is /usr/share/nginx/html
. The second helper container is based on alpine
,
and for this container the emptyDir
volume is mounted at /pod-data
. The helper container writes
a file in HTML that has its content based on a ConfigMap. The web server container serves the HTML via HTTP.
apiVersion: apps/v1
kind: Deployment
metadata:
name: configmap-two-containers
labels:
app.kubernetes.io/name: configmap-two-containers
spec:
replicas: 3
selector:
matchLabels:
app.kubernetes.io/name: configmap-two-containers
template:
metadata:
labels:
app.kubernetes.io/name: configmap-two-containers
spec:
volumes:
- name: shared-data
emptyDir: {}
- name: config-volume
configMap:
name: color
containers:
- name: nginx
image: nginx
volumeMounts:
- name: shared-data
mountPath: /usr/share/nginx/html
- name: alpine
image: alpine:3
volumeMounts:
- name: shared-data
mountPath: /pod-data
- name: config-volume
mountPath: /etc/config
command:
- /bin/sh
- -c
- while true; do echo "$(date) My preferred color is $(cat /etc/config/color)" > /pod-data/index.html;
sleep 10; done;
Create the Deployment:
kubectl apply -f https://k8s.io/examples/deployments/deployment-with-configmap-two-containers.yaml
Check the pods for this Deployment to ensure they are ready (matching by selector):
kubectl get pods --selector=app.kubernetes.io/name=configmap-two-containers
You should see an output similar to:
NAME READY STATUS RESTARTS AGE
configmap-two-containers-565fb6d4f4-2xhxf 2/2 Running 0 20s
configmap-two-containers-565fb6d4f4-g5v4j 2/2 Running 0 20s
configmap-two-containers-565fb6d4f4-mzsmf 2/2 Running 0 20s
Expose the Deployment (the kubectl
tool creates a
Service for you):
kubectl expose deployment configmap-two-containers --name=configmap-service --port=8080 --target-port=80
Use kubectl
to forward the port:
# this stays running in the background
kubectl port-forward service/configmap-service 8080:8080 &
Access the service.
curl http://localhost:8080
You should see an output similar to:
Fri Jan 5 08:08:22 UTC 2024 My preferred color is red
Edit the ConfigMap:
kubectl edit configmap color
In the editor that appears, change the value of key color
from red
to blue
. Save your changes.
The kubectl tool updates the ConfigMap accordingly (if you see an error, try again).
Here's an example of how that manifest could look after you edit it:
apiVersion: v1
data:
color: blue
kind: ConfigMap
# You can leave the existing metadata as they are.
# The values you'll see won't exactly match these.
metadata:
creationTimestamp: "2024-01-05T08:12:05Z"
name: color
namespace: configmap
resourceVersion: "1801272"
uid: 80d33e4a-cbb4-4bc9-ba8c-544c68e425d6
Loop over the service URL for few seconds.
# Cancel this when you're happy with it (Ctrl-C)
while true; do curl --connect-timeout 7.5 http://localhost:8080; sleep 10; done
You should see the output change as follows:
Fri Jan 5 08:14:00 UTC 2024 My preferred color is red
Fri Jan 5 08:14:02 UTC 2024 My preferred color is red
Fri Jan 5 08:14:20 UTC 2024 My preferred color is red
Fri Jan 5 08:14:22 UTC 2024 My preferred color is red
Fri Jan 5 08:14:32 UTC 2024 My preferred color is blue
Fri Jan 5 08:14:43 UTC 2024 My preferred color is blue
Fri Jan 5 08:15:00 UTC 2024 My preferred color is blue
Update configuration via a ConfigMap in a Pod possessing a sidecar container
The above scenario can be replicated by using a Sidecar Container
as a helper container to write the HTML file.
As a Sidecar Container is conceptually an Init Container, it is guaranteed to start before the main web server container.
This ensures that the HTML file is always available when the web server is ready to serve it.
Please see Enabling sidecar containers to utilize this feature.
If you are continuing from the previous scenario, you can reuse the ConfigMap named color
for this scenario.
If you are executing this scenario independently, use the kubectl create configmap
command to create a ConfigMap
from literal values:
kubectl create configmap color --from-literal=color=blue
Below is an example manifest for a Deployment that manages a set of Pods, each with a main container and
a sidecar container. The two containers share an emptyDir
volume that they use to communicate.
The main container runs a web server (NGINX). The mount path for the shared volume in the web server container
is /usr/share/nginx/html
. The second container is a Sidecar Container based on Alpine Linux which acts as
a helper container. For this container the emptyDir
volume is mounted at /pod-data
. The Sidecar Container
writes a file in HTML that has its content based on a ConfigMap. The web server container serves the HTML via HTTP.
apiVersion: apps/v1
kind: Deployment
metadata:
name: configmap-sidecar-container
labels:
app.kubernetes.io/name: configmap-sidecar-container
spec:
replicas: 3
selector:
matchLabels:
app.kubernetes.io/name: configmap-sidecar-container
template:
metadata:
labels:
app.kubernetes.io/name: configmap-sidecar-container
spec:
volumes:
- name: shared-data
emptyDir: {}
- name: config-volume
configMap:
name: color
containers:
- name: nginx
image: nginx
volumeMounts:
- name: shared-data
mountPath: /usr/share/nginx/html
initContainers:
- name: alpine
image: alpine:3
restartPolicy: Always
volumeMounts:
- name: shared-data
mountPath: /pod-data
- name: config-volume
mountPath: /etc/config
command:
- /bin/sh
- -c
- while true; do echo "$(date) My preferred color is $(cat /etc/config/color)" > /pod-data/index.html;
sleep 10; done;
Create the Deployment:
kubectl apply -f https://k8s.io/examples/deployments/deployment-with-configmap-and-sidecar-container.yaml
Check the pods for this Deployment to ensure they are ready (matching by selector):
kubectl get pods --selector=app.kubernetes.io/name=configmap-sidecar-container
You should see an output similar to:
NAME READY STATUS RESTARTS AGE
configmap-sidecar-container-5fb59f558b-87rp7 2/2 Running 0 94s
configmap-sidecar-container-5fb59f558b-ccs7s 2/2 Running 0 94s
configmap-sidecar-container-5fb59f558b-wnmgk 2/2 Running 0 94s
Expose the Deployment (the kubectl
tool creates a
Service for you):
kubectl expose deployment configmap-sidecar-container --name=configmap-sidecar-service --port=8081 --target-port=80
Use kubectl
to forward the port:
# this stays running in the background
kubectl port-forward service/configmap-sidecar-service 8081:8081 &
Access the service.
curl http://localhost:8081
You should see an output similar to:
Sat Feb 17 13:09:05 UTC 2024 My preferred color is blue
Edit the ConfigMap:
kubectl edit configmap color
In the editor that appears, change the value of key color
from blue
to green
. Save your changes.
The kubectl tool updates the ConfigMap accordingly (if you see an error, try again).
Here's an example of how that manifest could look after you edit it:
apiVersion: v1
data:
color: green
kind: ConfigMap
# You can leave the existing metadata as they are.
# The values you'll see won't exactly match these.
metadata:
creationTimestamp: "2024-02-17T12:20:30Z"
name: color
namespace: default
resourceVersion: "1054"
uid: e40bb34c-58df-4280-8bea-6ed16edccfaa
Loop over the service URL for few seconds.
# Cancel this when you're happy with it (Ctrl-C)
while true; do curl --connect-timeout 7.5 http://localhost:8081; sleep 10; done
You should see the output change as follows:
Sat Feb 17 13:12:35 UTC 2024 My preferred color is blue
Sat Feb 17 13:12:45 UTC 2024 My preferred color is blue
Sat Feb 17 13:12:55 UTC 2024 My preferred color is blue
Sat Feb 17 13:13:05 UTC 2024 My preferred color is blue
Sat Feb 17 13:13:15 UTC 2024 My preferred color is green
Sat Feb 17 13:13:25 UTC 2024 My preferred color is green
Sat Feb 17 13:13:35 UTC 2024 My preferred color is green
Update configuration via an immutable ConfigMap that is mounted as a volume
Note:
Immutable ConfigMaps are especially used for configuration that is constant and is not expected to change over time. Marking a ConfigMap as immutable allows a performance improvement where the kubelet does not watch for changes.
If you do need to make a change, you should plan to either:
- change the name of the ConfigMap, and switch to running Pods that reference the new name
- replace all the nodes in your cluster that have previously run a Pod that used the old value
- restart the kubelet on any node where the kubelet previously loaded the old ConfigMap
An example manifest for an Immutable ConfigMap is shown below.
apiVersion: v1
data:
company_name: "ACME, Inc." # existing fictional company name
kind: ConfigMap
immutable: true
metadata:
name: company-name-20150801
Create the Immutable ConfigMap:
kubectl apply -f https://k8s.io/examples/configmap/immutable-configmap.yaml
Below is an example of a Deployment manifest with the Immutable ConfigMap company-name-20150801
mounted as a
volume into the Pod's only container.
apiVersion: apps/v1
kind: Deployment
metadata:
name: immutable-configmap-volume
labels:
app.kubernetes.io/name: immutable-configmap-volume
spec:
replicas: 3
selector:
matchLabels:
app.kubernetes.io/name: immutable-configmap-volume
template:
metadata:
labels:
app.kubernetes.io/name: immutable-configmap-volume
spec:
containers:
- name: alpine
image: alpine:3
command:
- /bin/sh
- -c
- while true; do echo "$(date) The name of the company is $(cat /etc/config/company_name)";
sleep 10; done;
ports:
- containerPort: 80
volumeMounts:
- name: config-volume
mountPath: /etc/config
volumes:
- name: config-volume
configMap:
name: company-name-20150801
Create the Deployment:
kubectl apply -f https://k8s.io/examples/deployments/deployment-with-immutable-configmap-as-volume.yaml
Check the pods for this Deployment to ensure they are ready (matching by selector):
kubectl get pods --selector=app.kubernetes.io/name=immutable-configmap-volume
You should see an output similar to:
NAME READY STATUS RESTARTS AGE
immutable-configmap-volume-78b6fbff95-5gsfh 1/1 Running 0 62s
immutable-configmap-volume-78b6fbff95-7vcj4 1/1 Running 0 62s
immutable-configmap-volume-78b6fbff95-vdslm 1/1 Running 0 62s
The Pod's container refers to the data defined in the ConfigMap and uses it to print a report to stdout. You can check this report by viewing the logs for one of the Pods in that Deployment:
# Pick one Pod that belongs to the Deployment, and view its logs
kubectl logs deployments/immutable-configmap-volume
You should see an output similar to:
Found 3 pods, using pod/immutable-configmap-volume-78b6fbff95-5gsfh
Wed Mar 20 03:52:34 UTC 2024 The name of the company is ACME, Inc.
Wed Mar 20 03:52:44 UTC 2024 The name of the company is ACME, Inc.
Wed Mar 20 03:52:54 UTC 2024 The name of the company is ACME, Inc.
Note:
Once a ConfigMap is marked as immutable, it is not possible to revert this change nor to mutate the contents of the data or the binaryData field.In order to modify the behavior of the Pods that use this configuration, you will create a new immutable ConfigMap and edit the Deployment to define a slightly different pod template, referencing the new ConfigMap.
Create a new immutable ConfigMap by using the manifest shown below:
apiVersion: v1
data:
company_name: "Fiktivesunternehmen GmbH" # new fictional company name
kind: ConfigMap
immutable: true
metadata:
name: company-name-20240312
kubectl apply -f https://k8s.io/examples/configmap/new-immutable-configmap.yaml
You should see an output similar to:
configmap/company-name-20240312 created
Check the newly created ConfigMap:
kubectl get configmap
You should see an output displaying both the old and new ConfigMaps:
NAME DATA AGE
company-name-20150801 1 22m
company-name-20240312 1 24s
Modify the Deployment to reference the new ConfigMap.
Edit the Deployment:
kubectl edit deployment immutable-configmap-volume
In the editor that appears, update the existing volume definition to use the new ConfigMap.
volumes:
- configMap:
defaultMode: 420
name: company-name-20240312 # Update this field
name: config-volume
You should see the following output:
deployment.apps/immutable-configmap-volume edited
This will trigger a rollout. Wait for all the previous Pods to terminate and the new Pods to be in a ready state.
Monitor the status of the Pods:
kubectl get pods --selector=app.kubernetes.io/name=immutable-configmap-volume
NAME READY STATUS RESTARTS AGE
immutable-configmap-volume-5fdb88fcc8-29v8n 1/1 Running 0 13s
immutable-configmap-volume-5fdb88fcc8-52ddd 1/1 Running 0 14s
immutable-configmap-volume-5fdb88fcc8-n5jx4 1/1 Running 0 15s
immutable-configmap-volume-78b6fbff95-5gsfh 1/1 Terminating 0 32m
immutable-configmap-volume-78b6fbff95-7vcj4 1/1 Terminating 0 32m
immutable-configmap-volume-78b6fbff95-vdslm 1/1 Terminating 0 32m
You should eventually see an output similar to:
NAME READY STATUS RESTARTS AGE
immutable-configmap-volume-5fdb88fcc8-29v8n 1/1 Running 0 43s
immutable-configmap-volume-5fdb88fcc8-52ddd 1/1 Running 0 44s
immutable-configmap-volume-5fdb88fcc8-n5jx4 1/1 Running 0 45s
View the logs for a Pod in this Deployment:
# Pick one Pod that belongs to the Deployment, and view its logs
kubectl logs deployment/immutable-configmap-volume
You should see an output similar to the below:
Found 3 pods, using pod/immutable-configmap-volume-5fdb88fcc8-n5jx4
Wed Mar 20 04:24:17 UTC 2024 The name of the company is Fiktivesunternehmen GmbH
Wed Mar 20 04:24:27 UTC 2024 The name of the company is Fiktivesunternehmen GmbH
Wed Mar 20 04:24:37 UTC 2024 The name of the company is Fiktivesunternehmen GmbH
Once all the deployments have migrated to use the new immutable ConfigMap, it is advised to delete the old one.
kubectl delete configmap company-name-20150801
Summary
Changes to a ConfigMap mounted as a Volume on a Pod are available seamlessly after the subsequent kubelet sync.
Changes to a ConfigMap that configures environment variables for a Pod are available after the subsequent rollout for the Pod.
Once a ConfigMap is marked as immutable, it is not possible to revert this change
(you cannot make an immutable ConfigMap mutable), and you also cannot make any change
to the contents of the data
or the binaryData
field. You can delete and recreate
the ConfigMap, or you can make a new different ConfigMap. When you delete a ConfigMap,
running containers and their Pods maintain a mount point to any volume that referenced
that existing ConfigMap.
Cleaning up
Terminate the kubectl port-forward
commands in case they are running.
Delete the resources created during the tutorial:
kubectl delete deployment configmap-volume configmap-env-var configmap-two-containers configmap-sidecar-container immutable-configmap-volume
kubectl delete service configmap-service configmap-sidecar-service
kubectl delete configmap sport fruits color company-name-20240312
kubectl delete configmap company-name-20150801 # In case it was not handled during the task execution
3 - Configuring Redis using a ConfigMap
This page provides a real world example of how to configure Redis using a ConfigMap and builds upon the Configure a Pod to Use a ConfigMap task.
Objectives
- Create a ConfigMap with Redis configuration values
- Create a Redis Pod that mounts and uses the created ConfigMap
- Verify that the configuration was correctly applied.
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
.
- The example shown on this page works with
kubectl
1.14 and above. - Understand Configure a Pod to Use a ConfigMap.
Real World Example: Configuring Redis using a ConfigMap
Follow the steps below to configure a Redis cache using data stored in a ConfigMap.
First create a ConfigMap with an empty configuration block:
cat <<EOF >./example-redis-config.yaml
apiVersion: v1
kind: ConfigMap
metadata:
name: example-redis-config
data:
redis-config: ""
EOF
Apply the ConfigMap created above, along with a Redis pod manifest:
kubectl apply -f example-redis-config.yaml
kubectl apply -f https://raw.githubusercontent.com/kubernetes/website/main/content/en/examples/pods/config/redis-pod.yaml
Examine the contents of the Redis pod manifest and note the following:
- A volume named
config
is created byspec.volumes[1]
- The
key
andpath
underspec.volumes[1].configMap.items[0]
exposes theredis-config
key from theexample-redis-config
ConfigMap as a file namedredis.conf
on theconfig
volume. - The
config
volume is then mounted at/redis-master
byspec.containers[0].volumeMounts[1]
.
This has the net effect of exposing the data in data.redis-config
from the example-redis-config
ConfigMap above as /redis-master/redis.conf
inside the Pod.
apiVersion: v1
kind: Pod
metadata:
name: redis
spec:
containers:
- name: redis
image: redis:5.0.4
command:
- redis-server
- "/redis-master/redis.conf"
env:
- name: MASTER
value: "true"
ports:
- containerPort: 6379
resources:
limits:
cpu: "0.1"
volumeMounts:
- mountPath: /redis-master-data
name: data
- mountPath: /redis-master
name: config
volumes:
- name: data
emptyDir: {}
- name: config
configMap:
name: example-redis-config
items:
- key: redis-config
path: redis.conf
Examine the created objects:
kubectl get pod/redis configmap/example-redis-config
You should see the following output:
NAME READY STATUS RESTARTS AGE
pod/redis 1/1 Running 0 8s
NAME DATA AGE
configmap/example-redis-config 1 14s
Recall that we left redis-config
key in the example-redis-config
ConfigMap blank:
kubectl describe configmap/example-redis-config
You should see an empty redis-config
key:
Name: example-redis-config
Namespace: default
Labels: <none>
Annotations: <none>
Data
====
redis-config:
Use kubectl exec
to enter the pod and run the redis-cli
tool to check the current configuration:
kubectl exec -it redis -- redis-cli
Check maxmemory
:
127.0.0.1:6379> CONFIG GET maxmemory
It should show the default value of 0:
1) "maxmemory"
2) "0"
Similarly, check maxmemory-policy
:
127.0.0.1:6379> CONFIG GET maxmemory-policy
Which should also yield its default value of noeviction
:
1) "maxmemory-policy"
2) "noeviction"
Now let's add some configuration values to the example-redis-config
ConfigMap:
apiVersion: v1
kind: ConfigMap
metadata:
name: example-redis-config
data:
redis-config: |
maxmemory 2mb
maxmemory-policy allkeys-lru
Apply the updated ConfigMap:
kubectl apply -f example-redis-config.yaml
Confirm that the ConfigMap was updated:
kubectl describe configmap/example-redis-config
You should see the configuration values we just added:
Name: example-redis-config
Namespace: default
Labels: <none>
Annotations: <none>
Data
====
redis-config:
----
maxmemory 2mb
maxmemory-policy allkeys-lru
Check the Redis Pod again using redis-cli
via kubectl exec
to see if the configuration was applied:
kubectl exec -it redis -- redis-cli
Check maxmemory
:
127.0.0.1:6379> CONFIG GET maxmemory
It remains at the default value of 0:
1) "maxmemory"
2) "0"
Similarly, maxmemory-policy
remains at the noeviction
default setting:
127.0.0.1:6379> CONFIG GET maxmemory-policy
Returns:
1) "maxmemory-policy"
2) "noeviction"
The configuration values have not changed because the Pod needs to be restarted to grab updated values from associated ConfigMaps. Let's delete and recreate the Pod:
kubectl delete pod redis
kubectl apply -f https://raw.githubusercontent.com/kubernetes/website/main/content/en/examples/pods/config/redis-pod.yaml
Now re-check the configuration values one last time:
kubectl exec -it redis -- redis-cli
Check maxmemory
:
127.0.0.1:6379> CONFIG GET maxmemory
It should now return the updated value of 2097152:
1) "maxmemory"
2) "2097152"
Similarly, maxmemory-policy
has also been updated:
127.0.0.1:6379> CONFIG GET maxmemory-policy
It now reflects the desired value of allkeys-lru
:
1) "maxmemory-policy"
2) "allkeys-lru"
Clean up your work by deleting the created resources:
kubectl delete pod/redis configmap/example-redis-config
What's next
- Learn more about ConfigMaps.
- Follow an example of Updating configuration via a ConfigMap.