5 Strategies Of Kubernetes Deployment

Java Code GeeksMarch 31st, 2023Last Updated: August 29th, 2023

0 497 15 minutes read

Kubernetes Deployment is a Kubernetes resource object that defines how to create and manage a set of identical pods. Deployments are a way to declaratively manage a set of replica pods with the same template. They provide a higher-level abstraction for managing replica sets, and help ensure that the desired state of your application is maintained even in the face of failures or changes.

A Kubernetes deployment defines the desired state of the application, including the number of replicas, the container images, and the configuration of each replica. When you create a deployment, Kubernetes creates a replica set that manages the specified number of replicas of your application. The replica set ensures that the specified number of replicas is always running, and automatically creates or deletes replicas as necessary to maintain the desired state.

One of the key benefits of Kubernetes deployments is that they support rolling updates and rollbacks. When you update the configuration of a deployment, Kubernetes automatically creates a new replica set with the updated configuration, and gradually replaces the old replicas with new ones. This allows you to update your application without downtime or disruptions to your users. If there are issues with the new version of your application, you can easily rollback to the previous version using the same deployment object.

To create a Kubernetes deployment, you define a YAML or JSON file that describes the desired state of your application, including the container images, replicas, and other configuration parameters. You can then use the kubectl command-line tool to create, update, or delete the deployment object.

In summary, Kubernetes Deployments are a powerful tool for managing containerized applications, allowing you to declaratively define the desired state of your application and easily update or rollback your application without downtime.

1. Rolling Deployment Strategy

The Rolling Deployment Strategy is a Kubernetes deployment strategy that updates your application in a controlled manner by gradually replacing old instances with new ones, ensuring that there is always a minimum number of replicas available. This strategy allows you to minimize downtime and mitigate the risk of errors.

The Rolling Deployment Strategy works by creating a new version of your application and gradually updating the replicas of your deployment to use the new version. During the rolling update, the old and new versions of the application run side by side until all replicas have been updated. This approach allows you to maintain the availability of your application and minimize disruptions to your users.

Here are the basic steps involved in a rolling deployment:

Create a new version of your application: Update the container image or other configuration settings of your Kubernetes deployment to create a new version of your application.
Update the replicas: Use the kubectl command-line tool or Kubernetes dashboard to update the replicas of your deployment to use the new version of your application. You can do this by specifying the new image or configuration settings in the YAML or JSON file for your deployment.
Monitor the rollout: Monitor the progress of the rollout to ensure that it is proceeding smoothly. You can use the kubectl rollout status command to check the status of the update.
Verify the update: Once the rollout is complete, verify that the new version of your application is running correctly. You can use the kubectl describe command to view the details of your deployment and check the logs of your application pods to verify that they are running correctly.
Rollback if necessary: If there are any issues with the new version of your application, you can easily rollback to the previous version using the kubectl rollout undo command. This will revert your deployment to the previous version and ensure that your application continues to run correctly.

In summary, the Rolling Deployment Strategy is a safe and efficient way to update your Kubernetes deployment, allowing you to gradually replace old instances with new ones while minimizing downtime and disruptions to your users.

Below we will present an example of a rolling deployment in Kubernetes using the kubectl command-line tool:

Create a deployment with 3 replicas:

kubectl create deployment example-app --image=nginx --replicas=3

Update the container image to a new version:

kubectl set image deployment/example-app nginx=nginx:1.19.6

Monitor the rollout status:

kubectl rollout status deployment/example-app

Verify the update:

kubectl describe deployment example-app
kubectl get pods
kubectl logs <pod-name≶

Rollback to the previous version:

kubectl rollout undo deployment/example-app

These commands will create a deployment with 3 replicas using the Nginx container image, then update the deployment to use version 1.19.6 of the image using the set image command. The rollout status command is used to monitor the progress of the update, and the describe and get commands are used to verify that the new version of the application is running correctly. Finally, the rollout undo command is used to rollback to the previous version if necessary.

Note that this is a basic example and you may need to modify the commands based on your specific application and deployment requirements.

2. Blue/Green Deployment Strategy

The Blue/Green Deployment Strategy is a Kubernetes deployment strategy that allows you to update your application with zero downtime by creating a new version of your application and switching traffic from the old version to the new version. This approach allows you to test and validate the new version before it is made available to users.

The Blue/Green Deployment Strategy works by creating two identical environments: the “blue” environment, which represents the current version of your application, and the “green” environment, which represents the new version of your application. Once the green environment is fully tested and validated, traffic can be switched from the blue environment to the green environment.

Here are the basic steps involved in a Blue/Green Deployment Strategy:

Create a new version of your application: Update the container image or other configuration settings of your Kubernetes deployment to create a new version of your application.
Create a new deployment and service for the green environment: Create a new Kubernetes deployment and service for the new version of your application, using a different name or label selector than the blue environment.
Test the new version: Validate and test the new version of your application by directing a small amount of traffic to the green environment. You can use Kubernetes tools like Istio or Flagger to manage traffic shifting between the blue and green environments.
Switch traffic to the green environment: Once the new version of your application has been validated, you can switch traffic from the blue environment to the green environment using Kubernetes tools like Istio or Flagger.
Monitor the rollout: Monitor the progress of the rollout to ensure that it is proceeding smoothly. You can use the kubectl rollout status command to check the status of the update.
Verify the update: Once the rollout is complete, verify that the new version of your application is running correctly. You can use the kubectl describe command to view the details of your deployment and check the logs of your application pods to verify that they are running correctly.
Rollback if necessary: If there are any issues with the new version of your application, you can easily rollback to the previous version by switching traffic back to the blue environment.

In summary, the Blue/Green Deployment Strategy is a safe and efficient way to update your Kubernetes deployment, allowing you to test and validate the new version of your application before making it available to users, and ensuring zero downtime during the update process.

Here is an example of the Blue/Green Deployment Strategy in Kubernetes:

Create a deployment for the “blue” environment:

kubectl create deployment my-app --image=my-app:v1 --replicas=3

2. Create a service for the “blue” environment:

kubectl expose deployment my-app --port=80 --type=LoadBalancer --name=my-app-blue

3. Create a deployment for the “green” environment:

kubectl create deployment my-app-new --image=my-app:v2 --replicas=0

4. Create a service for the “green” environment:

kubectl expose deployment my-app-new --port=80 --type=LoadBalancer --name=my-app-green

5. Test the “green” environment:

kubectl scale deployment my-app-new --replicas=1

At this point, a single pod of the “green” environment is deployed. You can now test this version of your application by directing a small amount of traffic to the my-app-green service.

Switch traffic to the “green” environment:

kubectl scale deployment my-app --replicas=0
kubectl scale deployment my-app-new --replicas=3

This command will switch traffic from the “blue” environment to the “green” environment by scaling down the “blue” environment and scaling up the “green” environment.

Verify the update:

kubectl get pods

This command will show you that the new version of your application is now running in the “green” environment. You can also check the logs of the new pods to verify that they are running correctly.

Rollback if necessary:

kubectl scale deployment my-app --replicas=3
kubectl scale deployment my-app-new --replicas=0

This command will rollback the deployment by scaling up the “blue” environment and scaling down the “green” environment.

Note that this is a basic example and you may need to modify the commands based on your specific application and deployment requirements. Also, Kubernetes tools like Istio or Flagger can be used to manage traffic shifting between the blue and green environments.

3. Canary Deployment Strategy

The Canary Deployment Strategy is a Kubernetes deployment strategy that allows you to release a new version of your application to a small group of users, monitor its performance, and gradually increase the percentage of users that receive the new version. This approach helps to reduce the risk of deploying a new version of your application to all users at once and allows you to quickly roll back if any issues arise.

Here are the basic steps involved in a Canary Deployment Strategy:

Create a new version of your application: Update the container image or other configuration settings of your Kubernetes deployment to create a new version of your application.
Create a new deployment for the canary environment: Create a new Kubernetes deployment for the new version of your application, using a different name or label selector than the current deployment.
Define a traffic split between the current and canary environments: Use Kubernetes tools like Istio or Flagger to define a traffic split between the current deployment and the canary deployment. For example, you can direct 10% of traffic to the canary deployment and 90% of traffic to the current deployment.
Test the new version: Validate and test the new version of your application by directing a small amount of traffic to the canary deployment. You can use Kubernetes tools like Istio or Flagger to manage traffic shifting between the current and canary environments.
Monitor the performance: Monitor the performance of the canary deployment to ensure that it is performing as expected. You can use Kubernetes tools like Prometheus or Grafana to monitor metrics like response time, error rate, and resource utilization.
Increase the traffic to the canary deployment: If the canary deployment is performing well, gradually increase the percentage of traffic directed to the canary deployment. For example, you can increase the traffic split to 20% canary and 80% current.
Rollback if necessary: If there are any issues with the canary deployment, you can easily rollback to the previous version by reducing the traffic split to 0% canary and 100% current.
Promote the canary deployment to production: Once the canary deployment has been thoroughly tested and validated, you can promote it to production by increasing the traffic split to 100% canary and 0% current.

In summary, the Canary Deployment Strategy is a safe and efficient way to update your Kubernetes deployment, allowing you to release a new version of your application to a small group of users and gradually increase the percentage of users that receive the new version, ensuring minimal impact on your overall user base.

Here’s an example of the Canary Deployment Strategy in Kubernetes:

Create a deployment for the current environment:

kubectl create deployment my-app --image=my-app:v1 --replicas=3

2. Create a service for the current environment:

kubectl expose deployment my-app --port=80 --type=LoadBalancer --name=my-app-current

3. Create a deployment for the canary environment:

kubectl create deployment my-app-canary --image=my-app:v2 --replicas=1

4. Create a service for the canary environment:

kubectl expose deployment my-app-canary --port=80 --type=LoadBalancer --name=my-app-canary

5. Define a traffic split between the current and canary environments:

cat <<EOF | kubectl apply -f -
apiVersion: networking.istio.io/v1alpha3
kind: VirtualService
metadata:
  name: my-app
spec:
  hosts:
  - my-app.com
  http:
  - route:
    - destination:
        host: my-app-current
        subset: v1
      weight: 90
    - destination:
        host: my-app-canary
        subset: v2
      weight: 10
EOF

Test the new version: At this point, only 10% of traffic is directed to the canary environment. You can now test this version of your application by directing a small amount of traffic to the my-app-canary service.
Monitor the performance: Monitor the performance of the canary deployment using Kubernetes tools like Prometheus or Grafana to ensure that it is performing as expected.
Increase the traffic to the canary deployment: Gradually increase the percentage of traffic directed to the canary deployment by modifying the traffic split definition in step 5. For example, you can increase the weight of the canary deployment to 50% to direct half of the traffic to the new version.
Rollback if necessary: If there are any issues with the canary deployment, you can easily rollback to the previous version by reducing the weight of the canary deployment in the traffic split definition.
Promote the canary deployment to production: Once the canary deployment has been thoroughly tested and validated, you can promote it to production by increasing the weight of the canary deployment to 100%.

4. A/B Testing Deployment Strategy

The A/B Testing Deployment Strategy is a Kubernetes deployment strategy that allows you to release two different versions of your application to different groups of users and compare their performance against each other. This approach helps to gather insights about how users interact with your application and which version performs better.

Here are the basic steps involved in an A/B Testing Deployment Strategy:

Create two versions of your application: Create two different versions of your application, each with its own container image or other configuration settings.
Create two deployments for the A/B environment: Create two Kubernetes deployments, one for each version of your application, using different names or label selectors.
Define a traffic split between the two deployments: Use Kubernetes tools like Istio or Flagger to define a traffic split between the two deployments. For example, you can direct 50% of traffic to each deployment.
Test the two versions: Validate and test the two versions of your application by directing traffic to both deployments. You can use Kubernetes tools like Istio or Flagger to manage traffic shifting between the two environments.
Monitor the performance: Monitor the performance of both deployments to determine which version performs better. You can use Kubernetes tools like Prometheus or Grafana to monitor metrics like response time, error rate, and resource utilization.
Analyze the results: Analyze the results of the A/B test to determine which version of your application performs better based on your desired metrics.
Promote the winning version: Once you have determined which version of your application performs better, you can promote it to production by increasing the traffic split to 100% for the winning deployment.

In summary, the A/B Testing Deployment Strategy is an effective way to compare two different versions of your application and determine which version performs better, allowing you to make data-driven decisions about which version to promote to production.

An example of the A/B Testing Deployment Strategy in Kubernetes.

Create two versions of your application: Create two different versions of your application, each with its own container image or other configuration settings. For example, you can create version A and version B of your application.
Create two deployments for the A/B environment: Create two Kubernetes deployments, one for each version of your application, using different names or label selectors. For example, you can create two deployments called my-app-a and my-app-b.

kubectl create deployment my-app-a --image=my-app:v1 --replicas=3
kubectl create deployment my-app-b --image=my-app:v2 --replicas=3

Define a traffic split between the two deployments: Use Kubernetes tools like Istio or Flagger to define a traffic split between the two deployments. For example, you can direct 50% of traffic to each deployment.

cat <<EOF | kubectl apply -f -
apiVersion: networking.istio.io/v1alpha3
kind: VirtualService
metadata:
  name: my-app
spec:
  hosts:
  - my-app.com
  http:
  - route:
    - destination:
        host: my-app-a
        subset: v1
      weight: 50
    - destination:
        host: my-app-b
        subset: v2
      weight: 50
EOF

Test the two versions: Validate and test the two versions of your application by directing traffic to both deployments. You can use Kubernetes tools like Istio or Flagger to manage traffic shifting between the two environments.
Monitor the performance: Monitor the performance of both deployments to determine which version performs better. You can use Kubernetes tools like Prometheus or Grafana to monitor metrics like response time, error rate, and resource utilization.
Analyze the results: Analyze the results of the A/B test to determine which version of your application performs better based on your desired metrics.
Promote the winning version: Once you have determined which version of your application performs better, you can promote it to production by increasing the traffic split to 100% for the winning deployment.

This example demonstrates how the A/B Testing Deployment Strategy can be used in Kubernetes to compare two different versions of your application and determine which version performs better based on real-world usage.

5. Blue/Green with Red-Black Deployment Strategy

The Blue/Green with Red-Black Deployment Strategy is a combination of two popular deployment strategies: Blue/Green and Red-Black. This approach leverages the benefits of both strategies to minimize downtime and risks associated with deploying new versions of your application.

Here are the basic steps involved in a Blue/Green with Red-Black Deployment Strategy:

Create two identical environments: Create two identical environments for your application, referred to as Blue and Green. Each environment should have its own set of resources, such as nodes, pods, and services.
Deploy the current version to Blue: Deploy the current version of your application to the Blue environment, using Kubernetes tools like kubectl or a CI/CD pipeline.
Validate the Blue environment: Validate and test the Blue environment to ensure that the deployment is successful and that the application is functioning as expected.
Deploy the new version to Green: Deploy the new version of your application to the Green environment, using Kubernetes tools like kubectl or a CI/CD pipeline.
Validate the Green environment: Validate and test the Green environment to ensure that the deployment is successful and that the new version of the application is functioning as expected.
Switch traffic to Green: Use Kubernetes tools like Istio or Flagger to switch traffic from the Blue environment to the Green environment. This can be done gradually, to minimize the impact on users, or all at once.
Monitor the performance of Green: Monitor the performance of the Green environment to ensure that the new version of the application is functioning correctly.
Roll back if necessary: If any issues arise with the new version of the application, roll back to the previous version by switching traffic back to the Blue environment.
Deploy the next version to Blue: Once the new version of the application is stable, deploy the next version of the application to the Blue environment and repeat the process.

In summary, the Blue/Green with Red-Black Deployment Strategy provides a way to deploy new versions of your application with minimal downtime and risk, by leveraging the benefits of both Blue/Green and Red-Black deployment strategies.

Here is an example of the Blue/Green with Red-Black Deployment Strategy in Kubernetes:

Create two identical environments: Create two identical environments for your application, called Blue and Green. Each environment should have its own set of resources, such as nodes, pods, and services.
Deploy the current version to Blue: Deploy the current version of your application to the Blue environment, using Kubernetes tools like kubectl or a CI/CD pipeline.

kubectl apply -f my-app-blue.yaml

Validate the Blue environment: Validate and test the Blue environment to ensure that the deployment is successful and that the application is functioning as expected.
Deploy the new version to Green: Deploy the new version of your application to the Green environment, using Kubernetes tools like kubectl or a CI/CD pipeline.

kubectl apply -f my-app-green.yaml

Validate the Green environment: Validate and test the Green environment to ensure that the deployment is successful and that the new version of the application is functioning as expected.
Use Kubernetes tools to switch traffic to Green: Use Kubernetes tools like Istio or Flagger to switch traffic from the Blue environment to the Green environment. This can be done gradually, to minimize the impact on users, or all at once.

kubectl apply -f my-app-traffic.yaml

Monitor the performance of Green: Monitor the performance of the Green environment to ensure that the new version of the application is functioning correctly.
Roll back if necessary: If any issues arise with the new version of the application, roll back to the previous version by switching traffic back to the Blue environment.
Deploy the next version to Blue: Once the new version of the application is stable, deploy the next version of the application to the Blue environment and repeat the process.

This example demonstrates how the Blue/Green with Red-Black Deployment Strategy can be used in Kubernetes to minimize downtime and risk when deploying new versions of your application.

6. Conclusion

In conclusion, Kubernetes Deployment Strategies are an important aspect of modern software development and operations. With Kubernetes, deploying and managing containerized applications has become significantly easier and more efficient, allowing for faster and more frequent updates.

Different Deployment Strategies can be used in Kubernetes, including Rolling, Blue/Green, Canary, and A/B Testing, among others. Each strategy has its own strengths and weaknesses and can be selected based on the specific needs of your application and organization.

By leveraging Kubernetes Deployment Strategies, organizations can reduce the downtime and risk associated with deploying new versions of their applications, while increasing reliability, scalability, and efficiency. Furthermore, Kubernetes provides a flexible and scalable platform for managing containerized workloads, making it an essential tool for modern DevOps teams.