Top 6 Kubernetes Deployment Strategies

In the dynamic world of Kubernetes, deploying applications efficiently and reliably is crucial for maintaining user service availability. Whether you're running mission-critical applications or developing new features, choosing the right deployment strategy is essential for maintaining service reliability while delivering updates to your users. In this blog, we will explore top Kubernetes Deployment strategies, that will help you to roll out new features and versions in a safer and controlled way.

In the previous blogs, we covered what Kubernetes Deployment is. Before moving ahead, let's clarify what "Deployment" means in different Kubernetes contexts:

A Kubernetes Deployment is also a Kubernetes object, with its own YAML configurations which allows you to define how deployment of applications should occur and what should be deployed.
Kubernetes deployment is also a process of releasing newer versions of applications.

What is Kubernetes Deployment Strategy

A Kubernetes deployment strategy is the approach used to deploy or roll out new versions of applications while managing service availability. These strategies help teams control how application updates are delivered to end users, where each strategy offers different benefits for testing, user feedback, and maintaining service uptime.

The Default Kubernetes Deployment object comes with two fundamental deployment strategies as part of its Deployment:

Recreate: A basic deployment pattern that replaces all existing instances at once
Rolling Update: A gradual replacement of instances that maintains service availability

Advanced Deployment Strategies (Progressive Delivery): For more sophisticated deployment needs, Kubernetes supports several advanced strategies:

Blue/Green: Running two identical environments with different versions
Canary: Exposing a subset of users to the newer version of the application
A/B Testing: Testing different versions simultaneously with specific user groups
Shadow Deployment: Testing new versions with production traffic without affecting users

Top Kubernetes Deployment Strategy

Let’s take a look at each Kubernetes Deployment strategy and its pros and cons.

Recreate

A Recreate deployment strategy is supported by the Kubernetes Deployment object by default, this deployment strategy follows the way of it’s all or nothing. The Recreate deployment strategy terminates the current pods and replaces them with the pods with newer configurations i.e. configurations of newer versions.

This deployment strategy is not recommended for production environments, as there is downtime involved while rolling new versions of applications. The recreate deployment strategy is suitable for development environments or when applications have scheduled maintenance time.

[Fig. 1] Recreate Deployment Strategy

Pros/Cons of Recreate Deployment

Pros	Cons
It is straightforward and easy to implement, as it simply terminates all old instances before creating new ones.	Service becomes unavailable during the deployment as all instances are terminated before new ones start.
No need to manage multiple versions running simultaneously or handle complex routing between versions.	If the new version fails, you'll need to redeploy the old version, leading to additional downtime.
This deployment strategy comes in-built with the Kubernetes Deployment object, so there is no need to manage multiple tools.	Managing database connections, in-flight transactions, and session state becomes complex and risks data inconsistency or loss during the transition.

Rolling

Rolling deployment is the default strategy used by Kubernetes Deployment object that slowly replaces pods running the older application version with pods containing the new version configurations. This strategy ensures zero service downtime by maintaining both versions simultaneously during the deployment process. The Rolling strategy approach is particularly reliable as deployment performs readiness checks on the new pods to verify they are healthy and capable of handling traffic, before destroying old pods. If issues arise during deployment, Kubernetes makes it straightforward to roll back to the previous version, making this strategy both safe and practical for production environments.

[Fig. 2] Rolling Deployment Strategy

Pros/Cons of Rolling Deployment

Pros	Cons
Service remains available during updates as instances are replaced gradually	Rolling updates take longer to complete since instances are updated one by one.
No need for duplicate infrastructure	Limited control over traffic distribution - Less precise control over which users get the new version compared to other strategies
Ability to slowly release changes and monitor impact, making it easier to catch issues early	May face resource constraint issues during rollout if proper scaling thresholds aren't set
This deployment strategy comes in-built with the Kubernetes Deployment object.	Lack of control over how quickly or slowly the deployment will roll out.

Blue/Green deployment

The blue/green deployment strategy, also known as the Red/Black strategy is an advanced deployment strategy that allows organizations to roll out frequent updates while maintaining the high availability of services for users. In the blue/green deployment strategy, two similar production environments are used to deploy the newer versions of applications. Where the blue version runs the existing version of applications, and the green environment has the new version of the application. From both environments (blue/green) only one is live and receives production traffic. Once the newer version is completely deployed, tested, and ready to handle the traffic the production traffic is en route to the newer version. With the blue/green deployment strategy even if things go wrong the traffic can be switched to the older version. Once the newer version is stable the previous version can be taken down freeing up the resources. Read more about Blue/Green deployments.

[Fig. 3] Blue Green Deployment Strategy

Pros/Cons of Blue/Green Deployment

Pros	Cons
Zero-downtime deployment - Users experience no service interruption as traffic is switched instantaneously	Resource intensive - Requires maintaining two complete production environments, doubling infrastructure costs
Instant rollback capability - If issues are detected, you can immediately switch back to the stable environment	Higher operational complexity - Need to maintain and manage two complete environments, including monitoring, logging, and configuration
Predictable deployment - The entire environment is updated at once, making the deployment process more consistent and reliable	Blue/Green deployment is not available as a default strategy in Kubernetes deployment objects, requiring additional tools or custom implementation
Full testing capability - The new version can be thoroughly tested in isolation before receiving any production traffic	Blue/Green deployment strategy is not ideal for applications that have to deal with stateful workloads as it can be challenging to replicate data on both environments.

Canary deployment

The canary deployment strategy is a method that allows organizations to release newer versions of applications in a controlled way. In canary deployments, the newer versions are exposed to a fraction of traffic and gradually entire production traffic is shifted to newer versions. This deployment strategy is somewhat similar to the blue/green deployment but provides more control over the deployment of newer versions. In canary deployments, even if the deployment goes wrong it will affect a small subset of users and not the entire user base. To understand canary deployment better let’s take a look at an example: if you have 100 pods running older versions of applications, in canary deployment you will be rolling the newer version at 10 pods initially and gradually increasing the number of pods. So even if newer versions have some issues users with 10 pods will be affected, remaining 90 pods will be healthy.

The canary deployment strategy does not come with the default Kubernetes Deployment object, to execute canary deployments there is a need for customization and some open-source tools. To know how you can execute Canary Deployments refer to the following blogs:
Canary Deployment with Flagger and Istio
How to Execute Canary Deployments Using NGINX Ingress
Understanding the Basics of a Canary Deployment Strategy

[Fig. 4] Canary Deployment Strategy

Pros/Cons of Canary Deployment

Pros	Cons
Fine-grained control - Precise control over traffic distribution and the ability to gradually increase exposure	Increased operational overhead, as canary deployments require managing multiple versions of the application simultaneously.
Real user feedback - Gather actual production metrics and user feedback before full deployment	Canary releases often require time to gather meaningful insights before promoting or rolling back.
Risk mitigation - Allows testing new versions with a small subset of real traffic before full rollout	Canary deployment is not available as a default strategy in Kubernetes deployment objects, requiring additional tools or custom implementation
Zero-downtime deployment - Service remains fully available throughout the deployment process	Infrastructure cost shoots up, as there is a need to maintain similar replicas of applications.

A/B Testing

A/B deployment is a deployment strategy that enables multiple versions of an application to be run simultaneously to compare their performance and user experience. Unlike other deployment patterns, A/B testing focuses on gathering data by routing different user segments to specific versions. This approach allows teams to validate new features with real users while maintaining the ability to revert to the stable version if needed quickly. A/B deployments are particularly valuable for data-driven decision-making, as teams can collect metrics about user behaviour, feature adoption, and performance before deciding whether to roll out changes to the entire user base.

Shadow Deployments

Shadow deployment is a testing strategy that allows teams to test new versions of an application under real production conditions without affecting end users. In this approach, live production traffic is duplicated and sent to both the current production version and the new version simultaneously. Still, only the response from the production version is returned to users. This enables teams to monitor how the new version would perform under actual production loads and user patterns while eliminating any risk to the user experience. The shadow deployment provides valuable insights into potential performance issues, bugs, or behavioral differences between versions before going live

When to Choose Which Deployment Strategy

Deployment Strategy	Reasons to Use
Recreate	When downtime is acceptable or during development. When an application requires complete version change at once. Fast and Consistent.
Rolling	Execute deployments with minimal downtime. Need built-in rollback capabilities.
Blue/Green Deployment	For critical applications requiring zero-downtime updates. Easy to switch between versions.
Canary Deployment	When you want to test new features with limited user exposure. For gradual feature introduction in production. Need user feedback before full rollout.
A/B Testing	Making data-driven decisions about features.
Shadow Deployments	When testing performance under real production load.

Kubernetes Deployments with Devtron

Devtron is an open-source Kubernetes management platform designed to simplify application deployment and management across any Kubernetes environment. It streamlines the process of updating application configurations and triggering deployments for newer versions. With Devtron, you can effortlessly choose your preferred deployment strategy, whether it’s Recreate, Rolling Updates, Blue/Green, or Canary deployment.

[Fig. 5] Kubernetes Deployment with Devtron

Conclusion

Choosing the right Kubernetes deployment strategy is crucial for successful application delivery. From simple Recreate deployments to sophisticated Canary and Blue/Green approaches, each strategy serves different needs. While built-in strategies like Rolling updates offer a good starting point, advanced strategies provide more control and safety for production environments. The key is matching your deployment strategy to your application's requirements, considering factors like downtime tolerance, resource availability, and testing needs. With tools like Devtron, implementing these strategies becomes more manageable, helping teams deliver applications more effectively in their Kubernetes environments.