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Deployment Automation

Kubernetes Container Design Patterns | Quick Guide

Gursimran Singh | 07 Jul 2022

Container Design Pattern

Container Design Pattern - Optimize Efficiency

In the emerging era of technology, the cloud plays a crucial role. Application deployment becomes easy with the use of containers. Kubernetes is playing a vital role in the deployment and scaling of applications. As we know, applications run in the containerized form on Kubernetes Architecture, and these containers reside inside the pod. However, containerized applications need additional features to enhance their efficiency in some situations. We can improve an application’s efficiency using the various container design patterns. These design patterns are helpful when discussing applications' architecture and preventing application architecture changes during any testing process.

The deployment process of an application includes several steps. The whole process has been simplified with the containerisation approach. Containers are helpful for moving an application for deployment quickly in different environments. The container design patterns are introduced to make an application more utilizable and a container reusable. These patterns help solve application deployment's common problems and make an application more stable by following a defined architecture.

Helm simplifies application deployment and management on Kubernetes by providing a templating system. Users can create reusable application packages called charts, which contain all the necessary resources and configurations for deployment. Introduction of Helm Package Manager for Kubernetes.

What are the types of Container Design Patterns for Kubernetes?

In general, the container design patterns in Kubernetes are helpful for a specific purpose. Combining the containers in a pod is unnecessary, but it is essential to understand which pattern is suitable for a particular problem.

1. Single-Container Pattern

The single-container pattern means deploying an application by putting it inside a container. This is a simple pattern from where the journey of a container starts. In this case, the container should contain only one responsibility. The containers can be used for various things. During runtime, the container's behavior can be changed by using the docker commands. We can use that container's base image if we want to add some dependencies in a container as per our requirement.

2. Sidecar Pattern

This pattern is used to extend the behavior of a container. The sidecar container is attached to a parent application container in this pattern. The Sidecar Pattern provides supporting features to the main application. The lifecycle of the sidecar is the same as the parent application. The application container performs the primary task, and the sidecar extends its functionality by performing the secondary tasks. It describes how to enhance a primary container's functionality without changing it. This pattern is suitable when the difference between the primary and secondary studies is clearly defined.

3. Ambassador Pattern

This pattern is suitable for running additional services with our main container. Ambassador Pattern's primary goal is to simplify the main container’s access to other services. Simply put, the application container can invoke the ambassador container, which acts as a service discovery layer. The ambassador container contains all external service configurations with the main application using the localhost service. This container connects to the service to keep the connection open and reconnect when something unexpected happens.

4. Adapter Pattern

The adapter container pattern is suitable when we want to keep the communication between containers consistent. It generally transforms the primary container's output into the output that fits our applications’ standards. For example, an adaptor container can expose our application's monitoring interface even though it does not implement it in a standard way. In Adapter Pattern, we can easily replace the existing container without affecting the application container because of just the configuration changes. This container's main benefit is that the adapter pattern enables a container to reuse a common system problem.

5. Leader Election Pattern

Sometimes, it is necessary to replicate the running component to share the load among the components' repeated instances. The distributed systems with replicated processes contain a common problem of electing a leader. The application may need to select a leader from the replicas' running set. If the election fails, then another group must move in to take its place. It means that when a service starts, a node is elected as the leader, and when the service goes down, the rest of the nodes elect a leader based on specific criteria to keep the cluster healthy. Some libraries are limited to a particular language to handle such type of election. An election leader container links the leader election library with our application. Leader Election Pattern's main objective is that once we build the leader election container, it can be reused across our application.

6. Work Queue Pattern

The work queue pattern focuses on splitting up a big task into smaller tasks to reduce running time. In simple terms, this pattern is used to solve the producer-consumer problem. This pattern allows handling the processing code packaged as a container, arbitrary data, and building a work queue system. For example, if a user requests to transform one million records, this will take a lot of time. We can implement the work queue pattern and transform it into smaller chunks to speed up the process. The code that does the processing work can be packed into a container, and then we can spin up containers simultaneously to complete the processing work.

7. Scatter/Gather Pattern

The work queue pattern splits a big task into smaller ones. The scatter/gather pattern does a similar kind of work. The difference is that the work queue pattern doesn't focus on a response, but the container responds to the user in the scatter/gather pattern. An external client sends a request to a root container (parent node), which further scatters the request among the group of containers in parallel to complete a particular task. All the containers in the group perform the assigned task. The root container gets the partial data from each container as a response. The root container then merges the gathered data to send it as a single response for the client's query.

8. Init Container Pattern

Every container includes a configuration concerning the task for which it is made. We deploy applications on Kubernetes in the form of a pod. Sometimes we need to replace the default configuration of an application with our custom configuration files during the deployment process. For such a problem, we can use init containers. Init containers execute a defined job before the initialization of the primary container. During the deployment process, init containers execute before the primary container. After their successful completion, the primary container executes. These containers become an integral part of the primary container.


Build resilient and reliable Platform Engineering and IDP with Kubernetes Services and streamline their application deployment processes, improve scalability, and achieve greater stability.

A Holistic Approach to Kubernetes Container Design

The selection of these patterns depends on the specific problem at hand. It is important to note that there is no one-size-fits-all approach in implementing these patterns. In some cases, multiple patterns may be necessary to address different aspects of the problem. Each design pattern serves a unique purpose and is tailored to solve a specific type of problem. Thorough consideration of the implementation architecture and careful selection of the most suitable pattern are vital. Once a design pattern is successfully implemented, it becomes easier to define the overall architecture and make necessary adjustments.