Introduction to Container Design Patterns
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, and these containers reside inside the pod. But there are some situations where containerized applications need additional features to enhance their efficiency. Using the various container design patterns, we can improve an application’s efficiency. These designing patterns are useful while talking about applications’ architecture and preventing application architecture changes during any testing process.
Cloud applications can keep businesses moving forward, even in this pandemic, people have been able to shop, connect with friends and, of course, work from home.
The deployment process of an application includes several steps. The whole process has been simplified with the containerization approach. Containers are helpful to move an application for deployment in different environments quickly. 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 complete an application more stable by following a defined architecture.
What are the types of Container Design Patterns for Kubernetes?
In general, the container design patterns are useful for a specific purpose in Kubernetes. It is unnecessary to combine the containers in a pod, but it is essential to understand which pattern is suitable for a particular problem.
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. If we want to add some dependencies in a container as per our requirement, we can use that container’s base image.
This pattern is used to extend the behavior of a container. In this pattern, the sidecar container is attached to a parent application container. 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.
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. In simple words, the application container can invoke the ambassador container, which acts as a service discovery layer. The ambassador container contains all external services configuration 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.
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.
Container Storage Interface is an initiative to combine the storage interface of Container Orchestrator Systems that combined with storage vendors like Ceph, Net App.
Leader Election Pattern
Sometimes, it is necessary to replicate the running component so that the load can be shared among the components’ repeated instances. The distributed systems that have 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, when a service starts, a node is elected as the leader, and when service goes down, the rest of the nodes elect a leader based on specific criteria to keep the cluster healthy. Some libraries are there limited to a particular language to handle such type of election. An election leader container is used to link 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.
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. To speed up the process, we can implement the work queue pattern and transform it into smaller chunks. The code which does the processing work can be packed into a container, and then we can spin up containers at the same time to complete the processing work.
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.
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.
The use of these patterns depends upon the problem. A particular way doesn’t need to be suitable for a problem. Sometimes we need to implement more than one pattern. Each design pattern has its purpose and solves a particular kind of problem. We need to keep in mind the architecture of implementation and selecting a suitable pattern. Once a pattern is implemented, it becomes easy to define the architecture or add some changes.