Application Containerization
Published: 2023-03-06 09:35:58

Containerization is a method of packaging software applications and their dependencies into a single, self-contained unit known as a container. Each container is isolated from the host system and from other containers, and provides a consistent and reliable environment for running the application. Containers can be easily moved between different environments, such as development, testing, and production, without requiring any changes to the application code. Containerization provides many benefits, such as improved portability, scalability, and efficiency, and has become increasingly popular in recent years as a way to modernize and streamline application development and deployment.

Containerization is needed for several reasons. Here are a few of the most important:

1. Portability: One of the main benefits of containerization is that it provides a consistent and portable environment for running applications. This means that containers can be easily moved between different environments, such as development, testing, and production, without requiring any changes to the application code. This makes it easier to deploy and manage applications across different infrastructure environments, such as on-premise data centers, public clouds, or hybrid environments.

2. Scalability: Containers are designed to be lightweight and easy to replicate, which makes them ideal for scaling applications horizontally. By running multiple instances of the same container, businesses can easily scale up or down the resources allocated to an application in response to changing demand.

3. Efficiency: Containers are isolated from the host system and from other containers, which helps to improve efficiency and reduce the risk of conflicts or interference between different applications. Additionally, containers can be spun up or down quickly, which helps to reduce the time required to deploy or update applications.

4. Consistency: Containerization helps to ensure that applications are run in a consistent and reliable environment, which helps to improve stability and reduce the risk of errors or failures. This consistency can be particularly important in complex or distributed systems, where different applications or components need to work together seamlessly.

Overall, containerization is needed to provide a more efficient, scalable, and portable approach to application development and deployment, which can help businesses to improve their agility and respond more quickly to changing market demands.

## More landed with real examples

Let's say you're developing a Java web application using the Spring Framework, and you need to deploy it to multiple environments, such as development, testing, and production. Traditionally, you might package your application into a WAR file, along with its dependencies, and deploy it to a web server running on each environment. However, this approach can be time-consuming, error-prone, and difficult to manage, particularly as the application grows in complexity.

Instead, you could use containerization to package your application and its dependencies into a Docker container. This container would provide a consistent and reliable environment for running your application, regardless of the underlying infrastructure. You could then easily move the container between different environments, such as by pushing it to a container registry and pulling it down onto a different server.

For example, you could use the following Dockerfile to create a container for your Java web application:

```
Copy code
FROM openjdk:11-jre-slim
COPY myapp.jar /app/
CMD ["java", "-jar", "/app/myapp.jar"]
```
This Dockerfile specifies that the container should use the openjdk:11-jre-slim image as its base, and then copy the myapp.jar file into the container's /app directory. It also specifies that the container should run the command "java -jar /app/myapp.jar" when started.

You could then build the container using the following command:

docker build -t myapp:latest .

This command would create a new Docker image with the tag "myapp:latest", based on the Dockerfile in the current directory.

Once you have built the container, you could then run it using the following command:

```
docker run -p 8080:8080 myapp:latest .
```

This command would start a new container based on the "myapp:latest" image, and map port 8080 on the host to port 8080 in the container. You could then access your Java web application by navigating to http://localhost:8080 in a web browser.

Overall, containerization provides a more efficient, scalable, and portable approach to application development and deployment, which can help you to streamline your development workflow and improve your agility.

## More example to see it adavantages
In the previous example, we saw how containerization can be applied in a Java-based application, and how it can provide improved portability, scalability, and efficiency. We also saw how the application can be deployed to OpenShift, a popular container application platform, and how it can be exposed as a service to enable external traffic. In this section, we will explore how auto-scaling can be used to automatically adjust the number of replicas of the application based on the current demand, and how this feature can provide several benefits, such as improved resource utilization, reduced costs, and improved application performance.

here's an example of how you can deploy a Java-based containerized application to OpenShift, expose the service, and make it auto-scale:

### Deploying the application to OpenShift:
To deploy your containerized Java web application to OpenShift, you can use the OpenShift command line interface (CLI) to create a new deployment from your Docker image. You can use the following command to create a new deployment:

```
oc new-app myapp:latest
```
This command will create a new deployment in OpenShift based on your Docker image with the tag "myapp:latest". OpenShift will automatically detect that this is a Java-based application and will use the appropriate Java runtime environment to run it.

### Exposing the service:
Once your application is deployed to OpenShift, you can expose it as a service by creating a new OpenShift service. You can use the following command to create a new service:

```
oc expose deployment myapp --port=8080
```
This command will create a new OpenShift service called "myapp" that exposes port 8080. This service will allow external traffic to access your application running inside the OpenShift cluster.

### Auto-scaling the application:
To enable auto-scaling for your application, you can use OpenShift's horizontal pod autoscaler (HPA) feature. This feature allows you to automatically scale the number of replicas of your application based on the current demand.

You can use the following command to create a new HPA for your application:

```
oc autoscale deployment myapp --cpu-percent=50 --min=1 --max=10
```
This command will create a new HPA for your "myapp" deployment that will scale up the number of replicas when the CPU utilization reaches 50% and scale down when the CPU utilization drops below that threshold. The HPA will ensure that at least one replica is always running, but will not scale beyond a maximum of 10 replicas.

Auto-scaling provides several benefits, such as improved resource utilization, reduced costs, and improved application performance. By automatically scaling the number of replicas based on the current demand, you can ensure that your application is always running at optimal capacity, without wasting resources or incurring unnecessary costs. Additionally, auto-scaling can help you to maintain consistent application performance, even during periods of high traffic or demand.

## Don't stop there
In the previous section, we explored how containerization can be applied in a Java-based application, and how it can provide several benefits, such as improved portability, scalability, and efficiency. We also saw how the application can be deployed to OpenShift, a popular container application platform, and how auto-scaling can be used to automatically adjust the number of replicas based on the current demand. In this section, we will explore how auto-healing can be used to automatically recover from failures or errors in the application, and how this feature can provide several benefits, such as improved application availability, reduced downtime, and increased reliability. We will use the same Java-based application running on OpenShift as an example to demonstrate the auto-healing concept.

Auto-healing is a feature that enables the automatic recovery of an application in the event of a failure or error. When an application fails or experiences an error, auto-healing can automatically restart the failed components or deploy a new instance of the application to restore normal operations.

To enable auto-healing for your application running on OpenShift, you can use the Kubernetes readiness probe feature. A readiness probe is a mechanism for checking whether a container is ready to receive traffic. If the container fails the readiness check, it will be marked as "unready", and Kubernetes will automatically stop sending traffic to the container. This triggers a Kubernetes "liveness" probe, which checks whether the container is still alive. If the container fails the liveness probe, Kubernetes will automatically restart the container, which effectively auto-heals the application.

You can use the following YAML configuration to enable the readiness probe for your Java-based application running on OpenShift:

```
apiVersion: v1
kind: Pod
metadata:
  name: myapp
spec:
  containers:
  - name: myapp
    image: myapp:latest
    ports:
    - containerPort: 8080
    readinessProbe:
      httpGet:
        path: /healthz
        port: 8080
```
In this configuration, we have added a readiness probe to the container by specifying an HTTP GET request to the path "/healthz" on port 8080. This probe will check whether the container is ready to receive traffic, and will mark the container as "unready" if it fails. This will trigger the liveness probe, which will check whether the container is still alive. If the container fails the liveness probe, Kubernetes will automatically restart the container, which effectively auto-heals the application.

Overall, auto-healing provides several benefits, such as improved application availability, reduced downtime, and increased reliability. By automatically recovering from failures or errors, auto-healing can help to ensure that your application is always running smoothly and can provide a better user experience.

## Compare to traditional method
Traditionally, virtual machines (VMs) have been the preferred method for deploying and managing applications in a cloud environment. A VM is essentially a software emulation of a physical machine, which runs a guest operating system and provides a virtualized environment for running applications. While VMs have been widely used for many years, they have several drawbacks, such as slower startup times, higher resource usage, and increased complexity.

When it comes to autoscaling and auto-healing, VMs can achieve similar functionality, but with some differences. In a VM environment, autoscaling can be achieved using a combination of load balancers, auto-scaling groups, and dynamic resource allocation. When the demand for an application increases, the load balancer can distribute the traffic across multiple VM instances, while the auto-scaling group can automatically launch new VM instances to handle the additional load. Dynamic resource allocation can be used to allocate additional resources, such as CPU or memory, to the VM instances to handle the increased load.

Auto-healing in a VM environment can be achieved using similar techniques, such as monitoring tools and process managers. When an application fails or experiences an error, the monitoring tool can detect the failure and trigger a process manager to restart the failed components or deploy a new instance of the application.

Overall, while VMs can achieve similar functionality to containerization in terms of autoscaling and auto-healing, they often require more resources, are slower to start up, and are more complex to manage. Containerization, on the other hand, provides a more lightweight and efficient way to achieve these features, while also providing other benefits such as improved portability and faster deployment times.

## Conclusion
In conclusion, containerization has become a popular method for deploying and managing applications in a cloud environment, due to its many benefits, such as improved portability, scalability, and efficiency. Containerization is made possible by operating system-level virtualization, which uses namespaces to provide process-level isolation while sharing the same kernel. Containers can be easily moved between different environments without requiring any changes to the application code, making it easier to deploy and manage applications at scale. Containerization has also enabled new features, such as autoscaling and auto-healing, which help to ensure that applications are always running smoothly and providing a good user experience. Compared to traditional methods like virtual machines, containerization provides a more lightweight and efficient way to deploy and manage applications, while also reducing costs and increasing productivity. As the technology continues to evolve and improve, containerization is expected to become even more prevalent in the cloud computing landscape.