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Package Your Applications in Containers

In the age of cloud computing and distributed systems, containerization has become a popular practice. Packaging an application together with its configuration files, libraries, and other dependencies provides an efficient and error-free way to move them across different environments.

Dubbed as “lightweight virtualization,” application containerization encapsulates the software and its dependencies into a single isolated box. This makes it easier to deploy several distributed applications at once across machines of different configurations. In short, you can code once and deploy many times over.

Docker is one of the most popular container formats that we use to deliver applications. It is open-source and supported on Google Cloud, AWS, and Azure platforms.

Three Reasons to Containerize Applications

Speed Up

Speed up App Development and Deployment

Containerization empowers your development and IT teams to roll out frequent updates and new functionalities to end users. Bugs arising out of differences in environments (development/staging/production) are reduced when applications are placed in containers. These containers can be configured and deployed easily further simplifying the development cycle.

Migrate to the Cloud

Migrate to the Cloud

Portability is an immensely useful trait of containers. Abstracting applications away from the operating system and infrastructure allows applications to be moved from one environment to another without code changes. Hence, enterprises use containers to accelerate cloud migrations or distribute an application across multiple cloud environments.

Transition to Microservices

Transition to Microservices

Microservices architecture (MSA) is an architecture pattern that has grown popular with cloud computing. MSA speeds up development, allowing components to be developed and scaled independent of each other. Containers work best with such service-oriented architecture, with each container packaging an individual service that can be updated without disrupting the entire application.

Implementing DevOps with Containers

Containers are powerful tools in an organization’s DevOps transformation. You will realize many of the build and deployment operations become more efficient with containerization.

When applications are deployed in containers, development, testing, and production environments remain consistent and the application moves faster along the delivery chain. Also, when each microservice is hosted in a container, your team can make changes to the individual service without disrupting the rest of the application.

You can have containers integrated into the build and deployment environments to streamline your DevOps workflow. Docker files may be created based on the environment requirement and images pushed to the container registry. We can even integrate the build image creation into your DevOps automation. Deployment can be to a container orchestration system such as Kubernetes or directly using Docker.

Container Orchestration

Provisioning, deploying, and managing hundreds of containers in large, dynamic environments can be efficiently tackled using automated tools. You can use the container orchestration tool to manage containers throughout their lifecycle, monitoring and scaling them as required. Out of the various orchestration platforms available, we mostly use Kubernetes, the most popular one.

To deploy containerized applications, we need to create a configuration file with details such as the state of the container and where to pull the Docker images from. The tool executes the file and deploys on an appropriate host based on predefined parameters. On placing the container on the host, the orchestration tool will follow the specifications that have been laid out to manage the container’s lifecycle.

The Kubernetes platform can be configured to schedule different containers to utilize your compute resources efficiently. It can also manage service discovery and communication between the different microservices. We can even plug in tools like Prometheus into your orchestration platform for capabilities like logging and analytics.

Managed Container Services

Major cloud providers such as Google, AWS, and Azure offer managed container service to simplify container deployments. While Google Kubernetes Engine set the stage for managed container services, Amazon has multiple offerings including Elastic Container Service (ECS) and Elastic Kubernetes Service (EKS). We work with organizations to identify the best fit and set up container orchestration to reduce the operational overhead in deploying and operating Kubernetes clusters.

Securing Containers

Within container platforms, your applications can be secure. The inherent isolation provides for faster and safer software patching mechanisms. Containers also follow the principle of least privilege, limiting access to required resources alone. Another advantage of containers is the wrapper security you can add to the application without modifying the source code. We leverage these and other security best practices to secure containers for the enterprise.

Some of the measures we take to implement container security include:

  • Choose Docker images with fewer OS libraries and tools.
  • Create a generic user with the least privileges to run the application.
  • Use multi-stage builds to avoid leaking sensitive information into Docker images.
  • Ensure all sensitive information is passed as env variables, and not hardcoded in the image.
  • Secure the Docker registry.

Success Story

Our client wanted a learning platform built and migrated in the alpha phase to their servers on the cloud or on-premises. The solution had to support multiple deployments in a day and to move seamlessly between clouds, it had to be cloud-agnostic.

We built the solution with microservices architecture and used separate Docker containers for each service. To host and manage the Docker containers, we used Kubernetes. Adopting the twelve-factor methodology ensured stateless containers that allowed for multiple deployments and rollbacks with minimum worry. Custom CD pipelines were creed to automatically deploy the containers to the Kubernetes cluster based on code changes. In short, container technology allowed us to deliver a cloud-agnostic solution that could be easily migrated to the client’s data center.

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