3 Ways Containerization Transforms your DevOps Workflow for the Better

DevOps & Kubernetes

This past decade has brought a surging wave of containerization platforms that has left DevOps communities overwhelmed, sometimes enraged. Some have mixed feelings towards efficient app management, deployment — you name it. Nevertheless, containerization service and microservice platforms have introduced a new generation of scalable environment management, workflowing, and a simplified ‘production → release’ process.

Although container services and architectures (e.g. Kubernetes, and Docker) have evolved into many forms of convenience, they all represent one mission: Packaging OS-leveled application properties for ease of portability and transfer across systems. 

It gets better: containers destress the DevOps workflow by placing all operations under a universal umbrella. In other words, a container built on a developer’s laptop vs a container build by CI/CD for production. 

Regardless, before developers dive into the deep-end of integrating container virtualization into their workflow, they should understand the inherent benefits of containerization.

1.  An All-In-One Portability for Application Development, Testing and Release

Although most DevOps operators are well aware of the benefit of consistent OS-leveled properties across all testing/development environments, they should know that the advantages extend beyond portability. Ultimately, when you program, test and deploy your application inside containers, the inherent environment structure does not change during different parts of the delivery chain.

The capacity of containers to deliver consistent package dependencies and environment conditions across all virtual environments makes it such a ‘hit’ for emerging DevOps communities. Specifically, developers and IT managers can streamline the app deployment and release process by strengthening collaboration between different teams via a single containerized environment.

In addition to the high-level transferability of container architectures, developers, testers, and administrators can instantly startup operating system resources, beginning exactly where they left off. Additionally, if operators and testers wish to edit the container, they can copy the containerization backbone and begin re-engineering for their use case.

More importantly, these containers can be hosted on cloud environments for effective A/B testing, deployment automation and final application release. For example, Kubernetes, a leading containerization-orchestration platform, can host and run containers on public cloud environment, enabling developers to jumpstart a multi-cloud strategy for app deployment and testing.

2. Support for Multiple Programming Frameworks and Languages

Remember the good old days of designing program-specific frameworks for your application deployment purpose, where you had to reconfigure environments for each and every programming language? Well, containerization rids you of those programmatic burdens!

Containers empower Engineering teams with the agility to switch easily between different programming frameworks or deployment platforms within seconds. Program developers and testers can run virtually any type of app inside a container, regardless of the language it is written in. All-in-all, this removes hours of toppling stress for collaborative teams managing multiple languages/frameworks.

Additionally, you can easily transition and move apps between different host systems. For example, if a developer wants to switch from Red Hat to Ubuntu, you can execute that process in seconds with container architectures, such as Docker. The result? A more streamlined and time-efficient app execution process. Containers can troubleshoot app execution on multiple Operating Systems (OS) by supporting scalable properties and a consistent environment across distro and non-distro systems.

For DevOps teams juggling several isolated programming languages, whether that is Python, Java or C, containers ensure that program executions run consistently and scalably across all language frameworks.

3. Universal Support from Container-Orchestration Services: Kubernetes 

When we discuss Container-Orchestration toolkits, Kubernetes steals the spotlight in supporting streamlined deployment processes, workload scalability and open-source operations. Kubernetes, an open-source container-orchestration system, automates app deployment, scaling and management across one or several containers.

Kubernetes supports critical levels of workload scalability by using resources efficiently and offering several useful features for scaling purposes. For example, Kubernetes uses an “auto-scaling” management tool, which allows you to change the number of running containers, based on CPU utilisation or other application-provided metrics.

In addition to auto-scaling the executions of multiple containers, Kubernetes allows you to manually scale container utilization via a command-line interface. This hierarchical level of control between auto-scaling and manual scaling protocols allows developers to adjust resource utilization, performance and efficiency of their app deployments in real-time.

Finally, Kubernetes establishes a set-in-stone high availability model, allowing IT operators to tackle the availability of both applications and infrastructure. For example, health checks and self-healing mechanisms are autonomously started, protected containerised apps against failures. This is done by checking the health of nodes and their associated containers. By continuously evaluating the health status of containerized apps, Kubernetes autoreplace unstable versions with a rollback version in a stable state.

Benefits for a  Business Professional

Business professionals can enjoy a hassle-free union between virtual machines and containerized applications. Containers provide the following conveniences for your business management workflow:

  • Agility: A new container can be deployed nearly 20 times faster than implementing and executing a new Virtual Machine (VM). The definitive startup time is measured in seconds rather than minutes. Once deployed, containers scale up and down in response to load. This means that businesses can deliver consumer-ready apps, products and services ‘on the fly’ with real-time programmatic updates and bug fixes.
  • Density and Storage: The vast majority of containers consume only a mere megabytes in size rather than gigabytes for a VM. This smaller footprint allows for nearly five times greater density levels than VMs, meaning you are able to run multiple isolated processes on a node. 
  • Cost Savings: Every traditional VM requires a hypervisor and an Operating System (OS), which may involve costly licensing and registration fees. Fortunately, containers run side by side, sharing the OS kernel of a single physical machine while maintaining isolated copies of specific dependencies and library versions they depend on. 

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