What is Containerization?
Containerization can be defined as bundling or packaging together software codes with all their necessary components similar to frameworks, libraries, and other dependencies into a single virtual package.
Containers are an alternative to coding on a single platform or operating system, which makes relocating an application difficult because the code may not be compatible with the new environment. The new environment becomes prone to bugs, errors and glitches resulting in the dissipation of time and money. As there is a need to resolve these bugs and errors, the development cycle is delayed for deployment. Packaging up an application not only helps us to move across different platforms and infrastructures but it also provides flexibility in the movement of the code to different dynamic platforms and hosting environments. That is because it has everything it needs to run successfully, so in the end, there are no discrepancies left.
Benefits
Containerization is characterized by the light-weight or portable nature of containers, which can share the host machine’s operating system kernel, obviating the need for a separate operating system for each container and allowing the application to run as before with the same infrastructure, including cloud and virtual machines (VM).
- Lightweight
- Portable
- Easy to operate and setup
- No need for a separate operating system
- Easy environment setup
- Allowing applications to run the same
Containers vs. virtual machines
A virtual machine (VM) is a virtual environment that works as a virtual computer system with its own CPU, network, interface, memory, and storage, created on a physical hardware system (located off- or on-premises).
Containerization and virtualization have one thing in common: they both allow for complete isolation of applications, allowing them to function in numerous environments without issues or mistakes. The key distinctions are in terms of size and portability.
VM is the larger of the two, specifically measured in gigabytes and containing its own Operating System, which allows it to perform multiple resource-intensive functions at once. Abundant availability of the resources in VMs allow them to abstract, duplicate, split, and surpass entire servers, desktops, databases, networks, and operating systems.
Containers are substantially smaller than virtual machines (VMs), usually measured in megabytes, and their packing is limited to a programme and its execution environment. The lightweight nature of the containers and their shared operating system (OS) makes them very easy to move across multiple environments.
On the other hand, where VMs work well with traditional, monolithic IT architecture, containers were made to be compatible with newer and emerging technology like CI/CD, DevOps, and clouds.
Which one to use?
The small, moveable and lightweight nature of containers makes them doable to be rapt simply across blank metal systems similarly as personal, hybrid, public, and multi-cloud environments. Containers need fewer IT resources to deploy, run, and manage the overall environment. Containers spin up in a fraction of a second. Containers will host more containers than VMs since their order of magnitude is less.
Achieving Scalability through Containerization
Monolithic design is taken into account to be a conventional method of building applications. A client-side software, a server-side application, and information are usually included in such a response. It’s unified, and all of the functions are handled and supplied from a single location.
Normally, monolithic applications have one massive codebase and lack modularity. If developers need to update or modification one thing, they need to access an identical codebase. Hence, they create changes within the whole stack promptly.
A heritage application (legacy app) could be a software system program that’s noncurrent or obsolete. Though a heritage app still works, it should be unstable as a result of compatibility problems with current operative systems (OSes), browsers, and data technology (IT) infrastructures. Most enterprises use heritage applications and systems that still serve important business wants. Typically, the challenge is to stay the heritage application running, whereas changing it to newer, a lot of economical code that creates use of current technology and programming languages.
Obsolete systems can’t be maintained and utilized forever; for some purpose, an associate degree enterprise can upgrade hardware, writing language, OS, or the appliance in question. Modernization and migration involve refactoring, repurposing, or consolidating inheritance computer code programming to line with current business wants. The goal of an inheritance application modernization project is to form new business prices from existing applications.
A microservices design could be a form of application design wherever the appliance is developed as a group of services. It provides the framework to develop, deploy, and maintain microservices design diagrams and services severally. Typically, microservices square measure accustomed speed up application development. Microservices architectures engineered exploitation Java square measure common, particularly Spring Boot ones. It’s conjointly common to check microservices versus service-oriented design. each has an identical objective, that is to interrupt up monolithic applications into smaller parts, however, they need completely different approaches.
Scalability
Container technology offers a better degree of application measurability than ancient monolithic applications. By reconfiguring bequest design to a microservice design, developers will add and alter resources by adjusting the containers among the cluster. This offers the flexibleness to form new updates instantly while not probably disrupting the full application or inflicting the time period of alternative containers.
A monolithic pack application has most of its practicality at intervals one instrumentation, with internal layers or libraries, and scales out by biological research the instrumentation on multiple servers/VMs. However, this monolithic pattern may conflict with the instrumentation principle “an instrumentation do you factor, and will it in one process”, however, can be ok for a few cases. The drawback of this approach becomes evident if the appliance grows, requiring it to scale. If the complete application will scale, it is not very a haul. However, in most cases, simply a couple of components of the appliance area unit the choke points that need scaling, whereas alternative elements area unit used less.
A container-based design works well for homeless designed applications. After all, resiliency and quantifiability square measure enforced by restarts of failing containers or initiate identical containers in parallel to perform the applying functions at a better load. This works best once no state should be managed within the application logic. However, most inheritance applications need state management and information determination. Kubernetes will coordinate states and information determination by providing a mechanism to trace storage volumes and maintain hostnames when a restart of the instrumentation by victimization the StatefulSet resource. this permits containerization of the components of the inheritance app that manages states like databases.
A great way to introduce how containerized microservices work is to describe the other strategies for running microservices (and explain what’s wrong with them):
- Each microservice runs on its own physical server with its own package instance: This approach keeps the microservices isolated from one another, however, it’s wasteful. Considering that fashionable servers have the process power to handle multiple package instances, a separate physical server for every microservice isn’t necessary.
- Multiple microservices run on one package instance on an identical server: this is often risky as a result it doesn’t keep the microservices autonomous from one another. there’s an associate degree accrued probability of failures caused by conflicting application parts and library versions. a tangle with one microservice will cause failure cascades that interrupt the operation of others.
- Multiple microservices run on totally different virtual machines (VM) on identical servers: This provides a singular execution surrounding for every microservice to run autonomously. However, a VM replicates the package instance, therefore you’ll pay to license a separate OS for every VM. Also, running a wholly new OS is an associate degree unessential burden on system resources.
Also Read: Evolution Of DevOps And Its Future
