Organizations continually strive to empower developers, data analysts, and data scientists to drive the quick creation and deployment of new applications and services. To that end, they require rapid adoption of upcoming self-serving, cloud-native architecture and infrastructure. Furthermore, the preferred environment for all this development and deployment is often open source, using Linux and tools such as Docker and Kubernetes. Consequently, containers form the fundamental and foundational building blocks of modern-day IT development.
Benefits of Containers in IT Development
The primary advantage that containers have, especially over a virtual machine (VM), is that containers share the machine’s OS kernel. So, while VMs need an entire OS instance for operating each application, containers can just share their host machine’s OS for their operations — making them relatively smaller in size, less resource-intensive, and quick to spin up. They also offer better support for cloud-native applications and are faster to set up when compared to VMs.
Here are some other advantages of container architectures:
- The lightweight, and portable nature of containers, coupled with their platform independence, means that once their software is written, you do not need to re-configure it for deployment on other computing machines or cloud applications.
- They bring a level of abstraction to the OS. While operating VMs, efficient utilization of computational power and memory of the physical machine was always a concern of the developers. Containers now allow them to improve it a step further. Since containers enable microservice architectures, developers can deploy components of an application. This capability allows for a granular scaling up of an application. These capabilities and the inherent nature of containers make them the perfect fit for modern-day IT development.
- Containers also provide application-level isolation as well as faster communication with hardware. This capability boosts efficiency and reduces the amount of time taken to deliver the application. A combination of all these factors encourages microarchitecture and design.
Disadvantages of Containers
Just as the saying goes, “One man’s food is another man’s poison,” similarly, the defining feature of containerization can be its most significant drawback. Containerization’s ability to share the host’s OS kernel exposes the physical machine to various security threats. Its lack of isolation from the host OS means that security threats have access to the entire system. One possible solution to this issue is to create containers inside a VM. While containers can utilize the VM’s OS for their operation, any security threats cannot penetrate further beyond the virtual machine.
Other obstacles containers pose include:
- While a virtual machine provides OS flexibility, containers limit the use to operating on the same OS that the host machine utilizes. So, a VM running on a Linux-based OS can be set up on a host machine that operates on a Windows OS. This is not possible with containerization.
- Since containers are small and less resource-intensive, it is possible to set up and operate hundreds or even more containers on a single server. But monitoring what’s happening in each of these hundreds of containers is another hindrance to accepting container-based architecture. This issue can be mitigated by augmenting containers with various proprietary or open-source tools created to address operational challenges.
- Containerization, as compared to VMs, is a relatively new technology, and not many IT admins or consultants are familiar with its operations or have experience using it. And, while IT professionals are a quick study, there still is an associated learning curve with any new technology.
- Although this technology has come out of its infancy, it’s far from mature, which makes containerization for supporting application development, in the long run, a tricky affair.
How IT Pros are Adopting Containers
Container architecture has become exceedingly popular with application developers because containers enable them to create and deploy applications using agile software development methodologies along with CI/CD. These capabilities allow for ease of creation and quick deployment along with rapid and efficient rollbacks.
Containers have also occupied a prominent space for themselves, especially in cloud-based environments. Many organizations are considering replacing their VMs with container architecture. These containers would be used as general-purpose computational platforms for their applications and workloads. But all these are still very broad-scope use cases. Let’s attempt to narrow the key use cases of containers where they are most relevant.
Applications constructed using microservice architecture comprise many loosely coupled and independently deployable smaller services. The small, portable nature of containers makes them the perfect match for microservice architectures.
Since many teams have been working on a common foundation for building, shipping, and operating software, embracing DevOps and using a combination of microservices as architecture and containers as a platform is an easy transition.
Hybrid and multi-cloud functionality
Containers are platform-independent and easy to migrate. They form the underpinning architecture for hybrid and multi-cloud scenarios. Since containers can work across laptops, computational devices, on-prem, and in cloud networks, organizations can operate across multiple public clouds or use a combination of their own data centers. They are also used for modernizing applications and their migration to the cloud.
While containers are excellent tools for bundling and running applications in production environments, IT professionals need to ensure that containers are not only running these apps, but also that there is zero downtime. If a container fails, another must be ready and quick in replacing the downed one. This shortcoming of containers is handled by an extensible platform called Kubernetes (K8). It was created by Google and later open-sourced in 2014 to manage containerized workloads and services.
Kubernetes is taking the telecom industry by storm. As telcos expand their infrastructure and use more computation-intensive applications, they’re opting for K8s and incorporating the technology as the backbone of their telecom services, such as 5G infrastructure. K8s is leading the cloud-native orchestration platform, and when telcos adopt such a technology, you can rest assured that the technology is here for a long time.
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Here is what to expect as more IT infrastructures incorporate containers.
- As an increasing amount of organizations are adopting containerized architecture, enterprises are shifting their focus beyond application development and testing. This focus has now shifted to Kubernetes (Container orchestration). Organizations are vying for more granular control, increased monitorability, and enhanced security.
- As containerized development is slowly becoming the norm, container architecture is penetrating farther into various areas of IT, such as storage, networking, and security. One potential trend is the use of containers and K8s in network edge. This trend is still in its early stages, but it may potentially allow for remote deployment and management of software across various locations and devices.
- Some enterprises are planning on using containers and K8s to deploy stateful applications such as machine learning apps. Some early adopters of these technologies are beginning to look beyond container orchestration and are mapping out broader Agile and DevOps transformations possibilities.
- With VMware leading the trend of on-premises adoption, Kubernetes isn’t far behind. As VMware introduces more products and partnerships, it will further drive the on-prem adoption and bring K8s to mainstream audiences.
- While the K8s is having its “moment,” serverless development is predicted to make a comeback. Serverless enables developers to utilize cloud-native infrastructure for simplifying the deployment, monitoring, and operation of their applications. While K8s can scale globally, doing so is still a very complex process.