Container Cons: The complexities associated with Containers
In the fast and ever-progressing world of application development, Containers have become inevitable and are exploding into the scene, especially in the area of cloud computing. Container-based virtualization is a disruptive technology that is being adopted at an incredible pace by businesses across the globe. Although having been in use for years, its popularity has increased lately, leading large enterprises like AWS, IBM and HP rapidly shifting towards Containers. Many organizations are even considering containers as a replacement of VMs.
A Container, or otherwise known as operating-system-level virtualization, may be defined as a standard unit of software that packages up code and all its dependencies so that the application runs quickly and reliably from one computing environment to another. Containers isolate a software from its environment and ensure that it works uniformly despite differences. Available for both Linux and Windows-based applications, containerized software always runs the same, irrespective of the infrastructure, enabling it to function reliably when moved from one computing environment to another, be it a developer’s laptop or a test environment, from a staging environment into production or from a physical machine in a data center to a virtual machine in a cloud environment.
Another major advantage of Containers is flexibility. Containers facilitate applications to divide into distributed objects and offer more advantages around workload management providing the ability to create fault-tolerant systems effectively and easily.
But it’s not all rosy about Containers and they have their own perils. Containers increase app flexibility, but at the same time add complexity in a number of ways. To handle and migrate successfully to containers, the associated complexities need to be handled first. Complexities may arise in terms of security, orchestration, data storage and monitoring.
One of the main disadvantages of container-based virtualization compared to traditional virtual machines is security. Compared to a traditional stack, Containers need multi-level security as they have multiple layers. Having said that, in addition to the security of the containerized app, the container registry, the Docker daemon and the host operating system need to be secured as well.
Another complexity associated with Containers is orchestration. In the case of virtual machines such as VMware, orchestration can be done with a single orchestrator that comes with the virtualization solution such as VMware Orchestrator in case of VMware. But with Containers, one has to select from a range of orchestration tools like Swarm, Mesos, Kubernetes etc.
With virtual machines, data storage is pretty simple and straight. But in the case of Containers, it becomes much more complex. For persistent container data storage, the data have to be moved out of the container to the host or elsewhere with a persistent file system. The reason behind data loss is the way Containers are designed. It makes all of the data inside a container disappear forever when the container shuts down unless it is saved somewhere else. There are ways to save data in Containers, but this still remains a challenge.
Finally, in taming the complexity of Containers, it is crucial to monitor them for performance and security issues. A variety of basic monitoring tools and external monitoring services and analytics can help address this challenge. Considering the complex nature of the cloud environment, in-depth monitoring of security issues is important.
Nevertheless, the pros of Containers outweigh its cons, and at the end of the day, the decision as to whether Containers should be tried or not solely depends on cloud requirements. At an individual level, for beginners aspiring to create a small cloud, Containers could be a better option. But for a lone developer handling a substantial project, it is better to think twice and thoroughly know the nitty-gritty of Containers before taking a plunge.
Same applies to large scale enterprise projects as well. Containers may sound a lucrative and impressive option and work great for the enterprise, but they entail downsides that need to be meticulously covered. Being an industry leader in containerization, Sogeti, can successfully bridge this gap.
Digital transformation is inevitable for enterprises to survive and succeed in this competitive and fast-evolving technological era. Cloud, Big Data, Mobility, Blockchain, and AI are some of the core technology pillars for digital transformation and to leverage these next-gen technologies, enterprises need to radically shift their technological foundation to next level infrastructures such as container platforms. According to Gartner (Gartner, Feb – 2019), by 2022, more than 75% of global organizations will be running containerized applications in production, as compared to a mere 30% running currently. But this rapid adoption of containerized applications demands technological maturity and operational know-how. This is precisely where Sogeti can pitch in to enable enterprises scale up to the new IT infrastructure and be ready to embrace containerization. As the technological partner to enterprises, Sogeti can assess and evaluate if they have the right kind of skill sets to move ahead, given the steep learning curve required to migrate to container services like Docker, Kubernetes, and Apache Mesos. Migration to containers essentially requires enterprises to be more cloud-native. This is where Sogeti’s expertise again comes into play in helping customers become cloud-native and develop a hybrid cloud strategy facilitating migration to containerization.
The objective of discussing the complexities associated with Containers is not to deter individuals and enterprises from using it since in most cases the benefits of Containers outweigh the drawbacks. The whole idea is to be familiar with the complexities before taking a decision to migrate to Containers.
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