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Containerization rises as the wave of the future
while virtual machines stumble under inefficiencies

As data center technology hurtles forward, it has brought with it a divergence in data hosting strategies, forcing companies to choose between traditional virtualization and containerization. Driven in part by investment from industry leaders like Google, Microsoft, and IBM, containers have quickly expanded across the data landscape. As the immediate and explosive growth of Docker has demonstrated, containerization brings with it a host of advantages that are rendering virtual machines obsolete.


Containers vs. Virtual Machines: What’s the difference?

The performance advantage of containerization lies in its efficient architecture from the hardware level upward, the same point at which virtualization encounters its limits. A virtual machine is a software environment that essentially mimics a hardware-based environment. This occurs at two levels. First, virtual machines rely on a software component called a hypervisor between the host operating system and the guest operating systems that ultimately hosts applications and data requests. The hypervisor provides abstraction between hardware and virtual machines. It is capable of executing several virtual machines simultaneously. Second, load balancers are inserted in front of the host to manage the workload of a server and direct traffic where it can be executed with a minimum delay.

Containers work without a hypervisor, and are able to interact directly with both the host operating system and applications. They share the host OS kernel as well as any binaries or libraries needed for applications to function. No guest operating system is required to manage the applications connected to each container. Containers are typically read-only, with each possessing a unique mount for writing.


So, why switch to containerization? – Performance

There are a host of benefits associated with containerization, beginning with size and resource allocation. The first is the small footprint of a container. They’re usually only megabytes in size, so they’re space-efficient and take very little time to start. By comparison, virtual machines take up more space and usually require a few minutes to start running. They require a virtual copy of all hardware needed by the operating system, which quickly eats RAM and consumes valuable processing power.

Containers use only the resources they need to function at any given time, and don’t place resource holds like virtual machines do. VMs require a permanent block of system resources in order to start up. Virtual machines tie up bandwidth, memory, and processing power even when they’re not in use. Containerized systems auto-allocate system resources and distribute them optimally across applications.

Containers also provide a gateway for applications to access system hardware resources, where virtual machines cannot. Adding graphics cards and other hardware components allows a container to maximize its processing power and increase efficiency.

And, because you don’t need the guest operating system likevirtual machines, containers save resources, reduce redundancy, and maximize output without the demands of a guest OS that manages each application individually.

The transitory nature of containers allows you to maintain your data center workflow without interruptions in service. An orchestration system creates multiple copies of each container, which can be removed and replaced in the case of failure, with virtually no lag in service.

Ultimately, this means that a containerized system can run two to three times as many applications on a single physical server as virtual machines can.


Container Scalability

Virtual machines are scaled in essentially the same way as any bare metal system: a Web or database server monitors incoming program requests and directs traffic among multiple hosts.

Scaling in containers is very different. Among its barebones services and functions is a Web server, which works as a load balancer. Coupled with an orchestration system like REDHOT Enterprise Cloudware, containerized systems are able to determine when demand is high enough to increase the quantity of containers. This orchestration system can automatically replicate container images and remove them from the system when necessary. This means that containers are especially well-equipped to handle large or spiky workloads, as they can scale up to handle as much traffic as necessary.

Containers work very well with developer tools like application program interfaces (APIs) and command-line interfaces (CLIs). This makes containers far easier to integrate into existing systems and development workflows, reducing complexity as applications are added to the container system.


Container Security

Despite the overwhelming evidence of the superiority of container systems, there is concern among companies and IT professionals that containers are not as secure as other methods like virtual machines. Security presents a different set of challenges for both systems, and while securing containers is a totally unique process, it is effective and can be easily achieved.

The first step to securing a container system is to create the file system as read-only, forcing container processes to write to their specific file system alone. Since data isn’t stored in the container itself, but rather in a shared volume that is accessed by multiple containers at once, developers securing a containerized system can install a high degree of automation and build a security profile that matches the application needs of the container system in question.

The main challenge in securing container systems lies in the ephemeral nature of containers, which turn over much more rapidly than virtual machines, up to nine times faster. Since this high rate of churn creates a more fluid environment, developers and security teams should create toolkits that can monitor an application lifecycle and switch gears as new containers are created and destroyed.


Last Call: Containers vs. Virtual Machines

Ultimately, the decision to move to a container-based data center is dependent on the specific needs of your company. If your data center deals with high or unpredictable traffic loads requiring vast resources and maintenance, containerization will create a more efficient data environment that can handle the demands of a large system. Their built-in flexibility and scalability means that containers are vastly preferable to virtual machines, allowing you to expand the resources available to your servers without constant redistributing of RAM and processing power. All signs point toward containerization as the wave of the future, leaving behind the frustrating inefficiency and maintenance demands of virtual machines for a more automated, fully scalable system.