What’s application containerization?

<span id="hs_cos_wrapper_name" class="hs_cos_wrapper hs_cos_wrapper_meta_field hs_cos_wrapper_type_text" style="" data-hs-cos-general-type="meta_field" data-hs-cos-type="text" >What’s application containerization?</span>

Apr 09

Apr 09

Big Data


If you work in DevOps or software development, you’re likely familiar with application containerization. It not only saves you time, but it also saves data center administrators money due to its portability, efficiency and reduced hosting costs. Learn more about application containerization and how it complements the data center.

What’s is it?

Application containers are self-contained execution environments. They have their own isolated CPU, memory, block I/O and network resources that share the kernel of the host operating system. Application containerization lets developers package an application with its needed parts, like libraries and other dependences, and ship it out as one package.

Why application containerization is important

Portability, speed, efficiency and reduced hosting costs are the primary drivers for application containerization. “DevOps and software development are two areas that rely on containerization,” says Tommy Mac, Ingram Micro senior technology consultant. “Because they focus on applying lean and agile approaches to operations and software development work, speed and efficiency complement their efforts.”

The other key advantage of application containerization is saving application developers time. They know that their applications will run on any other Linux machine and won’t have to worry about configuring custom settings that any other Linux machine might have that differs from the machine writing and testing the code.

Why it’s important in the data center

In the data center, containers are more streamlined and lightweight, compared to virtual machines, so users can run more containers as virtual machines on the same hardware. “One of the benefits of containers is that they're portable and are scalable,” says Mac. “They can run them on top of virtual machines, bare-metal servers, on-premises or in the cloud. And containers can easily scale, saving time to market without any recoding for them to work.”

Topics: Data Center, Cloud

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