How Kubernetes improves IT’s operational efficiency
Containers are particularly useful for managing an increasing amount of applications. However, managing the containers themselves requires help. That’s where Kubernetes comes in. Scott Sanders explains why it might be beneficial to adopt Kubernetes and improve your IT operational efficiency.
As the shift to the cloud continues, enterprises are increasingly deploying Docker or other containers for their virtualization requirements. Instead of running applications on virtual machines, each with its own operating system, processor, memory and other resources, Docker allows you to “sandbox” individual stateless applications into unique containers; those containers then run on a single host that shares a single operating system and other resources with all of the containers that are present.
By sandboxing applications, developers are free to tune and deploy them while minimizing system resource consumption. That’s particularly helpful since users expect apps to be available on-demand, and developers are deploying new versions daily in some instances. And, given the typically large footprint required for building applications on virtual machines, containerization allows for significantly more density, allowing organizations to maximize efficiency of server real estate and bandwidth.
But keeping those containers organized and running smoothly can be tricky. That challenge is what spawned container management platforms like Kubernetes, a next gen orchestration system for standardizing how container applications are deployed.
Kubernetes improves efficiency
Google developed Kubernetes in 2014 to manage container sprawl; then made it available in 2015 to the open source community through its Cloud Native Computing Foundation―there’s now an active community contributing to its evolution. Patterned after web-scale methodology, Kubernetes enables developers to simplify and extend their virtualization capabilities, scaling containers as they’re needed according to rising and ebbing load demands. Kubernetes clusters can span private, public and hybrid cloud environments, such as the widely-adopted Microsoft Hyper-V and Azure platforms.
While Kubernetes leverages Docker’s Swarm clustering and scheduling tool, it adds some useful capabilities that make it more customizable and extensive, like self-healing replication using ongoing snapshots for recovering persistent data when something goes wrong. Kubernetes also addresses problems commonly arising from deploying large numbers of containers; for instance, it allocates scheduling units called pods that improve load balancing and ensure high availability. All of these efficiencies enable production applications to span multiple containers across multiple server hosts at the appropriate scale for serious business use.
Of course, no technology is without its challenges. Docker containerization is not always simple to deploy. It can’t auto-scale. There are many complex Linux dependencies and an awkward web interface set-up involving clusters, making it cumbersome for some users. Docker mandates a fairly sophisticated level of computer literacy (think command-line level); with the volume of apps, tools, systems, devices, APIs and widgets already in the data center, what administrator wants to add that complexity?
While offering a more intuitive, elegant management approach, Kubernetes still requires a familiarity with Docker and the principles of how it works. Up until now, virtualization has meant slicing-and-dicing hardware to build a virtualized server infrastructure. Docker and other similar containerization tools evolve that model to allow the building of stateless, workload-specific containers that keep persistent data away from the workload. That provides more efficiency and greater density to virtualized environments.
Although there are many benefits to that model, one must be comfortable with the required change in methodology, architectural approach and mindset. Any Docker container is sharing the kernel with every other container, there’s a challenge to understanding the related concepts. In simplifying the set-up, deployment and scaling of containers, Kubernetes makes it easier for enterprise IT to schedule and run containers on clusters of physical or virtual machines in production environments.
Organizations can often find cost savings and gain more compute and scaling efficiency by adopting it. Of course as the volume of clusters grows within an enterprise, the management, monitoring and security of even multiple Kubernetes deployments will also increase. Given the trending Kubernetes adoption curve, a unified approach to those requirements will be needed simply to keep up with the demand.
As happens with all technologies, virtualization is in the midst of its own evolutionary path, with containerization and Kubernetes offering options that administrators didn’t have before. There are new levels of efficiency that enterprises are just beginning to recognize and embrace. Given the upside potential, it may be time for your enterprise to evaluate how Kubernetes might improve your IT operations.