Utilizing Kubernetes to Deploy, Scale, and Operate Containers

Drew Bixby
Read Time: 2 minutes


The introduction of containers in developing software was a step forward in virtualization. They are isolated components that enable bundling of dependencies, binary code, libraries, and configuration files but abstracting away the operating system. This configuration allows for software to run in a variety of environments. Hence, a developer can package the different microservices into containers and deploy them over a cluster of hosts. In doing so, there are some benefits:

  • Reduced overhead: Containers do not include operating system images, therefore requiring minimal resources as compared to traditional software environments.
  • Consistency and Portability: Containers can run in different environments due to ease in allocating resources to processes
  • Cost-effectiveness: Breaking down software into containers reduces the complexity of software, thus cutting down on workforce and time required to develop large programs.
  • Easier Debugging and Maintenance: These entities reduce software size complexity and help make modifications fast.


As the size of software increases, so does the number of containers created and overall complexity in operating on these many entities. This challenge gives rise to the need to automate the management of containerization software. Kubernetes mitigates the problem of deploying, scaling, and operating on application containers across collections of servers, thereby offering a tool to container orchestration. The platform is popular for managing cloud software, making it attractive to many organizations seeking to unlock the many benefits offered by cloud services.

Engineers working in Google built Kubernetes upon over a decade of experience, and later open sourced in 2014. Google Borg is an earlier container management tool that Google used, and Kubernetes borrows basic concepts from it. Though commonly used together with Docker, the container orchestration tool can also be used together with any container facility that upholds the Open Container Initiative (OCI) standards.

The Kubernetes architecture is made up of clusters, each consisting of:

  • master node/s
  • worker nodes
  • distributed key-value store

The master nodes are responsible for managing the cluster by making overall decisions. Each component of the master node performs an administrative job. These are:

  1. API server: is the end-point that facilitates communication.
  2. Controller managers: runs loops that regulate the cluster, aimed at achieving the desired state as contained in the API server.
  3. Scheduler: balances workload among worker nodes.

The worker nodes are tasked with executing the workload as directed by the master node. This node constitutes the following major parts:

  1. Pods: several containers that are a logical unit. They do not all need to run on a single machine as the constituent containers can be spread over several nodes.
  2. Kubelet: communicates with the master node and runs processes within pods to guarantee good internal health.
  3. Kube-proxy: balances load and implements service abstraction.


The large size of modern software applications is a reason for the growing popularity of Kubernetes as a means of managing distributed software. The platform comes with a dashboard where operations are initiated over the familiar graphical user interface. Little knowledge is required to make use of the panel.

Compatibility between Kubernetes and existing cloud technologies like Azure and AWS among many others serves to promote its uptake among companies adopting cloud services. Anti-affinity rules placed within the platform also achieve improved availability of services, by countering downtime using backup measures.

Companies demand technological solutions that are flexible in response to the evolving nature of the business environments. A product requires support for upgrading to adapt to changes not only within but also without the said organization. Otherwise, the facility will cause major bottlenecks at the end of its lifetime and eventually lead to losses at entropy. Kubernetes makes an allowance for rolling updates using Stateful Sets without downtime.

At DoubleHorn, we are excited about the opportunities Kubernetes presents for businesses and love helping companies migrate to the cloud. If your company is interested in migrating to the cloud contact us for a complimentary consultation.