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Kubernetes' Impact on Developmentby@asadfaizi
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Kubernetes' Impact on Development

by Asad FaiziMarch 23rd, 2022
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Kubernetes is the reason containerization has garnered a mass acceptance among enterprises. Cloud giants with deep pockets have already extensively adopted K8s, with AWS, Google Cloud, and Azure, all with individual services: EKS, AKS, and GKE, respectively. DevOps teams need to work on automated software delivery pipelines to get the best out of containers. Deployment of mission-critical applications may take an eternity with the complexities of the distributed system. It actually takes more than subscribing to these services to make KuberNETes ready for prime time.

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Chant the word “Kubernetes” a couple of times while passing a lobby of developers, operators, IT managers, or even tech-savvy marketers and CEOs, and you will have their unwarranted attention. Repeat Kubernetes in your startup pitch a number of times, and investors will drive in hordes to throw their millions on you. While the latter might not be true (sorry VCs), the hype around Kubernetes is real, and it doesn’t seem to fade away. As if Kubernetes is a new technology, it is five years old and is only growing in popularity.


Developers take containerization for granted while deploying applications and give little credit to Kubernetes. That doesn’t mean that Kubernetes brings little to the table for developers. Kubernetes is the reason containerization has garnered a mass acceptance among enterprises. Whether you like it or not, Kubernetes makes your life as a developer easy. This is especially relevant if your organization insists on following DevOps practices and makes you work on automated software delivery pipelines.

Kubernetes and DevOps: a match made in heaven?

For DevOps teams, kubernetes makes developers more productive because, in conjunction with containers, it makes them more efficient and frees them from the burden of rewriting software in order to move it to another cloud provider. Operators will appreciate how dramatically it reduces the amount of time they spend deploying applications and scaling.


Even if you have reached a conclusion that Kubernetes is just not for you, there is little you can do to avoid it. Kubernetes saves companies millions of dollars every year by allowing them to do more with less IT manpower and efficiently utilize the infrastructure that powers their applications.

These companies are not startups with limited funding or resources. In fact, the startups backing K8s have already exited. The cloud giants with deep pockets and massive resource pools have already extensively adopted K8s, with AWS, Google Cloud, and Azure, all with individual services: EKS, AKS, and GKE, respectively.

The underlying complexities of Kubernetes at large scale

While these services (GKE, AKS, EKS) have eliminated some of the complexities of the distributed system Kubernetes brings, it actually takes more than subscribing to these services to make Kubernetes ready for prime time and power mission-critical enterprise applications.


Large enterprises invested in container-based applications struggle to realize the true value of Kubernetes and container technology due to day-2 management challenges. Those are a handful of things to manage. To name a few, you have to take care of packaging & artifacts, cloud computing, configuration management, provisioning, orchestration, service discovery, process management, logging, monitoring, observability, visualization, security, error tracking, and some other random stuff related to Kubernetes cluster management.


Typically, when we begin to experiment with Kubernetes, we deploy Kubernetes on a set of servers. This is only a test deployment, and we realize this basic deployment is not practical in production for multifaceted applications because it doesn’t include components that are critical to ascertain the smooth operations of enterprise-grade Kubernetes-based applications. While deploying to a local Kubernetes environment is a straightforward process that doesn’t take over a few hours, deployment of mission-critical Kubernetes-based applications may take an eternity.


A comprehensive Kubernetes infrastructure requires the right DNS, load balancers, Ingress, and Kubernetes role-based access control or RBAC, alongside a number of auxiliary components, which makes the deployment process a little too complicated for the average-Joe developer. Once Kubernetes is deployed, comes the need for monitoring and everything mentioned in associated operations playbooks to fix problems whenever they arise—for example, when capacity runs, ensuring HA, timely backups, and much more. Lastly, the cycle repeats itself, every time a new version of Kubernetes comes along courtesy of its community. Then it would be best if you upgraded your production clusters without running into the risk of application downtime.

The management challenges of Kubernetes day-2 operations

At a high level, Kubernetes regulates how a group of containers (Pods) that make up a feature in the application is planned, deployed, and scaled up and down. Also, how they make use of the network and the remaining onboard storage.


Once your Kubernetes cluster is deployed, IT Operations teams need to figure out how these pods are tied to the applications in question via request routing; how they ensure the integrity of these pods, HA, zero-downtime environment upgrades, etc. As the cluster grows in complexity, IT is required to empower developers to be embarked in seconds, facilitate monitoring, troubleshooting, and ascertain smooth operations.


The major management challenges associated with Day 2 operations of Kubernetes when you go beyond the first install are many and that causes delays.


  • Configuring networking and persistent storage at a large scale
  • Staying up to date with the rapidly moving community releases of Kubernetes
  • Updating applications and the Kubernetes version to security patches, maintenance fixes, and feature updates
  • Setting up and maintaining monitoring and logging
  • Disaster recovery for the Kubernetes master(s)


Managed Kubernetes services essentially deliver an enterprise-grade Kubernetes, without the operational burden. These could be services provided solely by the public cloud providers like AWS or Google Cloud, or solutions that allow organizations to run Kubernetes on their own data centers or on hybrid environments.


Even with managed services, you need to be mindful that different types of solutions would use “Managed” or “Kubernetes-as-a-Service” to describe very different management experience levels. Some would only provide you an easy, self-service way to deploy a K8s cluster while others would handle a few of the ongoing operations for managing that cluster. Yet none offer you a fully-managed Kubernetes service that takes over most of the management task from you, with guarantees on service level agreement, and without asking for any management overhead or Kubernetes expertise from the customer.

CloudPlex makes Kubernetes manageable

CloudPlex can help managers and development teams to make the transition to Kubernetes smooth. When it comes to CI tools such as Jenkins, CircleCI, Bitbucket, etc., you just have to integrate webhook in your CI pipeline—a copy-paste operation.


Whether you need to bootstrap your own cluster with full management capabilities or use one of the managed services like AKS, EKS, and GKE, CloudPlex gives you the freedom and the flexibility to accomplish your technical choices effortlessly.


CloudPlex automatically configures storage class, persistent volume, persistent volume claim, and their associations. CloudPlex only requires basic information about the size of the volume and the identity of the container to associate. Moreover, CloudPlex provides a uniform interface for all public clouds.


Kubernetes manageable


If Kubernetes default RBAC setting is giving you nightmares, with CloudPlex, you only need to provide information about resources and permissions. CloudPlex automatically creates and configures the Service Accounts, Roles, and Role Bindings.


Kubernetes


If autoscaling is emerging as a challenge, CloudPlex sets up the Metrics Server for each public cloud provider. In the case of pod autoscaling, developers provide minimum and maximum values for replicas and resource quotas. In the case of node autoscaling, developers select a CloudPlex provided node template.


Kubernetes


The best part is getting started on CloudPlex for free. Signup Now


Asad Faizi

Founder CEO

CloudPlex.io, Inc

[email protected]