The benefits of using Kubernetes (K8s) at an enterprise level are numerous. K8s is portable, extensible, scalable and reliable. When it comes time for your enterprise to deploy its K8s clusters, there are several deployment frameworks and tools to choose from. But which solution is right for your enterprise? Read on as we break down deployment solutions into categories and demonstrate how each framework and tool can enable you to operate, manage and deploy your K8s clusters in different ways.
Every major public cloud provider has its own K8s implementation service, including:
- Amazon Web Services EKS
- Azure AKS
- Google GKE
Each cloud-managed solution can deploy and manage your K8s clusters. They are especially beneficial if you consistently use these providers. It’s relatively easy to start with each of them, and they are fully integrated into each corresponding cloud.
However, each cloud is specific to each provider. Therefore, if you have a multi-cloud or hybrid environment, it will become much more difficult, perhaps even impossible in certain situations, to use cloud-managed solutions to deploy your K8s cluster.
Development and Testing Frameworks
There may be times when you need to test your K8s cluster, but you aren’t ready to fully deploy it just yet. Two options for development solutions are kind and minikube. These lightweight solutions allow you to quickly start playing with K8s, develop your cluster and test it on a local machine. To demonstrate the benefits of development and testing frameworks, we’ll explain how kind operates.
Kind is a simple, binary utility that allows you to run a K8s cluster in your docker environment. Kind is for development only and is especially beneficial to use for automated tests or research work. You can download the kind executable and immediately begin creating a cluster. It’s important to note that in some aspects, kind clusters will differ from a physical or virtual hardware K8s cluster. However, most aspects of development and testing will be the same as a cluster you deploy through other sources.
Frameworks like kind and minikube are effective ways to practice, plan and test K8s implementation before actually deploying your cluster.
When it comes to running an enterprise that uses a multi-cloud or hybrid environment, it’s best to use a deployment solution that supports multiple platforms. Some options for this include Kublr or Rancher. To demonstrate the advantages of multi-platform solutions, we’ll explain how Kublr operates.
- Kublr is a UI, API, multi-cloud, production-ready container management platform. Kublr has the ability to support each of the previously mentioned major public cloud providers on one platform. It’s a full platform that includes centralized logging and monitoring. Kublr can be deployed as a docker container, or deployed as a full platform in any cloud or data center.
Other multi-platform solutions may operate similarly, but focus on different goals pertaining to K8s. For example, Kublr is a K8s solution focused more heavily on security, compliance, infrastructure and operations.
Choosing the Best Deployment Solution
The examples in this article are a glimpse of the options you can choose from to deploy your K8s clusters. But how do you know which of these frameworks is best to choose? You should pick and choose each tool according to your business requirements and business goals.
If you only utilize AWS, for example, then choosing to deploy with AWS EKS is a good option. But if you have a large enterprise, with multiple platforms and clouds, consider deploying and managing with a multi-platform solution like Kublr. Kublr offers turnkey K8s and container management that allows you to deploy K8s across different environments without sacrificing operational capabilities.
Learn more about Kublr today!