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Kubernetes

▾ 4 MINUTE READ — CLOSE

Although technically best described as a container orchestration engine, Kubernetes is rapidly becoming the infrastructure platform for cloud-native computing, an approach to using public or private clouds flexibly.
What Is Kubernetes?
Kubernetes, also known as K8s, is a portable open-source platform — with a rapidly growing ecosystem — for managing containerized workloads and services. Kubernetes aids declarative configuration, automates deployment, and manages cloud-native applications with on-premise systems or public cloud infrastructure.
What Is a Kubernetes Cluster?
A Kubernetes cluster is a set of nodes for running containerized applications. A node is a device or data point in a network. With a Kubernetes cluster, teams can run containers in multiple environments such as public clouds, on-premise, virtual, or physical environments.

Clusters often comprise a control plane — which manages the cluster’s desired state — and some worker nodes, which could be virtual machines or physical computers depending on the cluster. Each Kubernetes cluster has a desired state that determines elements such as applications or running workloads, corresponding images, and configuration details.
Benefits of Kubernetes Architecture
The idea behind the cloud-native computing approach is to put your applications within containers and then manage them against available resources using Kubernetes.

Beyond orchestration itself, Kubernetes as a platform solves many enterprises’ IT issues. Some of the benefits of Kubernetes architecture include:

Service discovery. Service discovery is the process of automatically locating devices on a network. Kubernetes has labels and annotations for additional metadata to identify and group objects with similar attributes. These labels and annotations make it easy to associate a service with a group of pods in service discovery.
Storage orchestration. Kubernetes allows teams to mount chosen storage systems, such as public cloud providers and local storage, into pods.
Flexibility. A container runtime or engine is a program that runs containers. Kubernetes supports several types of container runtime and infrastructure as long as they have some version of Linux or Windows. K8s portability makes it easy for development teams to switch engines, servers, or environmental configurations.
Multi-cloud operations. Many organizations believe that cloud computing is the best way to handle IT operations. Each cloud provider offers unique interfaces, posing a danger that a customer’s operations may be “locked” into that specific provider. This risk makes many companies adopt a multi-cloud strategy. Kubernetes supports multi-cloud infrastructure and quickly scales its environment from one cloud to another.
Developer productivity. Kubernetes has an operations-friendly approach that enables development and operations (DevOps) teams to innovate, scale, and deploy faster than they previously could.
Bin packing. Kubernetes fits containers into nodes based on defined resources such as CPU, RAM, and the cluster of nodes developers provide for containerized risks.

Using Kubernetes for Containers Eases Application Deployment
Containers allow organizations to streamline the development process for an automatic transition between the developer and the production deployment. Containers free up developers to use whatever languages and frameworks they prefer, given the ability to package all the dependencies for these specific choices within the container itself.

On the operations side, Kubernetes allows operators to make the best use of available resources by moving containers or having them automatically moved around to best match the optimal performance and price.
Major Cloud Providers Now Support K8s Deployment
Google first created Kubernetes based on its software for managing containers, called The Borg. The company was already using containers in its operations for well over a decade. Company engineers had plenty of expertise and best practices in hand when designing this new software, which was released as open-source in 2014 and is now hosted by the Cloud Native Computing Foundation (CNCF).

Many major cloud vendors now offer Kubernetes as a service, since K8s provides an abstraction through a set of APIs that allows users to potentially mix and match cloud services.
How Organizations Can Improve Kubernetes Deployment
Efficient deployment greatly impacts the development process, resource management, and user experience. There needs to be structure in central organizational governance to ensure that teams efficiently deploy code.

Here are some areas development teams need to consider to avoid governance challenges in Kubernetes deployment:

Visibility and Management. As clusters grow, managing and tracking them becomes a complex task. Troubleshooting problems is also time-consuming if different software is used because one solution may not work for all programs. Centralized governance and updates on application performance are essential for successful deployments. Operators need to actively and consistently obtain insights about their systems to prevent visibility issues.
Operational Complexity. Having multiple Kubernetes clusters in different business units leads to difficulties in user identity tracking. When users onboard, offboard, or change teams, operators may lose the ability to define user responsibilities and roles. This process ensures that the right user performs their tasks within the environment. Teams should also set structures to detect role violations, conduct adequate compliance checks, and assess management risks. When there are fewer potential risks, efficiency is possible.
Developer and operator empowerment. Although Kubernetes supports the DevOps approach, there is a need to balance developers’ freedom and operators’ ability to manage policies and ensure the environment’s security. Organizations need to define the extent of developers’ innovative independence so that necessary procedures are not compromised.

Get the Latest Updates on the Kubernetes Platform at The New Stack
At The New Stack, we monitor how enterprise Kubernetes adoption impacts business outcomes. We’re also watching how Kubernetes advancements will accommodate artificial intelligence and machine learning (AI/ML) workload in production. And we keep a close eye on how the Kubernetes community prioritizes cloud-native security improvements.

Bookmark this page to stay current on Kubernetes developments.


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Kubernetes / Machine Learning
5 New Kubeflow 1.3 Features that Machine Learning Engineers Will Love
25 Jun 2021 8:00am, by Janakiram MSV
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Lightning-Fast Kubernetes Networking with Calico and VPP
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Kubernetes: An Examination of Major Attacks
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Krustlet Brings WebAssembly to Kubernetes with a Rust-Based Kubelet
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