An open source container management platform, Kubernetes allows companies to manage containerized workloads and services. Kubernetes automates deployment, manages cloud native applications, and aids declarative configuration in conjunction with on-premise systems or public clouds.
Although technically best described as a container orchestration engine, Kubernetes is rapidly becoming the infrastructure platform for cloud native computing, an approach to flexibly using public or private clouds.
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.
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’s desired state determines elements such as applications or running workloads, corresponding images, and configuration details.
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, 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 into pods, such as public cloud providers and local storage.
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.
Can You Live without Kubernetes? We don’t think you should. Discover more about Kubernetes.
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 multicloud strategy. Kubernetes supports multicloud 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.
Containers allow organizations to streamline the development process to transition between the developer and the production deployment automatically. 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 use available resources best by moving containers or having them automatically moved around to best match the optimal performance and price.
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 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 potentially allows users to mix and match cloud services.
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 are 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. To prevent visibility issues, operators must actively and consistently obtain insights about their systems.
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 must define the extent of developers’ innovative independence so that necessary procedures are not compromised.
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) workloads in production. And we keep a close eye on how the Kubernetes community prioritizes cloud-native security improvements.