WHAT ARE KUBERNETES SERVICES AND WHY DO PROGRAMMERS NEED THEM?

Kubernetes is an open-source platform designed to manage containerized workloads and services with a focus on automation and configuration. It supports a variety of container environments and is highly extensible, featuring a broad and rapidly expanding ecosystem. Tools, support, and services for Kubernetes are readily available. What problems do Kubernetes services solve?

Kubernetes services – artistic impression. Image credit: Growtika via Unsplash, free license

The origin of Kubernetes services

The origin of Kubernetes and its services can be traced back to the experiences and technological developments at Google.

The name “Kubernetes” comes from the Greek word for helmsman or pilot. The shorthand “K8s” derives from counting the eight letters between the “K” and the “s” in the word. This technology was essentially born out of Google’s internal platform called Borg. Borg was developed to manage and orchestrate containerized applications across massive clusters of machines, which significantly influenced the design and architecture of Kubernetes.

Google made Kubernetes an open-source project in 2014, incorporating more than 15 years of its experience in running large-scale workloads, along with community-driven best practices and innovations.

As for Kubernetes services specifically, they are a conceptual and practical evolution of the patterns and tools developed and used internally at Google. Kubernetes services allow for the management and exposure of application services within the Kubernetes environment, providing a consistent way to access the ephemeral and dynamic backends created as part of deployments. This functionality reflects Google’s philosophy in efficiently handling service discovery and load balancing at scale, which are crucial for managing microservices and distributed systems in a cloud-native environment.

Coding, programming – illustrative photo. Image credit: Tai Bui via Unsplash, free license

Kubernetes, large-scale deployments and Pods

At its core, Kubernetes excels at running large-scale containerized applications, ensuring that various application components can seamlessly interact. This interaction is facilitated by Kubernetes Services, which enable efficient communication both within the cluster and with the external environment.

In the Kubernetes environment, Pods are ephemeral entities (for example, data structures) that are dynamically managed to ensure the cluster maintains the desired number of replicas of an application—creating and terminating Pods as needed to meet this state.

For instance, if the demand for an application increases, Kubernetes can automatically initiate additional Pods to manage the load. Conversely, if a Pod fails, Kubernetes swiftly replaces it to maintain service continuity. Updates to applications are handled similarly, with old Pods being replaced by new ones carrying the updated code.

However, this dynamic creation and termination of Pods pose a challenge in terms of connectivity due to their changing IP addresses. This is where Kubernetes Services come into play, providing a stable access point to a continually adjusting group of Pods. Thus, even though the Pods themselves may change, the Services ensure there is a consistent location through which the application remains accessible.

A server room. Image credit: Taylor Vick via Unsplash, free license

Advantages of containerized deployment approach

When operating applications on individual physical servers – which is now considered a ‘traditional’ approach – such setup did not allow for the definition of resource boundaries within a server, leading to issues such as resource monopolization by certain applications, which caused others to underperform.

A straightforward but inefficient solution was to allocate one physical server per application, which led to underutilization of resources and increased costs due to the need to maintain numerous servers.

To address these issues, virtualization technology was introduced. This innovation allowed multiple Virtual Machines (VMs) to run on a single physical server’s CPU. Virtualization helps isolate applications across different VMs, enhancing security by restricting applications from accessing each other’s data directly. It improved resource utilization and scalability, enabling easier application updates and additions, reducing hardware expenses, and simplifying the presentation of physical resources as a cluster of disposable virtual machines. Each VM operates as a complete unit with its own OS on the virtualized hardware.

However, the evolution of programming environments did not stop here. Containers emerged as a next step from VMs, offering lighter isolation by allowing applications to share the host system’s OS, making them more lightweight. Like VMs, containers maintain their own filesystem, CPU, memory, and process space, but with greater flexibility. They are also infrastructure-independent, enhancing portability across different clouds and OS distributions.

Containers have gained popularity for several reasons:

• They streamline the process of creating and deploying applications by simplifying container image creation compared to VM images.
• Containers support continuous development, integration, and deployment, enabling reliable and frequent builds with quick rollbacks due to image immutability.
• This approach helps separate development and operations concerns by allowing images to be created at build/release time, thereby decoupling applications from infrastructure.
• The use of containers offers enhanced observability, providing insights into OS and application health.
• They ensure environmental consistency across different stages of development, from local systems to the cloud.
• Containers are highly portable, running on various systems and infrastructures, from Ubuntu to RHEL, and from private data centers to public clouds.
• They also facilitate application-centric management by shifting the focus from running an OS on virtual hardware to running an application on an OS using logical resources.
• Furthermore, they enable the architecture of loosely coupled, distributed, elastic, and autonomous microservices, allowing dynamic deployment and management.
• This kind of programming environment provides predictable application performance through resource isolation.
• Through containerization, it is possible to achieve high efficiency and resource density, optimizing operational cost and infrastructure usage.

Thus, the evolution from physical servers to virtual machines and then to containers represents a significant advancement in how technology is leveraged to maximize efficiency, reduce costs, and increase the agility of software development and deployment.