Overview of Kubernetes evolution from virtual servers and Kubernetes architecture!

Kubernetes is a portable, extensible, open-source platform for managing containerized workloads and services that facilitates both declarative configuration and automation. It has a large, rapidly growing ecosystem. Kubernetes services, support, and tools are widely available. In this article, we first review the evolution of Containers and Kubernetes in particular followed by discussing where Kubernetes can or can not do. At last, we have high level overview of Kubernetes architecture.

1- Evolution of Kubernetes

The history of application deployment started with hosting applications on physical servers, then moving to using virtual servers to distribute server resources (both hardware and software) to multiple applications to recent advances and uses of containers. The following walks you through the evolution of containers such as Kubernetes.
Traditional physical server era: Early on, companies used physical servers. There was no way to define resource boundaries for applications in a physical server, and this caused resource allocation problems. For example, if multiple applications run on a physical server, there can be instances where one application would take up most of the resources, and as such, the other applications would underperform. A solution for this would be to run each application on a different physical server. But this did not scale as resources were underutilized, and it was expensive for organizations to maintain many physical servers.

Virtualized Server era: As a solution, virtualization was introduced. It allows you to run multiple Virtual Machines (VMs) on a single physical server’s CPU. Virtualization allows applications to be isolated between VMs and provides a level of security as the information of one application cannot be freely accessed by another application.
Virtualization allows better utilization of resources in a physical server and allows better scalability because an application can be added or updated easily, reduces hardware costs, and much more.
Each VM is a full machine running all the components, including its own operating system, on top of the virtualized hardware.

Container server era: Containers are similar to VMs, but they have relaxed isolation properties to share the Operating System (OS) among the applications. Therefore, containers are considered lightweight. Similar to a VM, a container has its own filesystem, CPU, memory, process space, and more. As they are decoupled from the underlying infrastructure, they are portable across clouds and OS distributions.
Containers are becoming popular because they have many benefits. Some of the container benefits are listed below:

 

  • Agile application creation and deployment: increased ease and efficiency of container image creation compared to VM image use.
  • Continuous development, integration, and deployment: provides for reliable and frequent container image build and deployment with quick and easy rollbacks (due to image immutability).
  • Dev and Ops separation of concerns: create application container images at build/release time rather than deployment time, thereby decoupling applications from infrastructure.
  • Observability not only surfaces OS-level information and metrics, but also application health and other signals.
  • Environmental consistency across development, testing, and production: Runs the same on a laptop as it does in the cloud.
  • Cloud and OS distribution portability: Runs on Ubuntu, RHEL, CoreOS, on-prem, Google Kubernetes Engine, and anywhere else.
  • Application-centric management: Raises the level of abstraction from running an OS on virtual hardware to running an application on an OS using logical resources.
  • Loosely coupled, distributed, elastic, liberated micro-services: applications are broken into smaller, independent pieces and can be deployed and managed dynamically – not a monolithic stack running on one big single-purpose machine.
  • Resource isolation: predictable application performance.
  • Resource utilization: high efficiency and density.

 

2- What Kubernetes Can Do

Containers are a good way to bundle and run your applications. In a production environment, you need to manage the containers that run the applications and ensure that there is no downtime. For example, if a container goes down, another container needs to start. Would not it be easier if this behavior was handled by a system?
That’s how Kubernetes comes to the rescue as it automates some tasks there were traditionally done by system admins. Kubernetes provides you with a framework to run distributed systems resiliently. It takes care of your scaling requirements, failover, deployment patterns, and more. For example, Kubernetes can easily manage a canary deployment for your system. In short, Kubernetes provides you with:

 

  • Service discovery and load balancing
    Kubernetes can expose a container using the DNS name or using their own IP address. If traffic to a container is high, Kubernetes is able to load balance and distribute the network traffic so that the deployment is stable.
  • Storage orchestration
    Kubernetes allows you to automatically mount a storage system of your choice, such as local storages, public cloud providers, and more.
  • Automated rollouts and rollbacks
    You can describe the desired state for your deployed containers using Kubernetes, and it can change the actual state to the desired state at a controlled rate. For example, you can automate Kubernetes to create new containers for your deployment, remove existing containers and adopt all their resources to the new container.
  • Automatic bin packing
    Kubernetes allows you to specify how much CPU and memory (RAM) each container needs. When containers have resource requests specified, Kubernetes can make better decisions to manage the resources for containers.
  • Self-healing
    Kubernetes restarts containers that fail, replaces containers, kills containers that don’t respond to your user-defined health check, and doesn’t advertise them to clients until they are ready to serve.
  • Secret and configuration management
    Kubernetes lets you store and manage sensitive information, such as passwords, OAuth tokens, and ssh keys. You can deploy and update secrets and application configuration without rebuilding your container images, and without exposing secrets in your stack configuration.

 

3- What Kubernetes Can Not Do

Kubernetes is not a traditional, all-inclusive PaaS (Platform as a Service) system. Since Kubernetes operates at the container level rather than at the hardware level, it provides some generally applicable features common to PaaS offerings, such as deployment, scaling, load balancing, logging, and monitoring. However, Kubernetes is not monolithic, and these default solutions are optional and pluggable. Kubernetes provides the building blocks for building developer platforms, but preserves user choice and flexibility where it is important.
Kubernetes:

  • Does not limit the types of applications supported. Kubernetes aims to support an extremely diverse variety of workloads, including stateless, stateful, and data-processing workloads. If an application can run in a container, it should run great on Kubernetes.
  • Does not deploy source code and does not build your application. Continuous Integration, Delivery, and Deployment (CI/CD) workflows are determined by organization cultures and preferences as well as technical requirements.
  • Does not provide application-level services, such as middleware (for example, message buses), data-processing frameworks (for example, Spark), databases (for example, mysql), caches, nor cluster storage systems (for example, Ceph) as built-in services. Such components can run on Kubernetes, and/or can be accessed by applications running on Kubernetes through portable mechanisms, such as the Open Service Broker.
  • Does not dictate logging, monitoring, or alerting solutions. It provides some integrations as proof of concept, and mechanisms to collect and export metrics.
  • Does not provide nor mandate a configuration language/system (for example, jsonnet). It provides a declarative API that may be targeted by arbitrary forms of declarative specifications.
  • Does not provide nor adopt any comprehensive machine configuration, maintenance, management, or self-healing systems.
  • Additionally, Kubernetes is not a mere orchestration system. In fact, it eliminates the need for orchestration. The technical definition of orchestration is execution of a defined workflow: first do A, then B, then C. In contrast, Kubernetes comprises a set of independent, composable control processes that continuously drive the current state towards the provided desired state. It should not matter how you get from A to C. Centralized control is also not required. This results in a system that is easier to use and more powerful, robust, resilient, and extensible.

Now that we learned what is Kubernetes as well as their capabilities and limitations, we move on to briefly review its architecture.

4- Kubernetes Architecture

Kubernetes is made up of the following components:

  • Kubernetes master
  • Kubernetes nodes
  • etcd
  • Kubernetes network

Here we briefly go over each component. For more in depth study, visit Kubernetes documentation site.

I. Kubernetes master
The Kubernetes master is the main component of the Kubernetes cluster. It serves several functionalities, such as the following:

  • Authorization and authentication
  • RESTful API entry point
  • Container deployment scheduler to Kubernetes nodes
  • Scaling and replicating controllers
  • Reading the configuration to set up a cluster

There are several daemon processes that form the Kubernetes master’s functionality, such as kube-apiserver, kube-scheduler and kube-controller-manager. Also, Hypercube and the wrapper binary can launch all these daemons. In addition, the Kubernetes command-line interface, kubect can control the Kubernetes master functionality.

II- Kubernetes node
The Kubernetes node is a slave node in the Kubernetes cluster. It is controlled by the Kubernetes master to run container applications using Docker or rkt.

III- etcd
etcd is the distributed key-value data store. It can be accessed via the RESTful API to perform CRUD operations over the network. Kubernetes uses etcd as the main data store.

IV- Kubernetes network
Network communication between containers is the most difficult part. Because Kubernetes manages multiple nodes (hosts) running several containers, those containers on different nodes may need to communicate with each other. If the container’s network communication is only within a single node, you can use Docker network or Docker compose to discover the peer. However, along with multiple nodes, Kubernetes uses an overlay network or container network interface (CNI) to achieve multiple container communication.

Summary

In this article, you learn about the evolution of containers and Kubernetes in particular from traditional virtual server hosting. As websites are growing in complexity of services and traffics, the need for adopting Kubernetes increases. We also briefly reviewed the key architectural components of Kubernetes which you can explore in more depth by reading the below two follow-up articles:
Comprehensive guide for migration from monolithic to microservices architecture
Review of 17 essential topics for mastering Kubernetes
9 advance topics for deploying and managing Kubernetes containers