The Era Before Kubernetes
In this segment, we are going to discuss the various methods of deployment before the arrival of Kubernetes.
Let’s get started with the traditional deployment era, where organizations ran applications on physical servers. When applications were on physical servers, there were issues of resource allocation as there was no way to define resource boundaries for applications.
For example, in this traditional method, there could be a few cases of underperformance as a single application would take up most of the resources.
One evident solution to the problem above is to run each application on a different physical server. However, in this probable solution resources are underutilised and hence did not scale and also proved to be expensive for organizations to maintain many physical servers.
After application being run on physical servers, there came a time of virtualized deployment. This was introduced primarily as a solution to the problems mentioned above.
Virtualized deployment basically allows developers to run multiple Virtual Machines on a single physical server's CPU and hence applications are isolated between different virtual machines. Hence, it has a high level of security because the information of one application cannot be freely accessed by another application. Also, there is a better utilisation of resources in virtualization and allows scalability as applications can be added and updated easily, reduces hardware costs, and provides many more such features.
Basically, a set of physical resources can be presented as a cluster of disposable virtual machines where each of them is a full machine that runs all the required components on top of the virtualized hardware.
After virtualisation, we reach the time where container deployment arrived and become popular. These containers are actually very similar to Virtual Machines however, the isolation properties to share the Operating System (OS) among the applications are relaxed and hence they are considered lightweight.
Containers have their own filesystem, share of CPU, memory, process space etc. Containers are a portable solution as they are decoupled from the underlying infrastructure. Containers are widely used and are extremely popular because of some of the benefits that it provides.
With the help of containers, developers can create and deploy agile applications. This technology increases ease of use and efficiency of creation and deployment of applications. It provides for Continuous development, integration, and deployment.
It decouples application from infrastructure as it creates application container images at the time of building or releasing the application rather than at the time of deployment.
There is consistency also as the development, testing and production runs on the same system as in the cloud. There is cloud and operating system distribution portability as it runs on Ubuntu, RHEL, CoreOS and on major public clouds.
Kubernetes and their Application
In the blog above, we mentioned that containers, in general, are a good way to bundle and run your applications. However, developers need to ensure that the containers that run the applications have no downtime. There has to behaviour in which starts another container if any container goes down.
Kubernetes comes into picture when this process is handled by a system. It provides a framework that can be used to run distributed systems resiliently. It also takes care of scaling and failover of applications and also provides patters for deployment.
With Kubernetes, users can have service discovery as well as load balancing. It can expose a container using DNS name or their own IP address. If there is high network traffic for a container, Kubernetes will load the balance and distribute the traffic in order to make the deployment stable.
There are self-healing Kubernetes also. They basically restart or replace containers that fail and also kills containers that don't respond to user-defined health check. They don't advertise them to the clients until they are ready to serve.
With Storage orchestration Kubernetes, a storage system of your choice can be automatically mounted. There are automated rollouts and rollbacks too. The desired state for the deployed container can be described using Kubernetes and the actual state can be changed to the desired state at a controlled rate, e.g., Kubernetes can be automated to create new containers for the deployment of the application and also to remove existing containers and adopt all their resources to the new container.
If there is a cluster of nodes with Kubernetes, it can use it to run containerized tasks. Kubernetes fit containers onto the nodes if the amount of CPU and memory (RAM) for each container is known. Automatic bin packing ensures best use of available resources
There are Secret and configuration management Kubernetes also that allows the storage and management of sensitive information, such as passwords, OAuth tokens, and SSH keys. The configuration of any application can be deployed without rebuilding the container images and maintaining high security standards.
The explanation above was an earnest effort to make you understand the concept of Kubernetes. I hope that the concept of Kubernetes is clear. However, there are a lot of misconceptions regarding Kubernetes. In the segment below, we try to elucidate what all Kubernetes is not.
Kubernetes cannot really be compared to a conventional Platform as a Service system. Kubernetes operates at the container level and not at the hardware level. It has some features that are common to Platform as a Service, such as deployment, scaling, load balancing and also lets the users integrate logging, monitoring, and alerting solutions.
This containerised solution is not monolithic. It provides the building blocks for building developer platforms but preserves user choice where it is important. The default solutions are optional and pluggable.
With Kubernetes, there is no limit to the type of applications supported. It has a variety of workloads, including stateless, stateful, and data-processing workloads. If an application is able to run in a container, it will run efficiently on Kubernetes too.
Kubernetes does not deploy source code or build the application. Continuous integration, delivery, and deployment workflows is decided by the culture and preferences of the organization as well as the technical requirements.
There are no application-level services in Kubernetes, such as middleware, frameworks for data-processing, various databases, caches, or cluster storage systems as built-in services. Portable mechanisms, such as the Open Service Broker can be used to run or access applications running on Kubernetes. We have some integrations as proof of concept and mechanisms to collect and export metrics but does not dictate logging, monitoring, or alerting solutions
Kubernetes gives a declarative API, targeted by arbitrary forms of declarative specifications but neither does it provide nor mandate a configuration language or system. Also, Kubernetes doesn’t provide comprehensive machine configuration, maintenance, management, or even self-healing systems.
We have discussed the concept of Kubernetes in detail. However, it is important to know that it is not a mere orchestration system, rather it eliminates the need for orchestration. Basically, orchestration is the execution of a defined workflow, for example, the instruction can be like first do step A, then step B, then proceed to step C. But Kubernetes, actually comprises independent, composable control processes that drive the current state towards the provided desired state. Basically, the procedure of getting from one step to another shouldn't matter and even centralized control is not required. Hence, Kubernetes is a system that is easy to use. It is a more powerful, robust, resilient, and extensible solutions.
We hope the concept of Kubernetes is clear! The basics of containerised technology is going to come handy every time you develop and deploy applications.
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