StarAgile
Nov 27, 2024
3,735
20 mins
Docker vs Kubernetes is a comparative study to know them in greater detail.
Cloud technologies are the latest buzz words and transforming lives and technologies across all domains. There are a lot of popular commercial cloud service providers and there are open source cloud providers also.
Cloud architecture benefits in various ways than on-premises architecture such as no cost of deployment, scalability, business continuity, collaboration, meter cost that is Pay-as-u-Use, no overheads, no maintenance cost, and easy to deploy architectures.
Cloud technology consists of three service models and they are Infrastructure-as-a-Service (IaaS), Platform-as-a-Service (PaaS), and Software-as-a-Service (SaaS). There are 4 deployment models and they are Private, Public, Community, and Hybrid Cloud.
You can deploy both open sources as well as private applications on the cloud. In this article, we will get to know about 2 cloud technologies namely Kubernetes and docker.
We will start knowing about the dockers first and it is the software that runs on the OS and supports many containerized applications. Containerization is a concept that makes each application runs on an OS that has its unique instance of the OS. By this, the application is said to be run in a container in such a way that it is independent and isolated from every other application and systems and gets its OS instance. Docker has such many containers and each container has its specific application. Docker allows creation, running, and managing containers in just one OS.
Unlike VM’s which take a long time to deploy and also configure the hardware in the cloud, we use docker networking which virtualizes the OS and runs isolated applications on top of the single OS. Each application with its libraries and binaries forms the container.
Now, coming to Kubernetes, it is used for the process of automating the scaling, fill in, managing, and getting rid of containers. It is used for orchestrating the containers. Kubernetes allows us to run containers across multiple compute nodes.
There are 2 concepts to know in Kubernetes such as nodes and pods.
For example, if you have a web server and cache server that are interdependent on one another they can be put in a single pod.
There are 2 types of nodes they are a Master node and worker node.
There are several features of docker, they are as follows,
We will look at 3 of the features in detail
a)Application Isolation – It is used to isolate the independent application and binds it with the OS with a unique and distinct instance. Thus it provides application isolation by isolating the application containers.
b)Swarm – This tool is used to schedule and cluster the Docker containers. It uses docker API as the front end which provides us the various tools to control it. It can be used as a pluggable backend and helps us to control the cluster of hosts as a single virtual host.
c)Security Management – It helps to create security management by allowing us to save secrets in the swarm itself. Then we can give the service access to certain secrets. Some of the commands such as secret create and secret inspect can be executed using this.
Again before we compare Docker vs Kubernetes you need to know their features in detail. Here you go with the same.
1) Sidecars – Sidecars enables the pod to have an additional container to be used as a watcher or proxy. This additional container then can be used for managing the applications. The sidecars can be used for logging or authentication of the primary containers. Sidecars can be used without modifying the source code of the primary container and can communicate with all the containers in a particular pod.
2) PodDisruptionBudget – PDB is the feature of Kubernetes which restricts the number of Pods in the cluster. It allows keeping the minimum number of pods active when there is auto-scaling down, maintenance and upgrading. When there is an administrative activity it helps to prevent application availability and performance from being impacted.
3) Health Checking – We can check the health of the pod or applications by putting a probe called a kubelet agent.
a)Readiness Probe – This determines whether the pods are ready to take the requests. If the probe fails, then the IP address of the pod is removed from any endpoints that direct the traffic to the pod.
b)Liveness Probe – This determines if the container is live and if not then it kills the container and the container is restarted.
c)Start-Up probe – This determines if the application inside the container is ready and live, if not it kills the container and restarts the container.
Probes can be customized with parameters such as minimum retry attempts, delayed runtimes, timeouts, and minimum success or failure thresholds
Serial # | Parameters | Docker | Kubernetes |
1 | Definition | Docker allows us to make containers that host isolated applications. | Kubernetes is used for the process of automating the scaling, fill in, managing, and get rid of containers. |
2 | Developed by | Docker Inc | Google Inc |
3 | Features |
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4 | Cluster Setup | Setup is complicated. Cluster Strength is strong. | The cluster setup is simple. Requires only two commands. Cluster Strength not as strong |
5 | Community | User communities update the software | Open source communities and big companies like Google, Amazon, Microsoft, and IBM support Kubernetes |
6 | Companies using | eBay, Spotify, Twitter, Pinterest, etc | Buffer, 9GAG, Evernote, Intuit, etc. |
7 | Compatibility | Customizable and Less extensive | Highly customizable and highly comprehensive |
8 | Container Limit | Maximum of 95000 container | Maximum of 300000 containers |
9 | Data volume | Shares storage volumes between multiple containers in the same Pod. | Shares storage volumes with any other container |
10 | Github forks | 15.5 k | 18.7 k |
11 | Github starts | 53.8 k | 54.1 k |
12 | Installation | Easy & fast | Complicated & time-consuming. |
13 | Large clusters | High Speed is considered for the strong cluster states | Does not consider the speed but Offers container deployment and scaling, even in large clusters |
14 | Load balancing | Auto load-balancing is done | Manually configure your load balancing settings |
15 | Node Support | Supports up to 2000 nodes and more | Supports up to 5000 nodes |
16 | Optimization | Optimized for a single large cluster | Optimized for multiple smaller clusters of SDLC |
17 | Public cloud service provider | Azure only. | Google, Azure, and AWS |
18 | Scalability | Scaling up is faster than K8S. But, its cluster strength is not as robust. | Scaling up is slow compared to docker. However, guarantees stronger cluster state Load balancing needs manual service configuration. |
19 | Scaling | No Autoscaling | Auto-scaling |
20 | Slave | Worker | Nodes |
21 | Support for logging and monitoring tool | It allows you to use a 3rd party tool like ELK | It offers an in-built tool for logging and monitoring. |
22 | Tolerance ratio | High fault tolerance | Low fault tolerance |
23 | Updates | An agent update can be performed in place. | A cluster can be upgraded in place. |
Docker can be used without Kubernetes as it becomes very challenging to use Kubernetes. Whereas, Kubernetes is a container orchestration tool and can be used with Docker as well as other containerized applications.
Both do not depend on each other; they can be used independently of each other. However, they can be used with one another also and its features can be leveraged to make the container applications stronger.
If you want to learn about Docker vs Kubernetes do enroll for the DevOps Online Training at StarAgile or call us on +91 – 80502 05233
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