This blog is a comparison of Kubernetes and Docker, which are two popular terms in organizations that work on very large-scale projects 🥇 They both bring out their own set of benefits to organizations that are struggling to either keep up with the pace of demand, or aren’t able to manage their large multiple services. Without their presence, the task becomes too complex and deployments take forever. One error in the system and the developers keep digging into the project, wasting time to find it.
All of these problems are overcome by two softwares that have become a de facto part of projects: Kubernetes and Docker. But there is a misconception about the companies and as a consequence in people’s minds, that Kubernetes and Docker are competitors and you can only go with one. But in reality, it is not a question of Kubernetes vs. Docker, but rather of how Kubernetes and Docker can work together in sync. Throughout this post, I will try to convince you that Kubernetes and Docker are at their best when they work together, and most importantly, they are not competitors but two completely different software in the industry 🤯
Table of Contents – A Comparison of Kubernetes and Docker
- What is Docker?
- What is Kubernetes?
- Similarities Between Kubernetes and Docker
- Docker Swarm – Docker’s orchestration
- Challenges With Kubernetes
- Challenges with Docker
What is Docker?
Docker is a tool that allows organizations to run their product into packages called containers. These containers are independent of each other and allow us to save resources and implement quick deployments. Consider a scenario where the organization does not use Docker for their developments. As the product grows larger, it becomes hard to manage the modules and debug them during deployments. A better solution is to divide these large services into smaller units called microservices and run them separately. This way if any of the microservice raises a red flag, we would know instantly which one went down and can debug quickly 🚩
A conventional method to run these microservices is to run each of them separately on different virtual machines. This works in software management too, but the wastage of resources is unimaginable. Virtual machines are not that resource-efficient. They take a good amount of space (which is pre-allocated to them) and a lot of RAM. What if that microservice does not even require that much space? Remember that we are talking about a large-scale organization that can have hundreds of microservices and therefore hundreds of virtual machines tagged to them. This is where Docker plays its part. Docker works directly above the operating system and removes the burden of creating independent virtual machines for microservices. Instead, Docker comes with containers that pack these microservices into them and they can work independently establishing the same principle of virtual machine isolation. In addition, Docker containers do not even demand pre-allocation of space. They grow as the microservice inside them grows.
Benefits of Using Docker
Docker is a great tool that works in packaging microservices and managing large software. With Docker, we get the following benefits:
- Management: Docker eases out the management process by dividing larger services into smaller entities.
- Independent System: With Docker containers working independently in the system, the others are not impacted if one of the containers goes down. Hence, the application will continue without shutting down. Also, it becomes easier to debug the system when the system is independent.
- Saves Resources: Docker does not ask for a pre-allocated disk or primary memory space. Hence, the resources are used efficiently.
- Cost Saver: Taking into effect the above-mentioned points, Docker saves a lot of money by conserving space, resources and deploying applications faster.
- Portable: The Docker images can be hosted on the internet and can be pulled and run anywhere (given that the target OS is the same).
- Easy Roll Backs: Docker provides the functionality of rolling back to the previous stage quickly if anything goes wrong in the new container or image.
- Scalability: Docker makes your application highly scalable with ease.
Alright! Now that we know one of the paddles that are steering up our boat, let’s check what the second paddle has in for us 💪
What is Kubernetes?
When we hear about Kubernetes, normally, we hear about the term “orchestrator” along with it. In general, an orchestrator is someone who commands and guides an orchestra bringing out the music a composer intended to. Kubernetes is also called the container orchestrator because of the similar things it does to a container system.
Kubernetes is a tool that manages your container infrastructure. So, any guesses on who provides those container infrastructures? Yes, Docker! Docker provides an environment for the containers to work together, but we need something that can manage that environment like a music orchestrator does with the music 🎵 A tool that can command and steer the system in the right direction. Kubernetes is that tool that can manage and command these containers to do the work that will establish the final goal of the microservices system.
Kubernetes’ primary job is to orchestrate the container applications. For this to happen, it needs a simplified architecture for itself. This architecture consists of two types of nodes in Kubernetes: the worker nodes and the master node. The master node takes on the responsibility of assigning the work to the worker nodes. The below image is the depiction of these nodes:
With the help of these nodes, we aim to establish the ultimate goals for our cluster-based system. Kubernetes brings down the downtime as it keeps in check for every container for if it’s working correctly or not. If any of the containers crashes due to recent upgrades, Kubernetes is fast enough to run it again with the last available version. Also, Kubernetes is extremely helpful in debugging issues in the containers.
So, as you can see, it is not a question of whether we need to use Kubernetes or Docker. It is the question of how to use both of them when we go for microservices-based deployments. In my personal opinion, this question can be answered just by looking over both of their logos. Docker’s logo is like a merchant navy ship with lots of containers 🐳 Kubernetes’ logo on the other hand is the ships’ steering wheel which in a hypothetical way can be seen as something that will steer the container-based system i.e. Docker 🎡
Hope this connection of logos helps you remember each of their work! Just like Docker, or any other popular tool, we get a bunch of benefits with Kubernetes as well. The most beneficial of them are highlighted in the next section.
Benefits of Kubernetes
Using Kubernetes also brings a set of benefits along with it:
- Easy Deployment: Kubernetes facilitates easy software deployments and provides automated features for them.
- Easy Development: Kubernetes is a container orchestrator tool. Hence, it does the tough job of managing so many containers and their work, smoothing out the development work.
- Monitoring Features: Kubernetes provides monitoring features for container-based applications which is an added advantage when containers start to grow in large numbers. The more containers we have, the tougher it becomes to monitor them.
- Scaling Advantages: Kubernetes helps in scaling the container-based system with ease in real-time. It also helps in scaling the environment to multiple cloud-based hosts.
- Testing Features: Kubernetes provides testing features for the complete software or the cluster on which you are working. This makes it easier to identify the faulty container and debug it for corrections.
- Flexible: Kubernetes is flexible enough to merrily work with any container runtime so that the developers can choose their favorite ones.
- Open-Source: Kubernetes is open-source software and like any other, it is free, has a vast community, and brings regular updates (including feedback work).
- Logging Functionality: Kubernetes also provides us with logging functionalities to log various resource usages such as CPU usage etc.
Similarities Between Kubernetes and Docker
While the fundamental principle of working in Docker and Kubernetes is different, they provide some common benefits to the overall software development process when we look at it as an aerial view. Some of these similarities can be sufficed as below:
- Kubernetes and Docker both increase the developer’s productivity by providing him with easy-to-use options.
- Kubernetes and Docker are both used for software development that includes microservices.
- Kubernetes and Docker both facilitate a faster upgrade cycle and enhanced automation testing capabilities.
- Bringing Kubernetes and Docker cuts down the overall project development cost (even if only one of them is deployed).
- Kubernetes and Docker both help in scaling the software to a larger level with ease.
- Both of the technologies are open-source and available for free to use.
- Kubernetes and Docker both come in lightweight binaries due to their internal programming structure.
- The file type used in Kubernetes and Docker is YAML, which is human-readable and easy to write commands with.
Docker Swarm – Docker’s Orchestration
A Docker swarm is a method of grouping various containers to form clusters and run various commands on them. Through these commands, we can perform various actions such as networking, scaling, and securing the clusters. Since it orchestrates the Docker containers in the infrastructure, we can call it Docker’s own orchestration tool. With these two options in our hands, let’s find out some differences between them 🤔
Kubernetes vs. Docker Swarm
More than about the similarities, I have found that people are eager to learn about the differences between Kubernetes and Docker Swarm. Here is a list of major differences between them:
|Management and Installation Units||Pods||YAML files/ Swarm Files|
|Scalability Factor||Comparatively Slower||Highly Scalable|
|Availability||Highly Available||Highly Available|
|GUI||Enhanced and Detailed||No in-built GUI module|
|Monitoring||Efficient and Detailed monitoring facilities||No in-built monitoring facilities|
|Load Balancing and Networking||Manual setup through DNS assignments.||In-built load balancers.|
Challenges with Kubernetes
Kubernetes and Docker do provide us with easy deployments and monitoring services. Not to mention they save our resources to a large extent. Who wants 100 VMs running on large machines all the time when we can directly deploy over the operating system? But it isn’t a smooth process at the beginning or after a long run too. By inviting Kubernetes into our infrastructure, we invite the following challenges along:
Security – Based Challenges
The primary and most common problem with Kubernetes architecture is the security flaws. Kubernetes architecture cannot be maintained with the conventional security analysis and configurations as we would do on our stand-alone application. Kubernetes has had a very scary past when it comes to its security issues. In 2018, Tesla’s Kubernetes architecture was infiltrated and breached by hackers to mint the cryptocurrency from their resource.
Security challenge has topped the list among the developer’s survey which calls for special attention in its security analysis.
Small Companies – Time and Cost Management
Kubernetes is an extremely important tool when it comes to large-scale applications such as Paypal or Netflix. They are spanned over 90% of the globe and have data centers at various locations that need management. But is Kubernetes a good choice for small companies?
Working with Kubernetes becomes a challenge when we talk about small-scale companies that have just entered the market and are still in their initial phase. Sure they know how to work with Kubernetes and how to handle its configurations, but the core aim of developing Kubernetes is to manage very large-scale applications. Kubernetes can be applied to small-scale projects too, but honestly, they don’t need it. It’s like using a supercomputer to run Microsoft word. You can do it but you don’t need to. The downside of this is that we end up wasting a lot of time configuring Kubernetes and paying for its cost (manual labor). The best time to go for Kubernetes is when we know we will be scaling in a couple of months and have established a good market.
Networking – Based Challenges
Another challenge that we face with Kubernetes is the networking challenge which is also the second topper in the list shown above. Kubernetes uses Pods to manage the containers. But these do not work as traditional IP address allocation, which we do with other things like MVC structures. Kubernetes works on the network entities and other information provided in the metadata. Such things are easier to configure and manage in small-scale applications, but as the application grows in size, so do these Pods and hence, the containers beneath them. When any Pod is deleted or spun, managing these networks brings us to the zeroth level of implementing networks again.
Also, Kubernetes works across multiple cloud infrastructures, which is one of its major benefits. These cloud infrastructures have their own network policies and constraints to maintain and prevent security breaches. Using Kubernetes we face additional challenges of networking when we take our application to the cloud (hybrid, public or private) 🌐
Along with these challenges, each company may face its own set of challenges that cannot be generalized for everyone. For example, the storage challenges can be considered personal to the companies as some companies have no problem in this segment. Sometimes configuring a load balancer along with the Kubernetes environment becomes a challenge too, but again such challenges are personal to the organization or teams working on it. If you have faced any such challenges, we would love to hear from you in the comment section!
Challenges with Docker
Docker is a service that provides a containerized environment to run our microservices smoothly. But like Kubernetes, it looks really easy by the definition. However, as our developers would know, Docker is not that easy to run on the system. It comes with the following challenges:
Monitoring the Containers 🔍
Docker is a very popular tool for businesses thriving in the market and making a global presence online. As these businesses grow, Docker starts to become a sea of containers that is hard to manage. Docker often goes up to eight containers per host which result in hundreds of container running the application. Monitoring all of them becomes very tough. Orchestration tools such as Kubernetes look like a solution but they only provide a platform with monitoring functionalities. That does not mean things start to monitor themselves magically 🧝♀️ On the ground level, monitoring so many containers may be the biggest challenge of all.
Another big challenge with applying Docker technology to the development process is the logging issues. Docker is extremely good at logging. It provides a stream of logs from the working containers that help understand the working and debug any issues with the infrastructure. This makes Docker very good at logging but, only at the container level. When it comes to these logs on a higher level (combined mix from every container) they become a mess too hard to clean. Sometimes, container produces logs from multiple processes that they are encapsulating within them. At the developer’s end, it becomes very hard to identify which process produced the error just by looking at the logs.
Today Docker is run by one-quarter of all the companies and the Docker deployment size has also seen a surge of 75% in a single year. When something becomes this popular (and is open-source), it invites hackers. Docker has been one of the main targets of hackers due to its security flaws. Once the Docker container is hacked, it is used for a variety of malicious and illegal activities. These include mining cryptocurrency Monero which is very hard to trace back. Analyzing the internal network of the infrastructure and accessing data files are other such examples. Docker’s security is flawed, but it can be managed with careful inspection and daemon-less configurations. Regular checks and implementing multiple layers along with orchestration software is also one solution that can prevent hacks into the system 🔥
So do these challenges makes it harder to work with Docker and Kubernetes? Actually, Kubernetes and Docker are the most popular technologies used for their respective targets. In a recently published Kubernetes statistics guide, 83% of the respondents were found to be using Kubernetes in production, up from 78% in 2019 and 58% in 2018. So, yeah, they are popular and as far as challenges are concerned, there is hardly any tool that is a piece of cake.
“What is the difference between Kubernetes and Docker?” has always been a popular question amongst people who are looking ahead to scale their operations and take things to the micro-level. But again, as I said a couple of times in this post, it’s not a “vs” question but rather a question of “How to use Kubernetes with Docker?”. Unfortunately, Kubernetes recently ended their support for Docker as they concluded their reasons with “it is going to be easy for everyone in the long run”. If you’re curious, you can read more about their reasons in their article “Don’t Panic”.
Docker is a containerization service that is used popularly across the world. But it can’t manage itself. It is like a packaging company that can come to your house and pack things up. Eventually, you need someone to put labels on it, ship them to the correct addresses, and resolve queries in case something unusual happens. In short, you need something to manage these containers which is where Kubernetes comes into action.
Docker and Kubernetes have gained success in information technology because they are worthy of it. They have become a necessity in the infrastructure and have crept so subtly into the complete system, that they are hard to get rid of now. They keep our software running even if it becomes so large that some part of it exists in another continent. This post was about a containerization service and an orchestration service, which are two separate entities. You can choose any containerization service available and any orchestration service too. Therefore, this post maintained the distance between Kubernetes and Docker and did not mix them up for good. As a result, you get a clear insight into two different technologies in a single post.
This blog reflected only my opinion. What do you think? I would love to hear your thoughts and suggestions in the comments section 🤩