Docker Reviews

In our company, I mostly design 5G networks and my work revolves around virtualization of the 5G core, which is known as backhaul. In our organization, we use many containerization technologies to obtain a proper ROI.

No-code servers and other servers are used in a combination predominantly as part of our company operations, which is the most relevant approach in the service provider or enterprise end. For small-scale customers of our organization, we use a combination of Kubernetes and Docker to drive adoption. 

One of the main use cases of Docker is resource utilization. Like traditional VMs, there is no need to depend upon reserving resources and it's much easier to spin up required instances for consumption using Docker. 

The capability of the solution to convert an application into a Docker image is a vital functionality. 

The learning curve with Docker is huge and extensive. Adopting Docker is a bit difficult because it requires a lot of expertise and background, including an understanding of networking and security concepts. Many professionals are facing issues with the different architectures that interact with each other in Docker.

Whenever in our company, we are working with the production environment, professionals are hesitant to adopt Docker due to the extensive learning curve, and most of the team members in our company are more accustomed to an environment like VMware instead of Docker. 

Docker runs on scripts, so if AI can automate most of the scripting process in Docker, it would be a great advantage in the future version of Docker. As of now, we can create scripts utilizing most of the functions within Docker, but that initial planning phase wherein to understand exactly how you will plan for the resources, how you will convert applications into a Docker-based image, and similar tasks needs to be simplified so that more professionals can adopt Docker.  

I have been working with Docker for almost four years. 

I would rate the stability an eight out of ten. Docker provides a highly stable environment to work with. 

I would rate scalability a five out of ten. In Docker, it's very difficult to predict how scaling works and this is where automation should be implemented. I would recommend Docker for small and medium-sized businesses as it provides a practical environment that can facilitate cost-savings. Docker also doesn't have critical workloads.

The applications used in critical workloads consume a high proportion of traditional server and physical infrastructure; by using Docker, the efficiency can be enhanced ten times. Docker is definitely a great option for small businesses that are trying to deploy applications on the cloud. Whether primarily deployed on-prem or cloud, with Docker the application can be moved in between them. 

I personally depend on the Docker community to resolve my issues with the product and avail support. 

The setup process of Docker is extremely simple. Docker is compatible with multiple operating systems, including macOS, Windows, and Ubuntu. 

I would rate the pricing of Docker as ten out of ten.  

OpenShift is gaining more popularity than Docker because it is used in enterprises that follow the traditional model. OpenShift is from Red Hat, and many enterprises are already running Red Hat-based systems at the back end, so it becomes much easier for them to move to OpenShift than to migrate to Docker.

For Docker based adoption, the entire existing infrastructure needs to be changed to migrate into the Docker environment but for OpenShift the older architecture just needs to be brought into the latest architecture. 

For container management, Kubernetes is our primary tool of choice in our organization, and we recommend the same for most of our customer's enterprise environments, but now we are witnessing a high adoption rate for OpenShift which has all the features of Kubernetes.

At our company, we are also noticing the rise of another competitor tool for Docker, which is called Amazon EKS, which runs on the cloud with a Kubernetes background. I can easily manage my public and private cloud using the same containerized environment and one single orchestrator. 

There are complexities in integrating Docker with other CI/CD tools because the available documentation is not straightforward. An expert is required with hands-on project experience to integrate Docker with other solutions. 

The solution should provide better deployment documentation with added project examples that can be used like a workbook by professionals. The vendor should develop and provide some explainer videos around Docker with a major focus on how AI has came to the picture and how Docker will provide integrations with automation and a Generative AI context. I have had two or three instances where I had used ChatGPT to deploy a code on behalf of me, but it took three of my colleagues to understand the AI-generated code. 

In recent days, I have noticed that enterprises are not adopting Docker, and they are choosing a solution like Proxmox. Other competitor solutions to Docker are easier to use, so the usability factor is causing the adoption of products other than Docker. But I would say Docker has a more mature environment than the competitors. 

The product is still at an early stage in terms of security. The basic aspects of security are covered, but there is a lot of room for improving the solution's security. Our organization works on container security and Docker should improve on container security. 

If you are working on Docker, you need to have expertise in the product, it's security, architecture and resource planning. I would choose OpenShift over Docker. I would overall rate Docker an eight out of ten. 

I'll definitely recommend Docker to users, especially to professionals who are working with a cloud-based environment, server-less architecture, or developers who are trying to build efficient applications. Docker is an excellent learning platform to initially get accustomed to basic architectures before shifting to more complex architectures like OpenShift. 

We are a service provider and we have various use cases. However, the most prominent one is that instead of virtualizing the application workloads, we use Docker. Docker allows you to create small applications and containerize them. You can create multiple such application containers that can run simultaneously on the Linux operating system.

We use Docker because if we want to create an application using Node.js, an environment for backend and frontend technologies, we can deploy this single application in a container. This container will run independently of its underlying OS. 

If you want to migrate this application to a different server, migrate the container image to the new server and start using the application there. This makes developers' jobs much easier because they don't have to copy everything the application needs. They just copy the container image, send it to a different server, and start using it there. All the required libraries, packages, and dependencies are encapsulated within that container. The container contains everything it needs to run. In a DevOps environment where multiple teams are creating applications, developing new versions, and deploying applications frequently, Docker is very helpful.

The greatest benefit of the solution is that you can create applications and multiple versions of the same application, distributing them across various Linux platforms. Setting up Docker is very quick; whereas setting up a Linux operating system can take five to ten minutes, you can set up a Docker-based Linux OS container within minutes. Docker also has a small footprint on memory and resources because it uses the system's resources efficiently. It operates within its environment, independent of the underlying operating system, running in its namespace. This isolation prevents negative impacts on the system.

For developers who frequently create and deploy applications, Docker makes it easy to quickly develop, deploy, and run the latest versions. You don't need to manage the operating system, applications, dependencies, or data separately; everything is encapsulated within the Docker container itself.

Moreover, AI is another application you can use through Docker. AI can help you set up more efficient Docker-based workloads. The role of AI is to guide you and provide the necessary knowledge for various tasks, whether it’s related to Docker or anything else. Additionally, AI itself can run as a container using Docker.

There's always room for improvement. Sometimes there's a bug or defect in the solution. However, the Docker team works on fixing it.

The solution’s stability is great. I rate it a nine out of ten.

Regarding scalability, Docker doesn't require any separate configuration for multiple users. Suppose you create a container and expose it to the public via an IP address and port. The ability to serve the number of users depends on the system's resources, like RAM, CPU, and storage. You can create or scale the number of containers based on these resources, and manage the number of users accordingly.

For example, if I have a small server, I can create containers and share them with the outside world according to the available resources. The server's ability to handle the number of users depends on its resources. Docker doesn't restrict you to a certain number of users; hundreds or even thousands of users can access the containers. Most of our customers are using the product.

The initial setup hardly takes minutes. All the container images are available on Docker Hub when you create a container. Docker Hub is a repository, like an App Store for containers. If you use Windows or Mac, you have an App Store where you can download and start using any application you want. Similarly, Docker Hub is the application store for containers. It's a cloud-based solution. In Docker Hub, you can find all kinds of container images. If you want to install an Apache server, a Postgres database server, or any other server—even Linux and Windows servers—they are all available in containers. Anyone who wants to use these can immediately download and start using the container image.

Our customers buy the software and the prices are available on Docker Hub. The subscription is typically yearly, and customers will need to buy the subscription directly. They can purchase it themselves.

The product is similar to GitHub.

If you are trying to create an application quickly for testing or development purposes, Docker is the best tool available. Docker can also be used on Mac and Windows with a tool called Docker Desktop. You can start using Docker there by installing Docker Desktop on a Windows or Mac system.

Whenever a new Docker image is created by the OEMs, like MySQL for instance, they name the new image with the version number. If you want to check the latest version, you can go to Docker Hub and search for it. There are multiple versions available, and Docker also allows you to create your own version. So let's say your company has specific requirements for MySQL. You can download the original MySQL image from Docker Hub, install a couple of additional applications within the Docker container, and share this customized Docker image via your own repository on Docker Hub.

There are two kinds of updates: one within the Docker technology itself, where the creators of Docker keep updating the Docker engine, and another for the Docker images. The Docker engine is the software tool that runs on your system, and the global team working on it keeps it updated. You can always check for the latest version of the Docker engine and upgrade as needed.

Moreover, container orchestration is a different technology. You need Kubernetes to orchestrate the containers in the solution. A single container is independent, but Kubernetes is an orchestration tool that manages these containers using its control and data planes. For example, if you have hundreds of containers, it takes work to manage each one independently. You need some orchestrator to control these containers' life cycles, maintain high availability, and more. Kubernetes handles this container orchestration.

Overall, I rate the solution a nine out of ten.

We use Docker for validation mechanisms and have built Docker images for our applications.

For container orchestration, we haven't used Kubernetes instances extensively. Docker works well for us.

It's flexible and easy to use. My team also finds it comfortable to work with.

Sometimes, it can become heavy and cause performance issues.

The stability is pretty good. 

We use horizontal scaling, and it works well. Considering its container architecture, I'd rate the scalability a nine out of ten. 

There are probably around 2,000 to 3,000 end users. It is extensively used. 

We have used Docker's technical support. I didn't have bad experience with the customer support. 

We used Kubernetes and other packaging techniques. 

Portability and accessibility were the main reasons we chose Docker. 

The initial setup is mostly straightforward. We used Ansible for deployment.

The ROI is high. Traditional deployments take more time and builds can be inconsistent across different environments. Docker solves these issues.

The value is there. Docker delivers high performance, leading to increased productivity. You can achieve more in less time, and your deployment cycle time is reduced.

I would rate the solution an eight out of ten.

AI with Docker is relatively new for us. But for traditional deployments like microservices and Spring Boot applications, Docker works very well.

I definitely recommend it. The landscape is changing, and Docker is transforming the way we approach deployments.

Currently, we are creating a JAR file and using microservices. There are around 178 services in a single project. We use Docker to manage and do load balancing for all the services together.

We are using Docker to host applications. We are using Docker Compose and sometimes Docker Screen.

We are facing multiple issues with the solution's stability.

We have been using Docker in the same project for five years, and we have recently deployed Docker into Kubernetes for four years.

We are facing multiple issues with the solution's stability. It is very difficult to analyze how much load a tool takes. Sometimes, our Docker images get crashed due to the unavailability of space.

I rate the solution a six or seven out of ten for stability.

Approximately, 400 users are using the solution in our organization.

I rate the solution a nine out of ten for scalability.

The solution’s initial setup is simple.

We implemented the solution through an in-house team. It took me around three to five hours to deploy the solution. Docker is easy to use and implement. For the deployment process, we used Docker in the CI/CD pipeline. Then, we pushed the Docker images to the Kubernetes as per the environment. We used Kubernetes to host and balance the load.

Since Docker is an open-source solution, it is free of cost.

Docker made it easy for us to monitor the microservices. Secondly, we were able to manage the key load balancer. Thirdly, we wanted to create a secure layer of protection for our organization. So, we started using the containers above the hypervisor.

It was like using a new operating system. We created our own network adapters. We created another isolated network inside the Docker containers to keep our organization and project safe and secure. We consider this very helpful in the secure software development life cycle.

We're implementing multiple stages in security. We are signing Docker images, Docker containers, Kubernetes containers, Kubernetes nodes, and clusters in cryptography. We are signing these so that no one tampers with the code or the docker images. We are doing this from a security point of view.

The solution's containerization helps us in providing integrity and availability. If you use a microservices architecture, I recommend implementing Docker and Kubernetes. I would recommend Docker and Kubernetes to manage multiple microservices running simultaneously.

We had to configure multiple services, like the utilization of the CPU and the utilization of the RAM for the service that we were building. Additionally, we had to mention the network adapters we will be using. We followed multiple benchmarks, like NIST Benchmarks and CIS benchmarks.

There were multiple advantages to using Docker. The most important advantage was scalability and availability. As I am working in the security team, I'm looking after the integrity of the Docker images.

Overall, I rate the solution an eight out of ten.

We set it up a lot of times to create environments for our students. 

When we teach our students, it's really important that everybody is on the same version of all their dependencies. So, Docker, we can set up the images on Docker, and it sets everybody up. 

So it's a much smoother process. Without Docker, without these containers, it would be a nightmare trying to get 20 to 30 students to set up their environments correctly. So this is just a really quick and easy way to use it.

Just the portability of Docker's containers and its ability to give everybody the exact same environment and experience is most valuable to me. 

It could be easier to create images and save them on reports.

Just improved development workflow, just quicker, like some better user experience creating the images for the Docker containers.

We have used it every day in my current company just to set up our environment for our build processes. We create a lot of labs.

We use the latest Docker version 4.22.

It is a very stable product.

It is extremely scalable. I would rate the scalability a ten out of ten.

The initial setup was very easy. I use it on-premises as well as in the cloud. So we use it in both places.

It's free, as far as I know. 

Docker is very reliable. It's easy to scale, and it's very stable.

Overall, I would rate the solution a nine out of ten. 

Our company uses the solution for the production environment, web projects, and hosting services. For example, we use it to host an NGINX box manager with  proxy, reverse proxy, and DNS server. 

We host a bunch of web services for clients and deploy both on-premises and on the cloud. Several of our development teams use the solution.

I also use the solution in my home lab. 

The solution is easy to deploy for clients so it saves a lot of hassle. 

The networking is an impressive feature. 

The volumes for persistent storage could be more user friendly right out of the box. 

I would like an option to just use it as local storage or some kind of NSF or CIF. Or to mount the volume straight to a Google Drive or through a particular cloud storage.

It's not that these things are impossible, but you have to do some extra work or configurations. 

I have been using the solution for three years. 

We use the solution mostly with Linux and it is stable.

We would like better stability with Windows containers. We need to use some kind of IAS to host them so support for these legacy projects would be a tremendous help. 

The solution is definitely scalable.

The documentation and community are good. I've never had a problem that I was unable to fix with a little bit of Google research. The official documentation is all you need to figure things out. 

I did not previously use another solution. 

The initial setup is straightforward. 

I handled implementation by myself and it was an easy process. 

There is definitely an ROI because the open-source version is free. 

The solution offers an open-source version that is free and includes a lot of functionality. 

When using the solution, don't rush or you might get overwhelmed. It takes a little bit of time to figure out how things work. Basic networking knowledge will save a lot of time. 

I rate the solution a ten out of ten. 

We use the tool for some of our services. We use it for containerization.

Load balancing features are valuable. We are leveraging this software for containerized services. We are using EKS for orchestration. We are leveraging almost all features. The solution helps save costs. We can know how much CPU memory is required so we can manage it accordingly.

Docker management is very difficult when we have a large number of nodes.

I have been using the solution for the last two years.

I rate the tool’s stability a six or seven out of ten.

I rate the tool’s scalability a six out of ten. We have more than 500 users. The tool is used extensively. We have plans to increase usage in the future.

We get good support from AWS.

The setup is straightforward. We need ten people for deployment, including managers, developers, and the IT team.

We can deploy the product ourselves.

We use the open-source version.

We use EKS for large applications. I will recommend the solution to others. If people want to leverage load balancing and containerized services with less CPU and load management, they can use Docker. We must pay for EKS based on the clusters and nodes we use. The price depends on the use case. Overall, I rate the solution an eight out of ten.

I'm using Docker local Kubernetes development. I'm building software that uses Docker for cloud and on-premises applications. I'm consulting for a company that provides an enterprise database solution built using Docker containers and Kubernetes, so everyone at the company is using Docker indirectly.

Docker packages up an application as a single item that you can then run without the need to install or configure it to work on any specific machine.

The command line interface could be more intuitive. I constantly struggle with it. 

I have been using Docker for three or four years.

Docker is stable.

Docker is scalable for the most part. But we have had issues where we ran out of disk space, and it doesn't work. When I say "disk space," I mean the space that Docker has allocated. Docker isn't scalable on its own, but it is if you're using it with something like Kubernetes.

Deploying Docker is pretty easy. 

An enterprise license costs $24 per user per month. For a team or a smaller license, it costs $9 or $5 per user.

I have looked at some of the newer ones that came out. We looked at Podman, but it didn't have the API that we needed. We also looked at Rancher. When I was at HPE, Docker started charging a license, so management decided to switch to something else because they didn't want to pay for it. After about six months and lots of wasted time and effort, they realized that it was worth paying for it. 

I rate Docker 8.5 out of 10.  From a business perspective, Docker is the de facto standard, and it's going to cost you less to use it than to try to find an alternative unless there's something that Docker can't do. It's going to cost you less because there are so many more free resources available. Your team can Google and find technical information much more easily about Docker than any other solution.

The advice I'd give to someone who is new to the solution is to find an online course that can walk you through Docker because it can be really confusing to get up to speed on it.