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 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.

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 work with containers for forecasting. 

The solution's most valuable feature is the Dockerfile, which makes the life of developers easy. Developers get a real understanding of container creation. 

I have encountered network issues while connecting with microservices. I want to optimize the application layers over the bucket. It should also have better documentation. 

I have been working with the solution for seven years. 

I rate the tool's scalability a nine out of ten. 

We solve issues using the documentation. 

Neutral

Docker's implementation is straightforward. However, it can get a bit complicated when you are doing sophisticated implementation. 

We have seen ROI with the tool's use. 

Docker's price is good. 

I rate the product an eight out of ten.