Docker on Ubuntu 26 Hardened
Containerized workflows have simplified deployments and are saving significant development time
What is our primary use case?
For deploying projects, I can deploy multiple projects on Docker Hub which runs on Ubuntu machines or Linux servers. I can create images of Postgres database, Node.js projects, or Java projects, and deploy them directly from Docker via Docker YML file.
What is most valuable?
Docker provides comprehensive support for any deployment process, maintenance, or surveillance of any kind of project because it offers CLI and APIs, Docker Hub, and Docker Desktop client. I upload my project and create an image, then I can directly deploy this image. It provides a full environment for a machine to deploy any kind of service, whether Java or Node.js projects. Surveillance is very easy through viewing logs, threads, and the running status and health of my service or project. The entire procedure is time-saving and seamless.
Docker provides multiple kinds of support with well-detailed documentation and support available on Stack Overflow and Google. The support is seamless. If I am using Docker, I do not require any kind of support calls because all features and issues are publicly available on the internet. This provides a lot of resources to use and understand the service very well.
What needs improvement?
Connecting two containers to each other is very tricky and time-consuming for me as a developer. Docker provides some encapsulation between containers, meaning they are separated from each other, and I cannot directly connect two containers. Docker should provide AI support that is much better. I could directly command the service and any kind of process would be created. Docker should provide AI features for the deployment processes because I have to use commands repeatedly. I have to write multiple commands or remember multiple commands for the deployment process, but many manual things are required. If I use Docker on a machine, and I have installed Docker as a UI-based Docker, it should provide a chatbot or AI terminal feature. I could chat with AI and it should do the whole process, automating the procedure. I would not have to enter multiple commands to bring my service up, which would save significant time. Regarding logs, if I encounter a failure or attack, I have to debug manually on the terminal, filtering through multiple logs repeatedly. Docker should provide an AI service so I can directly pull the logs and find the time frame, which would save time and allow me to respond as soon as possible.
For how long have I used the solution?
I have used Docker on Ubuntu 20.04 LTS for around two years, including my internship.
What do I think about the stability of the solution?
Docker is very stable and scalable. I understand it supports 99.9% uptime, which is impressive. I have never had an incident where Docker has crashed.
What do I think about the scalability of the solution?
Docker on Ubuntu 20.04 LTS is very scalable. It supports all kinds of services and all kinds of service providers.
How was the initial setup?
The setup is very straightforward. I only have to run three commands and Docker is installed directly via terminal.
What was our ROI?
Docker on Ubuntu 20.04 LTS provides absolute value for money. It saves a lot of time for a DevOps engineer and a simple developer. If a CI/CD pipeline is created by a DevOps engineer, a developer can directly use Docker and bring their service up in a couple of minutes. Without Docker, I would have to hire a DevOps engineer to deploy services. Docker makes the deployment process seamless and saves significant energy and time.
Which other solutions did I evaluate?
I can compare Docker on Ubuntu 20.04 LTS directly with Kubernetes or any other deployment service provider. Kubernetes is a very good competitor of Docker. Both are very mature services, but Docker is lightweight while Kubernetes is very heavy to use and very expensive. Docker provides features that are very straightforward for deployment, image creation, image pulling, running, and logging. Kubernetes requires creating pods and pulling services, configuring them with the server, and installing components that require a heavy machine to handle Kubernetes itself. Docker is very lightweight and I can use it anywhere, including on small machines.
What other advice do I have?
I can configure other kinds of services from AWS, Azure, and Google. I can directly connect a webhook to a system where Ubuntu is used with Docker on Ubuntu 20.04 LTS, and create CI/CD pipelines locally or on a server. I can push the code and automatically the webhook triggers, images are created, pulled, deployed, and running. Ubuntu has provided clear deployment processes since the early twenties. Everything is automated and I do not have to configure every time or update the environment variables. I only have to create deployment.yml files that directly pull my code, add the environment variables, and run automatic systematic commands. The image is built, the database is connected, and my service is up and running. The configuration of automatic CI/CD pipelines via Docker on Ubuntu 20.04 LTS in Ubuntu servers is very seamless.
Regarding licensing, I have independently used Docker without needing any kind of license because a single developer can use Docker directly without requiring any licensing. However, in corporate deployment, Docker on Ubuntu 20.04 LTS does require a license, though I do not have much information about licensing for the organization level.
In my organization's case, I purchased Ubuntu machines from marketplace providers such as Contabo or other service providers offering servers with Ubuntu operating systems. I installed software to make the deployment process seamless, including Docker on Ubuntu 20.04 LTS. I configured Docker, NGINX, and local work time items within Docker itself. I can install NGINX in Docker and Node.js in Docker, create images of my project, and deploy them directly. Locally, I use Ubuntu as a primary machine because I want Linux commands. Ubuntu is a very good OS as it provides sudo commands and multiple other commands to directly view logs, bring up services, create images, and configure service networking. Ubuntu is a very terminal-friendly OS that directly supports Docker integration. I can directly install Docker on Ubuntu 20.04 LTS in the terminal and pull images from the local machine for any kind of service such as Microsoft or Ubuntu or Mac. I build my project and the service itself in Docker Hub, then I can go to Ubuntu and pull the images from the local machine and deploy them directly in Docker on Ubuntu 20.04 LTS.
I provided a review rating of nine out of ten for Docker on Ubuntu 20.04 LTS.
Which deployment model are you using for this solution?
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
Cross‑OS containers have unified our secure AI workflows and support hybrid deployments
What is our primary use case?
We are working on two different deployments, one based on WSL, which is like Windows WSL, and the other one is Ubuntu. We have a local setup deployment that basically serves as a local AI inference agent based on NVIDIA GPUs, and we use Kubernetes with Docker.
What is most valuable?
First of all, since it is cross-OS, it is very easy for us to do small deployments on edge computers that are using Windows with Ubuntu, and then do the full production on Linux local servers. We use this frequently, and they have made a lot of progress lately with their cross-integrations and WSL integrations and Kubernetes.
A second thing that we really appreciate is that it is very easy for people to understand because it reminds them of the Git workflow, so all the image management is so convenient that people feel they are working with Git. Here they are not managing code; they are managing images.
Since we are doing a cross-compile, we want to decouple it and basically have a constant image for our environment. We are building OS inside OS, and we are using this feature. It allows us to create an independent cross-compile image that is basically decoupled from the host.
For us it is a small tool; it is not a big investment, so we are not tracking the ROI of the product directly, but I can tell you that it gives a lot of useful features and overall the ROI is worth it. Especially, now they have this MCP integration and all management of all MCP servers is in this new feature, and it basically allows you to deploy MCP servers securely because each MCP server is running in a separate Docker. In combination with all those features, the ROI is good.
What needs improvement?
I think the licensing is still confusing. Since it is so easy to install, the licensing remains confusing regarding what is for enterprise and what is for personal use. Basically, you can install it, but then you get a message that this is personal mode, and people are afraid whether they stand with the license or not. The licensing is a little bit confusing.
A second thing is that there is this Docker Hub, and I don't know why, but people say that they have issues with the images that they download there. Personally, we don't really use Docker Hub.
For how long have I used the solution?
We have been using this for many years, maybe five years.
What do I think about the stability of the solution?
In combination with Kubernetes, we don't see any limitations. There is now a composer, so sometimes people use composer, and many now use image composer images.
What do I think about the scalability of the solution?
In combination with Kubernetes, we don't see any limitations.
How are customer service and support?
I don't have something special to report, but I can tell you that it passed our internal CISO review. We are working with top secret data, and we have a Common Criteria regulation that we need to comply with. From a security specification standpoint, it was accepted.
Which solution did I use previously and why did I switch?
I am not sure of its competitors. I switched from working at Intel to a new company. At Intel, we had another solution; I don't remember the exact name, but it was more legacy, and everybody wanted to switch to Docker. It was something parallel to Docker, but eventually it was considered legacy.
How was the initial setup?
It is very easy; it is one of the easiest setups.
What was our ROI?
For us it is a small tool; it is not a big investment, so we are not tracking the ROI of the product directly, but I can tell you that it gives a lot of useful features and overall the ROI is worth it. Especially, now they have this MCP integration and all management of all MCP servers is in this new feature, and it basically allows you to deploy MCP servers securely because each MCP server is running in a separate Docker. In combination with all those features, the ROI is good.
What's my experience with pricing, setup cost, and licensing?
I am not paying for it, but I know that there was no issue. I don't remember the exact number, but comparing it to other costs that we have in other tools and especially in AI, it is reasonable. It is not something that is preventing the purchase.
Which other solutions did I evaluate?
At Intel, we had another solution; I don't remember the exact name, but it was more legacy, and everybody wanted to switch to Docker.
What other advice do I have?
We have a very high bar because we are developing a security product, so it is the highest bar that can be.
Basically, we have here two types of environments. One environment is top secret data that cannot leave a special network that is only inside the organization; we cannot use any cloud provider for it, so all this setup is running locally. We have the same images from an infrastructure perspective that is handling other projects that do not have such secure data; their data is less secure. It is still secure, but it is at a level that allows us to use cloud. It is not external cloud; it can be AWS or Azure, but still, it is allowed. The fact that we are using this hybrid environment means we are reusing the same infrastructure for different data type classifications.
We never reached the point that we need to search in community forums for help. My overall rating for this product is 9 out of 10.
Containerization has streamlined deployments and supports diverse monitoring and web workloads
What is our primary use case?
My main use case for Docker on Ubuntu 20.04 LTS is to run Docker containers.
A quick specific example of how I use Docker containers in my environment includes utilizing them for all kinds of applications, everything from Nginx to ForgeRock, and various tooling and monitoring solutions such as Prometheus and Grafana.
What is most valuable?
The best features Docker on Ubuntu 20.04 LTS offers are excellent for using official Docker repos.
Docker on Ubuntu 20.04 LTS has positively impacted my organization as it provides a good way to run our toolsets and applications.
The positive impact of Docker on Ubuntu 20.04 LTS definitely makes deployments easier and improves efficiency, which aligns with the main business case for the product.
What needs improvement?
Docker on Ubuntu 20.04 LTS can be improved, particularly as security features can always be enhanced, and the configuration is somewhat fragmented with different configuration files that can sometimes be cumbersome.
For how long have I used the solution?
I have been using Docker on Ubuntu 20.04 LTS for seven to eight years.
What do I think about the stability of the solution?
Docker on Ubuntu 20.04 LTS is stable.
What do I think about the scalability of the solution?
The question of how Docker on Ubuntu 20.04 LTS's scalability applies does not seem relevant when we are talking about a single Docker instance.
How are customer service and support?
I have never had to use customer support for Docker on Ubuntu 20.04 LTS.
Which solution did I use previously and why did I switch?
I did not previously use a different solution before Docker on Ubuntu 20.04 LTS.
How was the initial setup?
My experience with pricing, setup cost, and licensing for Docker on Ubuntu 20.04 LTS is quite good as it is all official on Docker.
What was our ROI?
I cannot say I have seen a return on investment while using Docker on Ubuntu 20.04 LTS, as it is the usual use case for Docker and containerization, which is already a standard way of working.
What's my experience with pricing, setup cost, and licensing?
My experience with pricing, setup cost, and licensing for Docker on Ubuntu 20.04 LTS is quite good as it is all official on Docker.
Which other solutions did I evaluate?
I did not evaluate other options before choosing Docker on Ubuntu 20.04 LTS.
What other advice do I have?
I would rate Docker on Ubuntu 20.04 LTS a nine out of ten.
I give it a nine because there is always room for improvement, so I would not give any product a perfect ten.
Regarding Docker on Ubuntu 20.04 LTS's AI capabilities, I think its governance and security work quite well in terms of namespace isolation; the security is quite strong, but if you want something like image vulnerability scanning, it does not have anything built in, so you have to rely on third-party toolsets, and secret management is a bit of a downside.
Docker on Ubuntu 20.04 LTS is pretty accurate regarding its AI capabilities and the accuracy and reliability of output.
My advice to others looking into using Docker on Ubuntu 20.04 LTS is that if you are not using it, then try it. My overall review rating for Docker on Ubuntu 20.04 LTS is nine.