Overview

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This is a repackaged open source software wherein additional charges apply for extended support with a 24 hour response time.
Docker on CentOS 8 provides a robust and flexible platform for developing, shipping, and running applications in lightweight containers. This AMI enables users to quickly deploy Docker without the hassle of manual installation and configuration, ensuring a seamless operational experience.
Features:
- Optimized for CentOS 8: Pre-configured to leverage the stability and performance of CentOS 8.
- Latest Docker Version: Includes the latest stable version of Docker, ensuring you have access to the newest features and security enhancements.
- Pre-installed Container Tools: Comes with essential tools for managing containers, facilitating easy deployment and orchestration.
- Enhanced Security: Implements security best practices to safeguard your containers and the host environment.
- Customizable Environment: Easily customize the Docker environment to meet specific development or production requirements.
Benefits:
- Rapid Deployment: Launch your containerized applications quickly and efficiently, reducing time-to-market for new deployments.
- Simplified Management: Benefit from an easy-to-use interface and command-line tools for container management, minimizing administrative overhead.
- Scalability: Effortlessly scale applications as demand grows, leveraging Docker's inherent capabilities for load balancing and resource allocation.
Use Cases:
- Microservices Architecture: Ideal for deploying microservices, enabling you to manage each service independently while maintaining communication between them.
- Development and Testing Environments: Quickly spin up containers for development and testing, ensuring consistency across different stages of deployment.
- CI/CD Pipelines: Integrate with continuous integration and deployment pipelines to automate the build and release processes.
Harness the power of containerization on CentOS 8 with this pre-packaged Docker AMI, designed to enhance your application lifecycle management while delivering performance and reliability.
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Highlights
- The Docker on CentOS 8 AMI offers a robust environment for deploying containerized applications seamlessly. This pre-configured image empowers developers to streamline the setup process by eliminating the need for manual installations. By leveraging Docker's capabilities within the CentOS 8 ecosystem, users can easily manage, scale, and orchestrate container workloads, enhancing application deployment efficiency while ensuring consistency across development and production stages.
- With Docker on CentOS 8, teams can take advantage of CentOS's stability and security features alongside Docker's powerful isolation capabilities. It supports various programming languages and frameworks, making this AMI ideal for development and testing environments. Enterprises can utilize this solution to create microservices architectures, ensuring that each service remains resilient and independently deployable while allowing for rapid iteration and deployment cycles.
- This AMI is particularly well-suited for organizations seeking to integrate DevOps practices. By facilitating continuous integration and delivery (CI/CD) pipelines, Docker on CentOS 8 enhances collaboration between development and operations teams. Additionally, it supports multi-container applications, allowing businesses to build complex systems that are easy to maintain and scale, ultimately leading to reduced time-to-market for new features and applications.
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Pricing
- ...
Dimension | Cost/hour |
|---|---|
t3a.micro Recommended | $0.07 |
t2.micro | $0.21 |
t3.micro | $0.07 |
c5n.18xlarge | $4.48 |
c5ad.xlarge | $0.28 |
d3.8xlarge | $2.24 |
r7iz.12xlarge | $3.36 |
c7i.xlarge | $0.28 |
r6idn.8xlarge | $2.24 |
r5.metal | $3.36 |
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The instance can be terminated at anytime to stop incurring charges
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Delivery details
64-bit (x86) Amazon Machine Image (AMI)
Amazon Machine Image (AMI)
An AMI is a virtual image that provides the information required to launch an instance. Amazon EC2 (Elastic Compute Cloud) instances are virtual servers on which you can run your applications and workloads, offering varying combinations of CPU, memory, storage, and networking resources. You can launch as many instances from as many different AMIs as you need.
Version release notes
System update
Additional details
Usage instructions
Once the instance is running, connect to it using a Secure Shell (SSH) client with the configured SSH key. The default username is 'centos'.
OS commands via SSH: SSH as user 'centos' to the running instance and use sudo to run commands requiring root access.
Run docker test with:
sudo docker run hello-world
Resources
Vendor resources
Support
Vendor support
Email support for this AMI is available through the following: https://supportedimages.com/support/ OR support@supportedimages.com
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
Standard contract
Customer reviews
Container isolation has improved availability while resource tuning still needs attention
What is our primary use case?
I have been using Docker on CentOS for five years.
I do not have a main use case for Docker on CentOS , just support tickets regarding the application on Linux.
An example of a support ticket I have handled involves pods that stop responding on an application and operational system impacted by Docker uses regarding CPU or memory resources.
Most of the time, I support Docker on CentOS, not the pods or applications that run inside these pods. I am responsible for the full high availability of servers that support or host Docker . Therefore, I have to ensure that everything is running fine and quickly on the host side.
What is most valuable?
The best features Docker on CentOS offers, from my perspective as someone responsible for high availability and server health, are the ability to work with containers and pods to run applications and set the best resources for the pods. I can isolate and ensure that everything is running as quickly and efficiently as possible.
Docker on CentOS is the main available solution on the market and is highly used all over the world. It is especially great for hosting applications and also for maintaining and developing these applications in isolated environments. For example, everything that will run in a pod will be handled in any of these pods in the replication and creation of these pods in any of the environments, making the whole infrastructure not only more secure but providing indescribable high availability for applications and customers based on Docker appliances.
Docker on CentOS has positively impacted my organization by helping to change and modify anything regarding applications that have to be available for the customer quickly, and it is also for those that have to be created in the fastest way. For example, Docker can create different specifications for different applications using only one host. It assures that we will not have high costs and will be great especially for the team responsible for the infrastructure as well as for the developers.
What needs improvement?
Docker on CentOS can be improved by ensuring that we are using the right image available around the world and choosing only the specific needs for applications, the right amount of CPUs and memory, and the isolation of the problems that we can have on production. We can use one host to have different scenarios in a fast and easier way than we would use in the old world or with on-premises virtual machines or physical hosts, which helps us to decrease the cost.
For how long have I used the solution?
I have been using Docker on CentOS for five years.
What other advice do I have?
I do not see any improvements needed for Docker on CentOS, aside from what I have already mentioned.
My advice for others looking into using Docker on CentOS is to always use a Linux version that has a support team or a community who supports the version regarding the kernel and especially the CVE features regarding vulnerabilities.
I do not have any additional thoughts about Docker on CentOS before we wrap up.
I would rate this review a 7.
Containerization has streamlined microservices delivery and ensures consistent hybrid deployments
What is our primary use case?
I have been working as a senior middleware engineer and DevOps engineer for the last 17 years, where I have used Docker on CentOS in various multi-level, multi-cloud platforms like AWS and Azure , and for Fortune 500 companies such as Charter, Mastercard, Cardinal Health, and Dell. Currently, I'm involved in the containerization of Spring 3.x, Java-based applications, and building microservices for distributed applications using Docker on CentOS . The containerization we are doing was initially using ECR, which has now migrated to EKS, and I am creating the CI/CD pipeline with GitLab , Docker builds and Argo CD deployments. Our architecture includes an 80-plus pods cluster, scaling from 2 to 85, with a target of zero downtime and 140 TPS. Docker on CentOS, being lightweight and stable, integrates well with the Linux kernel, providing minimum overhead and cost efficiency, which is crucial for resource-constrained environments.
What is most valuable?
The capabilities of Docker on CentOS that I have found the most valuable include its use for Spring-based applications, which significantly enhance the value I derive from it. Docker on CentOS is particularly effective for building distributed applications and microservices. Deployments are smooth and easy, and the integration with Kubernetes is seamless. I have successfully managed 80-plus pods clusters, scaling from 80 to 85 with 140 TPS without encountering any issues. Docker on CentOS's lightweight nature allows for flawless development across environments such as dev, stage, and prod.
From my perspective, the experience with the deployment of Docker on CentOS is quite positive, especially for the CI/CD pipeline. The architecture overview includes the use of a Git repository and GitLab CI, which facilitates the Docker build for our Spring 3.x Java applications.
What needs improvement?
I have faced challenges with the end-of-life cycle of CentOS since 2021-2022, security updates, network complexity with multi-node DNS issues, storage persistence pain points with EBS and EFS, and resource management before the Kubernetes abstraction.
For how long have I used the solution?
I have been working with Docker on CentOS for a very long time, starting with Docker Swarm and Docker, specifically for this current project itself.
What do I think about the stability of the solution?
While the end-of-life for CentOS was noted, the overall persistence and network performance, including firewall functionality, were commendable. Earlier issues with out-of-memory crashes were resolved with proper sizing adjustments, and overall, I experienced no conflicts during updates, maintaining the 140 TPS targets effectively.
What do I think about the scalability of the solution?
Regarding the scalability of Docker on CentOS, I initially built the Docker containers and moved them to Kubernetes, where my scaling efforts were focused.
Once Docker on CentOS is dockerized and deployed in Kubernetes, it scales effectively by meeting the target of 140 TPS with an SLA of one second for three REST endpoints.
How are customer service and support?
I do not often communicate with the technical support of Docker on CentOS, as I haven't found the need; the documentation has been sufficient.
The documentation for Docker on CentOS is excellent; I find answers to my questions regarding the Docker daemon and network configuration issues quickly and efficiently. The information available for storage and security has been helpful, despite some challenges in those areas along with conducting DR exercises.
How was the initial setup?
The steps I needed to take when setting the solution up involved starting with dockerizing the application on CentOS, primarily with versions 7/8. I pulled the Docker image after setting up CentOS and created user groups to prevent overwriting. Using the daemon setup, I configured the firewall and created the Docker file. My workflow continued with using Maven version 3.8 and integrating it with Eclipse to enhance several endpoints. This included updating PL/SQL procedures and aiming for an SLA of less than one second, with a multi-stage deployment reflecting the expanding functionality of our application.
From my perspective, the experience with the deployment of Docker on CentOS is quite positive, especially for the CI/CD pipeline. The installation is straightforward with easy updates and configurations, including starting Docker groups and handling the daemon without challenges. I utilized a JSON-based setup, firewall setups were simple, and the multi-stage deployments were effective. My integration efforts with Maven and Eclipse were also seamless, leading to a flawless push to ECR.
What other advice do I have?
Docker on CentOS is utilized in a hybrid setup within my organization; starting on-premises with CentOS, our architecture evolved to the cloud. I began with building everything locally, then transitioned to development environments, eventually versioning the applications and pushing to ECR, allowing flexibility whether on local or cloud resources.
In terms of reliability and stability, I find Docker on CentOS to be dependable, with good kernel support and daemon stability. I would rate this solution an 8 out of 10.
Which deployment model are you using for this solution?
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
Rapid containers have transformed how I test microservices and reset databases on demand
What is our primary use case?
My main use case for Docker on CentOS is for microservices, and I have been using Docker mainly for development and testing environments.
The most common use case for me with Docker on CentOS is to spin up a SQL container, as it is much faster than installing and configuring the database, and it keeps the environment clean.
A typical scenario with Docker on CentOS is when I use a container locally for testing. I usually create a new MySQL container for that.
What is most valuable?
I think that the container Docker on CentOS is the most beneficial because I am able to create a new container locally very easily.
I believe that the ease of container creation with Docker on CentOS helps my workflow, as it allows me to create testing environments locally.
It is especially useful when you need to test different database versions or reset the state quickly without affecting anything else on the system with Docker on CentOS.
Docker on CentOS has positively impacted my organization by being much faster than installing and configuring the database directly on the machine.
What needs improvement?
So far, I do not have problems with Docker on CentOS.
For how long have I used the solution?
I have been working in my current field for 20 years.
What do I think about the stability of the solution?
I am satisfied with Docker on CentOS in this aspect.
How was the initial setup?
I am able to create a database container with Docker on CentOS in minutes. If I want to create a testing environment, the time is approximately one day.
Which other solutions did I evaluate?
I recommend searching on the internet for the best practices for setting Docker on CentOS containers.
What other advice do I have?
Docker on CentOS deserves a perfect score of 10 out of 10. It is more efficient nowadays than in the past, which makes Docker on CentOS deserve a perfect score for me. Docker on CentOS is easy to use. Regarding Docker on CentOS's AI capabilities, I think security is important. When using Docker on CentOS's AI capabilities, I find it very accurate and reliable. I would rate this review a 10.
Which deployment model are you using for this solution?
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
Consistent containers have transformed QA workflows and make performance testing more reliable
What is our primary use case?
I decided to use Docker on CentOS for my testing environments because, from a performance perspective, Docker helps reduce setup time and improve test execution consistency. For example, we can run tests in parallel containers, isolate services, and compare results more reliably between local, staging, and CI environments. However, it is important to monitor CPU, memory, network usage, container startup time, and disk input and output because poor configuration can create false performance issues that are not related to the application itself.
What is most valuable?
Automation and performance control specifically have helped my team mainly by making execution more predictable, repeatable, and easier to scale. For example, in a recent project, we needed to run automated regression tests against multiple environments. Before using Docker on CentOS, every machine or server had small differences, such as different node versions, browser versions, drivers, dependencies, or missing packages. That created false failures, wasting time debugging the environment instead of the application. By moving the test execution into Docker containers and CentOS, we packaged the full test environment: framework, dependencies, browser configuration, test script, reporting tool, and environment variables. This made the automation much more stable, so every execution used the same baseline. An example of a challenge it solved was an unstable regression execution where tests were failing randomly because the host machine was under heavy load, especially when several suites were running at the same time. After containerizing the execution, separating services, and monitoring resource usage, we gained better visibility into bottlenecks, enabling us to identify when a container needed more memory, when parallel execution was too aggressive, or when the application response time was actually slow. The main benefit was that Docker on CentOS gave us a controlled testing layer. Automation became easier to maintain, performance results became more trustworthy, and at the end of the day, the team spent less time fixing environment issues and more time improving test coverage and product quality.
Docker on CentOS has positively impacted my organization because I know that many projects are using Docker on CentOS. The impact is positive because it provides us with a more stable and repeatable way to run automation, testing, and supporting services. One of the biggest benefits has been environment consistency. Before using Docker on CentOS, different servers or local machines could have various versions of Node.js, Java, browsers, drivers, or system packages, causing false test failures and making debugging slow. With Docker on CentOS, we were able to package the required dependencies into images, so our execution was the same.
What needs improvement?
Some needed improvements include clearer installation and version compatibility. Docker's official documentation currently lists maintained CentOS Stream 9 and 10 as supported for Docker Engine. Teams using older CentOS versions need to be careful with compatibility and support planning, so clearer migration guidance for older CentOS versions would be beneficial. Another area is in troubleshooting; it could be made easier. When Docker fails due to networking permissions, CI, Linux storage driver, or daemon configuration, the error messages can be too technical. A guided diagnostic tool for CentOS would be very useful, checking repositories, kernel compatibility, firewall rules, the overlay, Docker daemon status, and container resource usage. Additionally, performance visibility could be improved as Docker already provides resource control, but for QA and performance testing, better built-in dashboards for CPU, memory, disk, input/output, network latency, container startup time, and test execution would help in understanding performance issues. Security defaults could be stronger and easier to apply because features like rootless mode are available, but clearer recommendations and simpler setup flows for running containers with least privilege, managing secrets, scanning images, and avoiding risky volume permissions are needed. Lastly, container integration and delivery in QA could be better documented, as Docker works well with automation pipelines, but more official examples for CentOS-based Jenkins , GitHub Actions , self-hosted runners, GitLab , browser testing, API testing, and performance testing documentation would help QA teams adopt it faster.
For how long have I used the solution?
What do I think about the stability of the solution?
What do I think about the scalability of the solution?
How are customer service and support?
Which solution did I use previously and why did I switch?
Other options we evaluated included Jenkins , manually configured CI/CD agents, and manual Kubernetes .
How was the initial setup?
What about the implementation team?
What was our ROI?
What's my experience with pricing, setup cost, and licensing?
Which other solutions did I evaluate?
Other options we evaluated included Jenkins, manually configured CI/CD agents, and manual Kubernetes .
What other advice do I have?
I have one suggestion for teams implementing Docker on CentOS. It may be best to start with a simple Docker image for the test framework, then add Docker Compose if multiple services are needed. After that, I recommend defining the CPU and memory limits, collecting logs and reports from each container, and integrating the execution into the CI/CD pipeline because that workflow creates a clean and scalable foundation for both automation and performance.
My advice for others looking into using Docker on CentOS is to start simply but implement it with good governance from day one. Docker can bring significant value, but only if the team standardizes how images contain logs, resources, and security are managed. The most important recommendation is to use a supported CentOS version, standardize your images, integrate with CI/CD early, control CPU and memory usage, monitor container metrics, and think about security from the beginning.
Regarding Docker on CentOS's AI capabilities, I think governance and security are critical. Docker on CentOS can serve as a strong foundation for AI workloads because it provides isolated, repeatable, and scalable environments. However, AI use cases usually involve sensitive data, dependency models, credentials, and automated decision-making, so organizations need strong controls around image creation, access permissions, secrets, and vulnerability scanning. From a governance perspective, I recommend clear standards for approved base images, image versioning, access control, and audit logs. From a security perspective, I suggest running containers with less privilege, avoiding root execution when possible, scanning images, generating S-BOMs, and keeping the CentOS host updated. Docker supports rootless mode to reduce risks from the Docker daemon and container runtime, while Docker Scout can analyze images using S-BOMs and vulnerability data. It is also essential to be cautious with CentOS version support, as Docker Engine documentation currently lists maintained CentOS Stream 9 and 10 as supported. Using outdated CentOS versions creates governance and security risks. Overall, I view Docker on CentOS as a positive foundation for AI and automation workloads, provided it is implemented with strong governance, controlled images, secure measures, vulnerability scanning, resource limits, and clear ownership of the container.
Regarding Docker on CentOS's AI capabilities, I see accuracy and reliability as different aspects. Docker on CentOS itself does not make an AI model more accurate; accuracy depends on the model, training data, prompts, configuration, and validation process. However, Docker on CentOS can strongly improve the reliability and repeatability of the output by providing a controlled environment where the same model, dependencies, libraries, and resource limits are used each time. In an AI testing or automation scenario, Docker on CentOS can help ensure that the same model version, Python libraries, CUDA, or CPU configuration, and environment variables are used across local, staging, and CI environments, reducing inconsistent behavior caused by dependency differences. Additionally, the Docker model runner also supports managing and running AI models locally, configuring model parameters, and displaying prompt response details, which can help with traceability and repeatable validation. From a QA perspective, I would not trust AI output solely because it runs in Docker on CentOS. I would still recommend automation, automated validation, expected output checks, prompt versioning, model versioning, logs, and human review for critical cases, along with monitoring for hallucination or unstable responses. Overall, I would say that Docker on CentOS is reliable as an execution platform for AI workloads, especially when properly configured, but the accuracy of the AI output must be measured separately through testing benchmarks and business validation. Since Docker Engine officially supports maintained CentOS Stream 9 and 10, I would also avoid outdated CentOS versions for AI workloads that require strong reliability and security.
Building secure multi-tier projects has boosted learning but still needs stronger protection
What is our primary use case?
My main use case for Docker on CentOS is building a four-tier project on my PC.
I use Docker on CentOS by installing Docker to manage the Docker files and also to manage my applications, websites, and MySQL from CentOS .
What is most valuable?
The best features Docker on CentOS offers in my experience are its speed and smooth operation, along with the fact that there is no need to add a repository, and it is free. I can use the repository to download any repository, which is why I use those features. CentOS is free, and I have used it to practice for my exams and to build my four-tier project.
What needs improvement?
I chose a seven out of ten because Docker on CentOS is very fast and smooth. However, it also needs to improve its security, upgrade the packages, and fix bugs, which is why I deducted three points. It should also provide more updatable features.
Regarding Docker on CentOS's AI capabilities, if I am using it for a banking project, I think we need higher security to prevent hacking and direct attacks on servers. That is why we need to upgrade security on CentOS 9 and develop CentOS 10, an upgraded version, for more feature support and ease of use.
I think it would be very helpful to bring in AI to know more about CentOS 9 and the hidden features it offers.
For how long have I used the solution?
I have been using Docker on CentOS for the past two years.
What other advice do I have?
Docker on CentOS has positively impacted me by allowing me to upgrade to CentOS 9 to build more security and also manage subscriptions, which sometimes are free but not for organizations. I need to keep the subscription to access more packages and features in the subscription manager, as they do not always provide everything for free.
Docker on CentOS is deployed in my organization using both private and public clouds, as we normally use CentOS 9 for the UAT servers and proxy servers. We are using AWS and Azure for our public and private cloud deployments. I purchased Docker on CentOS through the AWS Marketplace .
I recommend that others looking into using Docker on CentOS consider that I have also recommended CentOS 9 to my colleagues for learning for their exams at no cost to build their skills.
It is important to build on CentOS and to bring in new versions, such as CentOS 9 and CentOS 10, for higher capabilities and features. I would rate Docker on CentOS overall as a seven out of ten.