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    Docker on CentOS 8

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    Deployed on AWS
    AWS Free Tier
    This product has charges associated with it for seller support. Experience the power of containerization with the Docker on CentOS 8 AMI, designed for seamless deployment in the AWS EC2 cloud. This pre-configured image provides a robust platform for running, managing, and scaling containerized applications, leveraging the stability and performance of CentOS 8. With Docker, developers can easily create, deploy, and share applications in any environment, ensuring consistent performance across development and production. Ideal for microservices architecture, DevOps workflows, and continuous integration/continuous deployment (CI/CD) pipelines, this AMI simplifies infrastructure management while enhancing application portability. Tap into the benefits of container orchestration, rapid deployment, and improved resource utilization, enabling you to accelerate your development cycles and respond quickly to market demands.
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    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.

    Try our most popular AMIs on AWS EC2

    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.

    Details

    Delivery method

    Delivery option
    64-bit (x86) Amazon Machine Image (AMI)

    Latest version

    Operating system
    CentOs 8

    Deployed on AWS
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    Pricing

    Docker on CentOS 8

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    Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time. Alternatively, you can pay upfront for a contract, which typically covers your anticipated usage for the contract duration. Any usage beyond contract will incur additional usage-based costs.
    Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator  to estimate your infrastructure costs.
    If you are an AWS Free Tier customer with a free plan, you are eligible to subscribe to this offer. You can use free credits to cover the cost of eligible AWS infrastructure. See AWS Free Tier  for more details. If you created an AWS account before July 15th, 2025, and qualify for the Legacy AWS Free Tier, Amazon EC2 charges for Micro instances are free for up to 750 hours per month. See Legacy AWS Free Tier  for more details.

    Usage costs (593)

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    • ...
    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

    Vendor refund policy

    The instance can be terminated at anytime to stop incurring charges

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    Usage information

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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

    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.

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    Accolades

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    Top
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    In Infrastructure as Code
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    100
    In High Performance Computing
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    25
    In Operating Systems

    Customer reviews

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    Sentiment is AI generated from actual customer reviews on AWS and G2
    Reviews
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    Overview

     Info
    AI generated from product descriptions
    Pre-configured Container Runtime
    Latest stable version of Docker included with pre-installed container management tools for immediate deployment without manual installation and configuration
    Operating System Foundation
    CentOS 8 base operating system providing stability and performance optimization for containerized workloads
    Security Implementation
    Security best practices implemented to safeguard containers and host environment with CentOS security features
    Container Orchestration Support
    Support for multi-container applications and container orchestration enabling microservices architecture deployment and independent service management
    Development and CI/CD Integration
    Compatibility with continuous integration and continuous deployment pipelines supporting automated build and release processes
    SELinux Security Enforcement
    SELinux enforcement enabled by default for mandatory access control and security policy enforcement
    Cloud-Init Automation Integration
    Built-in cloud-init support for automated provisioning workflows and instance configuration during deployment
    ENA Networking Support
    Enhanced Networking Adapter (ENA) support optimized for AWS EC2 high-performance networking capabilities
    Automatic Security Updates at Boot
    System synchronizes with upstream repositories during first boot to install newest security updates and package revisions
    Forward-Looking Development Platform
    Continuously delivered Linux distribution that tracks development path leading to future Red Hat Enterprise Linux releases
    In-Place Linux Distribution Conversion
    Convert2RHEL tooling enables in-place conversion of instances running on rpm-based Linux distributions to Red Hat Enterprise Linux 7 while preserving existing customizations, configurations, and preferences.
    Extended Security Support
    Extended Life Cycle Support (ELS) provides access to security patches and updates until June 2029, extending support five years beyond the CentOS Linux 7 end-of-life date.
    High Availability Support
    High Availability tooling and capabilities included for configuring and managing highly available infrastructure and applications.
    System Observability and Management
    Red Hat Insights integration provides monitoring, analysis, and remediation capabilities for security, stability, and performance issues across workloads, applications, and platforms.
    Cross-Infrastructure Consistency
    Unified operating foundation supporting consistent management and deployment across physical, virtual, private cloud, public cloud, and edge environments using standardized tools.

    Contract

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    Standard contract
    No

    Customer reviews

    Ratings and reviews

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    4.2
    34 ratings
    5 star
    4 star
    3 star
    2 star
    1 star
    44%
    56%
    0%
    0%
    0%
    14 AWS reviews
    |
    20 external reviews
    External reviews are from G2  and PeerSpot .
    Vinicius Canovas

    Container isolation has improved availability while resource tuning still needs attention

    Reviewed on Jun 27, 2026
    Review provided by PeerSpot

    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.

    VijaySoundaram

    Containerization has streamlined microservices delivery and ensures consistent hybrid deployments

    Reviewed on Jun 23, 2026
    Review from a verified AWS customer

    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?

    Hybrid Cloud

    If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?

    Luisfernando Benavides

    Rapid containers have transformed how I test microservices and reset databases on demand

    Reviewed on Jun 18, 2026
    Review from a verified AWS customer

    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?

    Private Cloud

    If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?

    IsaacHernandez

    Consistent containers have transformed QA workflows and make performance testing more reliable

    Reviewed on Jun 18, 2026
    Review from a verified AWS customer

    What is our primary use case?

    My main use case for Docker on CentOS  is that it can be very useful for QA and performance testing because it gives the team a consistent and repeatable environment. One scenario where I would use it is running automated API or UI test suites inside Docker  containers on a CentOS-based server. Instead of depending on each engineer or local setup, we can define the test environment with a Dockerfile and Docker  Compose, including the test framework, browsers, dependencies, environment variables, and reporting tools.

    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?

    The best features Docker on CentOS offers include stability, repeatability, automation, and performance control. I think that for testing teams, Docker makes it easier to package the full QA environment, run test suites in parallel, control dependencies, and reproduce performance results. It integrates well with CI/CD pipelines and allows teams to scale test execution without manually configuring each CentOS  server. My main recommendation is to use and maintain CentOS  stream versions, define resource limits, avoid running containers as root when possible, and include logs, reports, and monitoring as part of the implementation.

    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?

    I mentioned many benefits, but I have noticed some areas for 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?

    I have around ten and a half years of experience in my current field.

    What do I think about the stability of the solution?

    Docker on CentOS is stable, which is why we chose it, as it requires fewer resources than virtual machines.

    What do I think about the scalability of the solution?

    Docker on CentOS is highly scalable for our use cases. It allows us to move from a single machine or manually configured test execution to a more flexible model where we can run multiple containers in parallel, isolate workloads, and scale tests based on available CPU or memory.

    How are customer service and support?

    From our side, customer support has been great, especially when we encountered some issues.

    Which solution did I use previously and why did I switch?

    Before choosing Docker on CentOS, we evaluated options including virtual machines and manually configured setups.

    Other options we evaluated included Jenkins , manually configured CI/CD agents, and manual Kubernetes .

    How was the initial setup?

    For our private or hybrid deployments, we use various cloud providers, including AWS , Google Cloud , and Azure . My experience with pricing, setup cost, and licensing has generally been positive. The initial setup cost was more related to infrastructure, configuration, and monitoring. Once the Docker images and pipelines were standardized, the long-term costs became easier to manage because we spent less time fixing environment issues and more time executing tests. From a licensing perspective, Docker Engine on Linux is licensed under Apache, while Docker Desktop has a separate subscription. Overall, I would say that the pricing and licensing experience is reasonable, but it requires good governance to clarify the distinction between server-side Docker Engine usage and Docker Desktop usage, track who needs paid subscriptions, and include cloud compute, storage, networking, image registry, and monitoring costs.

    What about the implementation team?

    We did not purchase Docker on CentOS through the AWS Marketplace . In our case, Docker was deployed on our VMs and CentOS-based servers or cloud virtual machines, mainly as part of our internal infrastructure. Before using Docker on CentOS, we mainly relied on more traditional setups, such as dedicated virtual machines, manually configured Jenkins agents, and local development or QA environments with dependencies installed on the host machine. The primary reason we switched to Docker on CentOS was to reduce environment inconsistency. Different servers could have various versions, which led to issues during execution. Docker on CentOS provided us with a more repeatable and controlled execution environment.

    What was our ROI?

    For example, in one project, we saw several positive and measurable outcomes, especially around test execution stability and environment consistency. One major improvement was reducing the time spent preparing and fixing test environments. Before Docker on CentOS, a lot of time was lost because different machines had different versions of Node.js. After containerizing the test execution, the setup became much more predictable because the same Docker image was used across local, staging, and CI environments. In terms of outcomes, we saw improvements such as less troubleshooting time, faster onboarding, more stable automation, better parallel execution, and cleaner CI/CD execution logs. We now have logs, reports, and artifacts that are easier to collect from each container. A practical example is the regression testing, where previously, when a test failed, the team often had to check whether the problem came from the application, the server, the browser version, or the local configuration. With Docker on CentOS, we had a standardized execution layer that reduced false failures and made debugging faster. From a performance control perspective, Docker on CentOS also helped avoid overloading the host server by defining memory and CPU limits, allowing us to better understand whether a slow execution was caused by the application, the test framework, or the infrastructure. This made performance results more reliable.

    What's my experience with pricing, setup cost, and licensing?

    My experience with pricing, setup cost, and licensing has generally been positive. The initial setup cost was more related to infrastructure, configuration, and monitoring. Once the Docker images and pipelines were standardized, the long-term costs became easier to manage because we spent less time fixing environment issues and more time executing tests. From a licensing perspective, Docker Engine on Linux is licensed under Apache, while Docker Desktop has a separate subscription. Overall, I would say that the pricing and licensing experience is reasonable, but it requires good governance to clarify the distinction between server-side Docker Engine usage and Docker Desktop usage, track who needs paid subscriptions, and include cloud compute, storage, networking, image registry, and monitoring costs.

    Which other solutions did I evaluate?

    Before choosing Docker on CentOS, we evaluated options including virtual machines and manually configured setups.

    Other options we evaluated included Jenkins, manually configured CI/CD agents, and manual Kubernetes .

    What other advice do I have?

    I have some additional suggestions regarding my main use case or how Docker on CentOS fits into my testing workflows. My main suggestion for implementation is to use official Docker repositories and maintain CentOS version. Docker currently documents CentOS Stream  9 and 10 as supported for Docker Engine, while CentOS Linux 7 reaches end of life on June 30, 2024. Therefore, I would avoid using old CentOS versions for new implementation to avoid issues.

    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.

    Jprajapat Prajapati

    Building secure multi-tier projects has boosted learning but still needs stronger protection

    Reviewed on Jun 11, 2026
    Review from a verified AWS customer

    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.

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