Docker vs. Red Hat Advanced Cluster Management for Kubernetes

You are going to be able to find the most resources and examples using Docker whenever you are working with a container orchestration software like Kubernetes. There will always some entropy when you run in a container, a containerized application will never be as purely performant as an app running directly on the OS. However, in most scenarios this loss will be negligible to the time saved in deployment, monitoring, etc.

Incentivized

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Well suited for - Large-scale Edge deployments of OpenShift instances. Policy-based consistency for all workloads is Less appropriate for - Small-scale deployments. Stand-alone deployments of K8s clusters. Deployments in the same data center.

• Packaging of application to limit the space occupied
• Ease of running the application
• Provide multiple ways to handle the application issues and integration of different components like pipeline, ansible, terraform etc

• Continuous deployment of other OpenShift instances.
• Controls clusters and applications from a single console.
• Built-in Security & compliance.

• Docker hub image retention policy can be relaxed
• Docker hub policies can be more developer friendly
• Docker CLI help section can be improved
• Image and container storage (local) management can be optimized

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• Initial deployment of the ACM itself needs to be made easy.
• Dependency on the Software versions of underlying open shift workloads during upgrades.
• LCM of ACM itself.

I have been using Docker for more than 3 years and it really simplifies the modern application development and deployment. I like the ability of Docker to improve efficiency, portability and scalability for developers and operations teams. Another reason for giving this rating is because Docker integrates CI/CD pipelines very well

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Haven't seen any outages, fatal/unrecoverable errors in my usage so far. Enough said.

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Docker Desktop. The CPU high usage is a known issue. Needs fixing. Otherwise, it is great overall. Would not use anything else still.

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The reason why we are still using Docker right now is due to that is the best among its peers and suits our needs the best. However, the trend we foresee for the future might indicate Amazon lambda could potentially fit our needs to code enviornmentless in the near future.

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I have also used TNA by Google Cloud, but that is not mature enough as ACM. Right now, ACM is the best choice as a cluster manager for private cloud data centers.

It is the only tool in our toolset that has not [had] any issues so far. That is really a mark of reliability, and it's a testimony to how well the product is made, and a tool that does its job well is a tool well worth having. It is the base tool that I would say any organisation must have if they do scalable deployment.

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• Reduces the number of virtual machine which impacted our quarterly billing
• Using docker with proxy we run multiple application on same port on same host.
• impact on billing is we have to provide docker training to the people who are working on it.

• Reduced the deployment duration of individual nodes by 50%.
• Acts as a central manager for all the clusters.
• Provides a lot of infrastructure options (storage, networking, etc) to build instances of your choice.