Docker vs. Google Cloud Run

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

Microservices and RestFul API application as it is fast and reliant. Seamless integration with event triggers such as pubsub or event arc, so you can easily integrate that with usecases with file uploads, database changes, etc. Basically great with short-lived tasks, if however, you have long-running processses, Cloud Run might not be idle for this. For example if you have a long running data processing task, other solutions such as kubeflow pipelines or dataflow are more suited for this kind of tasks. Cloud Run is also stateless, so if you need memory, you will have to connect an external database.

Incentivized

• 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

• multiple entry points to have a deployment ready (artifact repository, container repository, git actions)
• easy to use with other Google services with built in connectors for cloud sql and redis
• great in built logging and monitoring

Incentivized

• 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

Incentivized

• CLI is bloated and can be difficult to get started.
• The learning curve for configuration is higher than expected for a "simple" paradigm.
• Limited storage of any kind requires a significant rethink from stateful pipelines.

Incentivized

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

Incentivized

The UI/console is great... the documentation is top-notch for developers, but the CLI itself when you have to script around it is very complex and easy to forget some options... the downside of a generic command line client.

Incentivized

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

Incentivized

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

Incentivized

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.

Incentivized

The Goolge docs for their products as well as the UI is a lot nicer than AWS or Azure and in general I found it much easy to work with. We selected Google mainly because of startup credits and the support offered but can confidently say we would choose them again without that added perk in the future

Incentivized

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.

Incentivized

• 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.

• allowed for easy deployment
• allowed teams to get around our normal deployment controls and practices
• caused fuzziness about when to use which solution

Incentivized