CoreOS rkt / Container Linux (project ended) vs. Google Cloud Run

CoreOS rkt is well suited for any development environment where operating systems and hardware are not homogeneous. CoreOS rkt allows us to write code on one machine with the confidence that it will work on any other. This has been immensely helpful as our developers are often switching to the latest and greatest machines and operating systems. CoreOS rkt is less suited for environments that are not Software as a Service. There is often no need to bring the entire developer environment and associated dependencies when delivering a one time product. In these environments CoreOS rkt just adds unneeded overhead.

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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.

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• Running a secure container without messing up with low-level details
• Very clear and straightforward approach to building a container
• A way to go for new projects thinking of containers
• Comprehensive and well-written documentation compatible with UNIX keep it simple way of thinking

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• Auto scaling is the best one
• provide direct VPC connectivity and rigid network
• Cloud SQL and Pub/Sub services
• Handling latency issues

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• Market share, it's often very difficult to find new talent who use CoreOS rkt.
• Lack of wow features, CoreOS rkt doesn't necessarily offer any immediate advantages over other container solutions.

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• The UI can be made simpler. Currently the UI is bloated and it takes time to find out what you want
• More integrations with container registry providers (ECR, dockerhub)
• Better permissions UX. Currently GCP requires service accounts to be used with cloud products, the experience adding/removing permissions is difficult to navigate

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We definitely need to renew it because we dont own our own infrastructure and storage and we are happy with Cloud Run features

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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.

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Not seen any major issues when we run applications its good

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Initially we felt slow but slowly it picked up and easy to manage

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I was involved in the initial implementation setup, Its easy with the given documentaiton we can do ourself. Not that critical

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Docker, lxc, Ubuntu Snappy, partisan chroot+unshare Reformulating the problem and realizing a container is not necessary when a testing environment with clearly defined behavior.

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AWS Lambda supports code zip package, enabling lower cold start time. Also, AWS Lambda pricing is much simpler, easier to understand.

Other than that, the 2 products are very similar, including the Docker image support: the image must be built based on proprietary base image.

Obviously, if your other services are running in GCP, then Google Cloud Run is your only choice for tight integration, & private networking.

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Not part of purchase.

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It has good auto scale feature and reliable also

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We have very good support when needed

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• Developers spend less time configuring and more time coding.
• Less time training developers as CoreOS rkt lets them use whatever hardware and operating system they want.
• Reduced our IT costs, solutions are containerized using CoreOS rkt meaning they can write one solution with many developers in mind.

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• Built in support for auto scaling helps reduce operational overhead
• Any application performance issues can be addressed quickly by allocating more resources while a proper fix can be planned and rolled out later
• Using Google Cloud Run enables development of microservices which provides granular control for scaling critical services in the platform

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