Google Cloud Run enables users to build and deploy scalable containerized apps written in any language (including Go, Python, Java, Node.js, .NET, and Ruby) on a fully managed platform. Cloud Run can be paired with other container ecosystem tools, including Google's Cloud Build, Cloud Code, Artifact Registry, and Docker. And it features out-of-the-box integration with Cloud Monitoring, Cloud Logging, Cloud Trace, and Error Reporting to ensure the health of an application.
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Google Kubernetes Engine
Score 8.1 out of 10
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Google Kubernetes Engine supplies containerized application management powered by Kubernetes which includes Google Cloud services including load balancing, automatic scaling and upgrade, and other Google Cloud services.
It has a similar purpose in terms of hosting and orchestrating applications in Docker containers. GoogleCloud Run stands out for being much easier and more intuitive to maintain and configure, and can even be used by teams with little knowledge of container orchestration …
Usage is easy and also we have GCP as out cloud partner hence we made up our mind to go with Cloud Run and so far no issues things are going fine with it. and getting good features from Google in it.
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.
If your application is complex, if it's planet-scale, or if you need autoscaling, then Kubernetes is best suited. If your application is straightforward, you can opt for App Engine or Cloud Run. In many cases, you can prefer to run the cloud on GKE. But once you deploy on Kubernetes, you get the flexibility to try different things. But if you don't seek flexibility, it's not an option for you.
Engine upgrade rollout strategy - well documented and configurable
Integration with other Google Cloud services like the Compute Engine, SaaS databases, and some cloud networking like Cloud Armor
Graphical interface for a lot of operations - either for a quick peek/overview or actual work done by administrators and/or developers (via the Google Cloud Console, for example)
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
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.
Very good Kubernetes distribution with a reasonable total price. Integration with storage and load balancer for ingress and services speed up every process deployment.
GKE spins up new nodes a LOT faster than AKS. GKE's auto scaler runs a lot smoother than AKS. GKE has a lot more Kubernetes features baked in natively.
When issues came up, we reached out to some folks at GCP and they seemed to be very prompt and attentive to our needs. They were always willing to help and provide additional details or recommendations or links to resources. This kind of support is very helpful as it allows us to navigate GKE with more confidence.