Google Cloud Run Professional, Scientific, and Technical Services Reviews & Insights

Most of our platform services are deployed as Google Cloud Run services.

Recently, we have also turned towards Google Cloud Run jobs for performing flow run tasks managed by a job server.

Being an early startup, using Google Cloud Run helps us to keep a tab on our cloud costs based on usage.

Google Cloud Run enables microservices architecture as multiple cloud run services or jobs can be deployed while keep the cloud costs optimal based on actual usage.

Google Cloud Run services support auto scaling which helps satisfy performance requirements of applications.

Google Cloud Run services and jobs are integrated with Google cloud logging which simplifies troubleshooting of application errors.

We use Google Cloud Run to host Google Tag Manager server side scripts.

To host GTM server side script, it is perfect and almost free.

We use Google Cloud Run to run various applications such as our NextJS front-end web app that is served to public users as well as for running various backend applications that typically perform async tasks or run our API infrastructure. Google Cloud Run helps make it really easy to scale up or down and easily deploy docker images.

Cloud run is well suited when you need to spin up a dockerised application or any stateless application like a web app or backend API. Its not so great when you have to run long-running or stateful applications (but I think that's well documented). I would also say its preferred for applications or tasks that don't require massive amounts of computing or RAM. Its better at running smaller applications that are horizontally scaled.

In our organization we use Google Cloud Run, and now Cloud Run functions, for all kinds of applications. We use it as microservices for API applications, we use it to deploy GenAI application running with Langchain, and all kinds of other stuff. The big advantage of Cloud Run is that it is almost self managed, we only it to create our Docker container, and specify some configuration about memory, cpu, and instances, and all the rest is managed by Google. Rarely or never had problems with Cloud Run itself.

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.

We use Google Cloud Run to host small parts of our websites and the backend systems for our mobile apps. It helps us deploy and manage these pieces without worrying about servers. Cloud Run makes it easier for us to build, scale, and maintain our applications, saving time and money along the way.

Any application small medium to large sizes, mainly i used if for small hr application to push multi builds in different testing environments to prod usge by end users