Google Cloud Platform

I am currently working on a long term mobile app project. Current stack: Frontend: Dart/Flutter Backend: Go, AWS Resources (AWS Lambda, Amazon DynamoDB, etc.) Since there are only two developers and we have limited time and resources, we are looking for a BAAS like Firebase or AWS Amplify to handle auth and push notifications for now. We are prioritizing developing speed so we can iterate quickly. The only problem is that AWS amplify support for flutter is in developer preview and has limited capabilities (We have tested it out in our app). Firebase is the more mature option. It has great support for flutter and has more than we need for auth, notifications, etc. My question is that, if we choose firebase, we would be stuck with using two different cloud providers. Is this bad, or is this even a problem? I am willing to change anything on the backend architecture wise, so any suggestions would be greatly appreciated as I am somewhat unfamiliar with Google Cloud Platform. Thank you.

I have started using AWS Batch for some long ML inference jobs. So far it's working well and giving a decent performance. Since it is fully managed, it saves a lot of extra work as well. But Batch takes a good amount of time to create a new cluster and then load the job based on the priority of the queue. Going forward would love to put effort into something which is fast to start and give more flexibility as well. What other tools you would suggest for long-running backend jobs which can scale well. I am not looking for something fully managed so ignore the options similar to batch in Google Cloud Platform or Microsoft Azure, Looking for open-source alternatives here. Do you think Kubernetes, RabbitMQ/Kafka will be a good fit or just overkill for my problem. Usually w we get 1000s of requests in parallel and each job might take 20-30 mins in a 2 vCPU system.

I am new to the cloud platforms. I am trying to figure out which Google Cloud product would be the best fit for my needs. Here are the requirements I am trying to meet:

1. Store data in Google Cloud Platform.
2. Support potentially thousands of concurrent users running analytical queries.
3. The data volumes would be moderate (as far as Google is concerned) - we are talking 10's of GB up to potentially 100s of GB.
4. The data needs to be updated once a day (but ideally a few times a day).
5. Perhaps my biggest goal is the following: I am trying to avoid having to build a traditional data warehouse with star-schema and ETL process. I have experience with these projects, and they end up being very costly, error-prone, hard to troubleshoot, and rigid (hard to deploy changes). Instead, I am hoping to just copy my OLTP tables to GCP and query them from there, relying on GCP horsepower. I appreciate any feedback.

Hello folks, we are making a company internal google chatbot system hosted on Google Cloud Platform. The backend is being written in ExpressJS + TypeScript, we are planning to use Cloud SQL to store basic entities like Users, Spaces, Connections(use-case specific).

The question I have is which tool is recommended for this basic use case where we want to query some data and perform CRUD operations. Also, how we should be handling the DB version control & migrations?