https://cloud.google.com/run/docs/tutorials/gcloud
https://cloud.google.com/resource-manager/docs/creating-managing-projects
https://cloud.google.com/iam/docs/understanding-roles#primitive_roles
You can shut down projects using the Cloud Console. When you shut down a project, this immediately happens: All billing and traffic serving stops, You lose access to the project, The owners of the project will be notified and can stop the deletion within 30 days, The project will be scheduled to be deleted after 30 days.
However, some resources may be deleted much earlier.

GCP App Engine natively offers traffic splitting functionality between versions. You can use traffic splitting to specify a percentage distribution of traffic across two or more of the versions within a service. Splitting traffic allows you to conduct A/B testing between your versions and provides control over the pace when rolling out features.
Ref: https://cloud.google.com/appengine/docs/standard/python/splitting-traffic

The goal is to create a serverless, scalable, and asynchronous transaction processing system with minimal management overhead.
Serverless Requirement:Options involving installing Kafka on VMs (A, B) or using VM instances for processing (B, C) introduce management overhead associated with VMs (patching, scaling configuration, OS management) and Kafka cluster management, violating the serverless and minimal management criteria.
Asynchronous Requirement:Both Kafka and Pub/Sub can handle asynchronous messaging. However, Pub
/Sub is Google Cloud's fully managed, serverless messaging service, inherently minimizing management overhead compared to self-managed Kafka on VMs.
Scalability and Processing:Cloud Run is a fully managed, serverless platform that automatically scales based on traffic, suitable for processing transactions without managing underlying infrastructure. VM instances require manual scaling configuration or managed instance groups, adding overhead.
Combining Pub/Sub for asynchronous message ingestion (fully managed, serverless) and Cloud Run for processing (fully managed, serverless, scalable) directly meets all requirements: serverless, scalable, asynchronous, and minimal management overhead. Option D is the only one that uses fully serverless components for both ingestion and processing.
References:
Google Cloud Pub/Sub Overview: "Pub/Sub is an asynchronous and scalable messaging service..." -
https://cloud.google.com/pubsub/docs/overview
Google Cloud Run Overview: "Cloud Run is a managed compute platform that lets you run containers directly on top of Google's scalable infrastructure." -https://cloud.google.com/run/docs/overview/what-is- cloud-run Serverless Patterns (Pub/Sub + Cloud Run): This combination is a standard pattern for event-driven, serverless applications. -https://cloud.google.com/run/docs/triggering/pubsub-push

As mentioned in Schema and data model, you should be careful when choosing a primary key to not accidentally create hotspots in your database. One cause of hotspots is having a column whose value monotonically increases as the first key part, because this results in all inserts occurring at the end of your key space. This pattern is undesirable because Cloud Spanner divides data among servers by key ranges, which means all your inserts will be directed at a single server that will end up doing all the work.https://cloud.
google.com/spanner/docs/schema-design#primary-key-prevent-hotspots