C:\GCP\appeng>gcloud config list
[core]
account = [email protected]
disable_usage_reporting = False
project = my-first-demo-xxxx
https://cloud.google.com/endpoints/docs/openapi/troubleshoot-gce-deployment

Reference: https://cloud.google.com/sdk/gcloud/reference/iam/roles/copy To create a copy of an existing role spanner.databaseAdmin into a project with PROJECT_ID, run: gcloud iam roles copy --source="roles/spanner.databaseAdmin" --destination=CustomSpannerDbAdmin --dest- project=PROJECT_ID

Quickstart: using the Google Cloud Console
This page shows you how to perform basic tasks in Pub/Sub using the Google Cloud Console.
Note: If you are new to Pub/Sub, we recommend that you start with the interactive tutorial.
Before you begin
Set up a Cloud Console project.
Set up a project
Click to:
Create or select a project.
Enable the Pub/Sub API for that project.
You can view and manage these resources at any time in the Cloud Console.
Install and initialize the Cloud SDK.
Note: You can run the gcloud tool in the Cloud Console without installing the Cloud SDK. To run the gcloud tool in the Cloud Console, use Cloud Shell .
https://cloud.google.com/pubsub/docs/quickstart-console

Let's evaluate each option based on the requirement of sub-millisecond latency for globally stored IoT data:
A: Spanner with Caching: While Spanner offers strong consistency and global scalability, the base latency might not consistently be sub-millisecond for all read/write operations globally. Introducing caching adds complexity and doesn't guarantee sub-millisecond latency for all initial reads or cache misses.
B: Bigtable: Bigtable is a highly scalable NoSQL database service designed for low-latency, high-throughput workloads. It excels at storing and retrieving large volumes of time-series data, which is typical for IoT sensor data. Its architecture is optimized for single-key lookups and scans, providing consistent sub-millisecond latency, making it a strong candidate for this use case.
C: BigQuery: BigQuery is a fully managed, serverless data warehouse designed for analytical queries on large datasets. While it's excellent for analyzing IoT data in batch, it's not optimized for the low-latency, high- throughput ingestion and retrieval required for real-time IoT applications with sub-millisecond latency needs.
D: Cloud Storage with Cloud CDN: Cloud Storage is object storage and is not designed for low-latency transactional workloads. Cloud CDN is a content delivery network that caches content closer to users for faster delivery, but it's not suitable for the primary storage of rapidly incoming IoT sensor data requiring sub- millisecond write latency.
Google Cloud Documentation References:
Cloud Bigtable Overview: https://cloud.google.com/bigtable/docs/overview - This document highlights Bigtable's suitability for low-latency and high-throughput applications, including IoT. It mentions its ability to handle massive amounts of data with consistent performance.
Spanner Overview: https://cloud.google.com/spanner/docs/overview - While Spanner offers low latency, Bigtable is generally preferred for extremely high-throughput, low-latency use cases like raw sensor data ingestion due to its optimized architecture for such workloads.
BigQuery Overview: https://cloud.google.com/bigquery/docs/introduction - This emphasizes BigQuery's analytical capabilities rather than low-latency operational workloads.
Cloud Storage Overview: https://cloud.google.com/storage/docs/overview - This describes Cloud Storage as object storage, not ideal for sub-millisecond latency reads and writes required for real-time IoT data.