Google Associate-Cloud-Engineer - Google Cloud Certified - Associate Cloud Engineer

The requirements specify a relational database that provides global scale and is a managed service.

Cloud Spanner is Google Cloud ' s globally distributed, strong-consistency database service. It provides limitless horizontal scaling while maintaining the structure of a relational database, making it the best fit for an application with a rapidly growing, global user base. As a fully managed service, it inherently minimizes management and administration efforts.

Cloud SQL (Option A) is a regional managed relational database and does not offer the same unlimited, global horizontal scaling capability as Spanner.

Google HTTP(S) Load Balancing has native support for the WebSocket protocol when you use HTTP or HTTPS, not HTTP/2, as the protocol to the backend.

Ref: https://cloud.google.com/load-balancing/docs/https#websocket_proxy_support

So the next possible step is to Meet with the cloud enablement team to discuss load balancer options.

We dont need to convert WebSocket code to use HTTP streaming or Redesign the application, as WebSocket support is offered by Google HTTP(S) Load Balancing. Reviewing the encryption requirements is a good idea but it has nothing to do with WebSockets.

Let ' s analyze each option to find the one that meets the requirements of no startup time for new traffic, two idle instances, and minimal administrative overhead:

A. Unchecking " Serve this revision immediately " and using a traffic simulation tool: Unchecking " Serve this revision immediately " does prevent the new revision from receiving traffic immediately. However, manually using a traffic simulation tool adds administrative overhead. It also doesn ' t guarantee that two idle instances will be ready before traffic is shifted; you would need to monitor and adjust traffic manually based on the simulation.

B. Configuring service autoscaling and setting the minimum number of instances to 2: Service-level autoscaling applies to all revisions of the service. Setting the minimum instances at the service level would ensure at least two instances are running across all active revisions, not specifically for the new revision before traffic shift.

C. Configuring revision autoscaling for the new revision and setting the minimum number of instances to 2: This is the correct approach. By configuring revision autoscaling specifically for the new revision and setting the minimum number of instances to 2, Cloud Run will ensure that at least two instances of the new version are running and ready to serve traffic before you redirect any traffic to it. This eliminates startup latency when you do shift traffic. It also minimizes administrative overhead as Cloud Run manages the instance scaling based on this configuration.

D. Configuring revision autoscaling for the existing revision and setting the minimum number of instances to 2: This would ensure the existing version has at least two idle instances, which doesn ' t directly address the requirement of having idle instances ready for the new version before traffic redirection.

Google Cloud Documentation References:

Cloud Run Autoscaling: https://cloud.google.com/run/docs/configuring/min-instances - This document explains how to configure minimum and maximum instances for Cloud Run services and revisions. It clarifies that you can set minimum instances at the revision level to ensure instances are always ready.

Cloud Run Traffic Management: https://cloud.google.com/run/docs/managing/traffic - This describes how to deploy new revisions and gradually shift traffic between them. Combining minimum instances on the new revision with traffic splitting allows for zero-downtime deployments with pre-warmed instances.

===========

Cloud Storage allows world-wide storage and retrieval of any amount of data at any time. We dont need to set up auto-scaling ourselves. Cloud Storage autoscaling is managed by GCP. Cloud Storage is an object store so it is suitable for storing photos. Cloud Storage allows world-wide storage and retrieval so cater well to our worldwide audience. Cloud storage provides us lifecycle rules that can be configured to automatically delete objects older than 30 days. This also fits our requirements. Finally, Google Cloud Storage offers several storage classes such as Nearline Storage ($0.01 per GB per Month) Coldline Storage ($0.007 per GB per Month) and Archive Storage ($0.004 per GB per month) which are significantly cheaper than any of the options above.

Ref: https://cloud.google.com/storage/docs

Ref: https://cloud.google.com/storage/pricing

Showing Deployment Manager templates to your team will allow you to define the changes you want to implement in your cloud infrastructure. You can use Cloud Source Repositories to store Deployment Manager templates and collaborate with your team. Cloud Source Repositories are fully-featured, scalable, and private Git repositories you can use to store, manage and track changes to your code.

https://cloud.google.com/source-repositories/docs/features

https://medium.com/google-cloud/how-to-deploy-cassandra-and-connect-on-google-cloud-platform-with-a-few-clicks-11ee3d7001d1

https://cloud.google.com/blog/products/databases/open-source-cassandra-now-managed-on-google-cloud

https://cloud.google.com/marketplace

You can deploy Cassandra as a Service, called Astra, on the Google Cloud Marketplace. Not only do you get a unified bill for all GCP services, your Developers can now create Cassandra clusters on Google Cloud in minutes and build applications with Cassandra as a database as a service without the operational overhead of managing Cassandra

https://cloud.google.com/compute/docs/autoscaler#specifications

Autoscaling works independently from autohealing. If you configure autohealing for your group and an instance fails the health check, the autohealer attempts to recreate the instance. Recreating an instance can cause the number of instances in the group to fall below the autoscaling threshold (minNumReplicas) that you specify.

Since we need the application running at all times, we need a minimum 1 instance.

Only a single instance of the VM should run, we need a maximum 1 instance.

We want the application running at all times. If the VM crashes due to any underlying hardware failure, we want another instance to be added to MIG so that application can continue to serve requests. We can achieve this by enabling autoscaling. The only option that satisfies these three is Set autoscaling to On, set the minimum number of instances to 1, and then set the maximum number of instances to 1.

Ref: https://cloud.google.com/compute/docs/autoscaler