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Create CPU Utilization and Request Latency as service level indicators.

Create GKE CPU Utilization and Memory Utilization as service level indicators.

Create Request Latency and Error Rate as service level indicators.

Create Server Uptime and Error Rate as service level indicators.

Create a service account (SA) in the legacy game ' s Google Cloud project, add this SA in the new game ' s IAM page, and then give it the Firebase Admin role in both projects

Create a service account (SA) in the legacy game ' s Google Cloud project, add a second SA in the new game ' s IAM page, and then give the Organization Admin role to both SAs

Create a service account (SA) in the legacy game ' s Google Cloud project, give it the Firebase Admin role, and then migrate the new game to the legacy game ' s project.

Create a service account (SA) in the lgacy game ' s Google Cloud project, give the SA the Organization Admin rule and then give it the Firebase Admin role in both projects

Configure a global load balancer connected to a managed instance group running Compute Engine

instances.

Configure kubemci with a global load balancer and Google Kubernetes Engine.

Configure a global load balancer with Google Kubernetes Engine.

Configure Ingress for Anthos with a global load balancer and Google Kubernetes Engine.

Configure Workload Identity and service accounts to be used by the application platform.

Use Kubernetes Secrets, which are obfuscated by default. Configure these Secrets to be used by the

application platform.

Configure Kubernetes Secrets to store the secret, enable Application-Layer Secrets Encryption, and use

Cloud Key Management Service (Cloud KMS) to manage the encryption keys. Configure these Secrets to

be used by the application platform.

Configure HashiCorp Vault on Compute Engine, and use customer managed encryption keys and Cloud

Key Management Service (Cloud KMS) to manage the encryption keys. Configure these Secrets to be used

by the application platform.

Use gsutil to batch move files in sequence.

Use gsutil to batch copy the files in parallel.

Use gsutil to extract the files as the first part of ETL.

Use gsutil to load the files as the last part of ETL.

Set up API key validation.

Integrate OAuth 2.0 authorization.

Configure Quota policies.

Activate XML threat protection.

Create network load balancers. Use preemptible Compute Engine instances.

Create network load balancers. Use non-preemptible Compute Engine instances.

Create a global load balancer with managed instance groups and autoscaling policies. Use preemptible Compute Engine instances.

Create a global load balancer with managed instance groups and autoscaling policies. Use non-preemptible Compute Engine instances.

Create an instance template for the backend. For every region, deploy it on a multi-zone managed instance group. Use an L4 load balancer.

Create an instance template for the backend. For every region, deploy it on a single-zone managed instance group. Use an L4 load balancer.

Create an instance template for the backend. For every region, deploy it on a multi-zone managed instance group. Use an L7 load balancer.

Create an instance template for the backend. For every region, deploy it on a single-zone managed instance group. Use an L7 load balancer.

Store as much analytics and game activity data as financially feasible today so it can be used to train machine learning models to predict user behavior in the future.

Begin packaging their game backend artifacts in container images and running them on Kubernetes Engine to improve the availability to scale up or down based on game activity.

Set up a CI/CD pipeline using Jenkins and Spinnaker to automate canary deployments and improve development velocity.

Adopt a schema versioning tool to reduce downtime when adding new game features that require storing additional player data in the database.

Implement a weekly rolling maintenance process for the Linux virtual machines so they can apply critical kernel patches and package updates and reduce the risk of 0-day vulnerabilities.

Deploy failure injection software to the game analytics platform that can inject additional latency to mobile client analytics traffic.

Build a test client that can be run from a mobile phone emulator on a Compute Engine virtual machine, and run multiple copies in Google Cloud Platform regions all over the world to generate realistic traffic.

Add the ability to introduce a random amount of delay before beginning to process analytics files uploaded from mobile devices.

Create an opt-in beta of the game that runs on players ' mobile devices and collects response times from analytics endpoints running in Google Cloud Platform regions all over the world.