Case Study 1 - HipLocal
Company Overview
HipLocal is a community application designed to facilitate communication between people in close proximity. It is used for event planning and organizing sporting events, and for businesses to connect with their local communities. HipLocal launched recently in a few neighborhoods in Dallas and is rapidly growing into a global phenomenon. Its unique style of hyper-local community communication and business outreach is in demand around the world.
Executive Statement
We are the number one local community app; it's time to take our local community services global. Our venture capital investors want to see rapid growth and the same great experience for new local and virtual communities that come online, whether their members are 10 or 10000 miles away from each other.
Solution Concept
HipLocal wants to expand their existing service, with updated functionality, in new regions to better serve their global customers. They want to hire and train a new team to support these regions in their time zones. They will need to ensure that the application scales smoothly and provides clear uptime data.
Existing Technical Environment
HipLocal's environment is a mix of on-premises hardware and infrastructure running in Google Cloud Platform. The HipLocal team understands their application well, but has limited experience in global scale applications. Their existing technical environment is as follows:
* Existing APIs run on Compute Engine virtual machine instances hosted in GCP.
* State is stored in a single instance MySQL database in GCP.
* Data is exported to an on-premises Teradata/Vertica data warehouse.
* Data analytics is performed in an on-premises Hadoop environment.
* The application has no logging.
* There are basic indicators of uptime; alerts are frequently fired when the APIs are unresponsive.
Business Requirements
HipLocal's investors want to expand their footprint and support the increase in demand they are seeing. Their requirements are:
* Expand availability of the application to new regions.
* Increase the number of concurrent users that can be supported.
* Ensure a consistent experience for users when they travel to different regions.
* Obtain user activity metrics to better understand how to monetize their product.
* Ensure compliance with regulations in the new regions (for example, GDPR).
* Reduce infrastructure management time and cost.
* Adopt the Google-recommended practices for cloud computing.
Technical Requirements
* The application and backend must provide usage metrics and monitoring.
* APIs require strong authentication and authorization.
* Logging must be increased, and data should be stored in a cloud analytics platform.
* Move to serverless architecture to facilitate elastic scaling.
* Provide authorized access to internal apps in a secure manner.
HipLocal wants to reduce the number of on-call engineers and eliminate manual scaling.
Which two services should they choose? (Choose two.)

• A. Use Google Kubernetes Engine for automated deployments.
• B. Use serverless Google Cloud Functions.
• C. Use a large Google Compute Engine cluster for deployments.
• D. Use Knative to build and deploy serverless applications.
• E. Use Google App Engine services.

You are running an application on App Engine that you inherited. You want to find out whether the application is using insecure binaries or is vulnerable to XSS attacks.
Which service should you use?

• A. Cloud Security Scanner
• B. Stackdriver Debugger
• C. Stackdriver Error Reporting
• D. Cloud Amor

You maintain a CI/CD pipeline for an application running on GKE. You use Cloud Build to create container images and push the images to Artifact Registry. When you build the image, you use the latest tag in your pipeline.
You recently had to roll back a deployment 24 hours after rollout. The rollback process was difficult because the latest tag had been overwritten. You need to prevent this issue in the future.
You want to use the most efficient approach. What should you do?

• A. Implement Helm charts to manage your container deployments.
• B. Use a Docker registry to store the container images, and create separate repositories for each version of the application.
• C. Rebuild the Docker image for each environment, and tag it with the specific environment name.
• D. Build a separate Docker image for each new version of the application, and tag it with the version number.

You are a developer that works for a local concert venue. Customers use your company's website to purchase tickets for events. You need to provide customers with immediate confirmation when a selected seat has been reserved. How should you design the ticket ordering process?

• A. Publish the seat reservation to a Pub/Sub topic. Configure the backend service to use Eventarc to process the seat reservation on GKE.
• B. Add the seat reservation to a Cloud Tasks queue, which triggers Workflows to process the seat reservation.
• C. Upload the seat reservation to a Cloud Storage bucket, which triggers an event to a Cloud Run service that processes the orders.
• D. Submit the seat reservation in an HTTP POST request to an Application Load Balancer.Configure the Application Load Balancer to distribute the request to a Compute Engine managed instance group that processes the reservation.