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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's data science team wants to analyze user reviews.
How should they prepare the data?

• A. Use the Cloud Data Loss Prevention API for de-identification of the review dataset.
• B. Use the Cloud Data Loss Prevention API for redaction of the review dataset.
• C. Use the Cloud Natural Language Processing API for redaction of the review dataset.
• D. Use the Cloud Natural Language Processing API for de-identification of the review dataset.

You are developing a mobile application that allows users to create and manage to-do lists. Your application has the following requirements:
- Store and synchronize data between different mobile devices.
- Support offline access.
- Provide real-time updates on each user's device.
You need to implement a database solution while minimizing operational effort. Which approach should you use?

• A. Create a Bigtable instance. Design a database schema to avoid hotspots when writing data. Use a Bigtable change stream to capture data changes.
• B. Use Firestore as the database. Configure Firestore offline persistence to cache a copy of the Firestore data. Listen to document changes to update applications whenever there are document changes.
• C. Implement a SQLite database on each user's device. Use a scheduled job to synchronize each device database with a copy stored in Cloud Storage.
• D. Create a Cloud SQL for MySQL instance. Implement a data model to store to-do list information.
  Create indexes for the most heavily and frequently used queries.

You work for an environmental agency in a large city. You are developing a new monitoring platform that will capture air quality readings from thousands of locations in the city. You want the air quality reading devices to send and receive their data payload to the newly created RESTful backend systems every minute by using a curl command. The backend systems are running in a single cloud region and are using Premium Tier networking. You need to connect the devices to the backend while minimizing the daily average latency, measured by using Time to First Byte (TTFB). How should you build this service?

• A. 1. Run the air quality devices' backends on Compute Engine VMs.
  2. Create a round robin routing policy on Cloud DNS for these Compute Engine VMs.
  3. Configure the air quality devices to connect by using this DNS.
• B. 1 Run the air quality devices' backends in a managed instance group.
  2. Create an external Application Load Balancer, and connect it to the managed instance group.
  3. Configure a connection between the air quality devices and the Application Load Balancer.
• C. 1. Run the air quality devices' backends on Compute Engine VMs.
  2. Create a weighted round robin routing policy on Cloud DNS.
  3. Configure the air quality devices to connect by using this DNS.
• D. 1. Run the air quality devices' backends in a managed instance group.
  2. Create an external passthrough Network Load Balancer to connect to the managed instance group.
  3. Configure a connection between the air quality devices and the Network Load Balancer.

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 has connected their Hadoop infrastructure to GCP using Cloud Interconnect in order to query data stored on persistent disks.
Which IP strategy should they use?

• A. Create manual subnets.
• B. Provision a single instance for NAT.
• C. Create multiple peered VPCs.
• D. Create an auto mode subnet.

You are tasked with using C++ to build and deploy a microservice for an application hosted on Google Cloud. The code needs to be containerized and use several custom software libraries that your team has built. You do not want to maintain the underlying infrastructure of the application.
How should you deploy the microservice?

• A. Use Cloud Shell to containerize your microservice, and deploy it on standard Google Kubernetes Engine.
• B. Use Cloud Functions to deploy the microservice.
• C. Use Cloud Shell to containerize your microservice, and deploy it on a Container-Optimized OS Compute Engine instance.
• D. Use Cloud Build to create the container, and deploy it on Cloud Run.