Your development teams release new versions of games running on Google Kubernetes Engine (GKE) daily.
You want to create service level indicators (SLIs) to evaluate the quality of the new versions from the user's perspective. What should you do?

• A.Create CPU Utilization and Request Latency as service level indicators.
• B.Create Request Latency and Error Rate as service level indicators.
• C.Create Server Uptime and Error Rate as service level indicators.
• D.Create GKE CPU Utilization and Memory Utilization as service level indicators.

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For this question, refer to the Helicopter Racing League (HRL) case study. HRL is looking for a cost-effective approach for storing their race data such as telemetry. They want to keep all historical records, train models using only the previous season's data, and plan for data growth in terms of volume and information collected.
You need to propose a data solution. Considering HRL business requirements and the goals expressed by CEO S. Hawke, what should you do?

• A.Use BigQuery for its scalability and ability to add columns to a schema. Partition race data based on season.
• B.Use Firestore for its scalable and flexible document-based database. Use collections to aggregate race data by season and event.
• C.Use Cloud SQL for its ability to automatically manage storage increases and compatibility with MySQL. Use separate database instances for each season.
• D.Use Cloud Spanner for its scalability and ability to version schemas with zero downtime. Split race data using season as a primary key.

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Your web application has several VM instances running within a VPC. You want to restrict communications between instances to only the paths and ports you authorize, but you don't want to rely on static IP addresses or subnets because the app can autoscale. How should you restrict communications?

• A.Use separate VPCs to restrict traffic
• B.Use service accounts and configure the web application to authorize particular service accounts to have access
• C.Use Cloud DNS and only allow connections from authorized hostnames
• D.Use firewall rules based on network tags attached to the compute instances

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You have been asked to select the storage system for the click-data of your company's large portfolio of websites. This data is streamed in from a custom website analytics package at a typical rate of 6,000 clicks per minute, with bursts of up to 8,500 clicks per second. It must have been stored for future analysis by your data science and user experience teams. Which storage infrastructure should you choose?

• A.Google Cloud SQL
• B.Google Cloud Bigtable
• C.Google Cloud Storage
• D.Google cloud Datastore

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Your company wants you to build a highly reliable web application with a few public APIs as the backend.
You don't expect a lot of user traffic, but traffic could spike occasionally. You want to leverage Cloud Load Balancing, and the solution must be cost-effective for users. What should you do?

• A.Store static content such as HTML and images in Cloud CDN. Host the APIs on App Engine and store the user data in Cloud SQL.
• B.Store static content such as HTML and images in a Cloud Storage bucket. Host the APIs on a zonal Google Kubernetes Engine cluster with worker nodes in multiple zones, and save the user data in Cloud Spanner.
• C.Store static content such as HTML and images in Cloud CDN. Use Cloud Run to host the APIs and save the user data in Cloud SQL.
• D.Store static content such as HTML and images in a Cloud Storage bucket. Use Cloud Functions to host the APIs and save the user data in Firestore.

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