You operate a database that stores stock trades and an application that retrieves average stock price for a given company over an adjustable window of time. The data is stored in Cloud Bigtable where the datetime of the stock trade is the beginning of the row key. Your application has thousands of concurrent users, and you notice that performance is starting to degrade as more stocks are added. What should you do to improve the performance of your application?

• A.Change the row key syntax in your Cloud Bigtable table to begin with the stock symbol.
• B.Change the row key syntax in your Cloud Bigtable table to begin with a random number per second.
• C.Change the data pipeline to use BigQuery for storing stock trades, and update your application.
• D.Use Cloud Dataflow to write summary of each day's stock trades to an Avro file on Cloud Storage.
  Update your application to read from Cloud Storage and Cloud Bigtable to compute the responses.

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You are deploying a new storage system for your mobile application, which is a media streaming service. You decide the best fit is Google Cloud Datastore. You have entities with multiple properties, some of which can take on multiple values. For example, in the entity 'Movie' the property 'actors' and the property 'tags' have multiple values but the property 'date released' does not. A typical query would ask for all movies with actor=<actorname> ordered by date_released or all movies with tag=Comedy ordered by date_released. How should you avoid a combinatorial explosion in the number of indexes?

• A.Set the following in your entity options: exclude_from_indexes = 'actors, tags'
• B.Set the following in your entity options: exclude_from_indexes = 'date_published'
• C.Manually configure the index in your index config as follows:
  
• D.Manually configure the index in your index config as follows:
  

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You plan to deploy Cloud SQL using MySQL. You need to ensure high availability in the event of a zone failure.
What should you do?

• A.Create a Cloud SQL instance in one zone, and create a read replica in another zone within the same region.
• B.Create a Cloud SQL instance in a region, and configure automatic backup to a Cloud Storage bucket in the same region.
• C.Create a Cloud SQL instance in one zone, and create a failover replica in another zone within the same region.
• D.Create a Cloud SQL instance in one zone, and configure an external read replica in a zone in a different region.

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You set up a streaming data insert into a Redis cluster via a Kafka cluster. Both clusters are running on Compute Engine instances. You need to encrypt data at rest with encryption keys that you can create, rotate, and destroy as needed. What should you do?

• A.Create a dedicated service account, and use encryption at rest to reference your data stored in your Compute Engine cluster instances as part of your API service calls.
• B.Create encryption keys in Cloud Key Management Service. Use those keys to encrypt your data in all of the Compute Engine cluster instances.
• C.Create encryption keys locally. Upload your encryption keys to Cloud Key Management Service. Use those keys to encrypt your data in all of the Compute Engine cluster instances.
• D.Create encryption keys in Cloud Key Management Service. Reference those keys in your API service calls when accessing the data in your Compute Engine cluster instances.

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You are designing a basket abandonment system for an ecommerce company. The system will send a
message to a user based on these rules:
No interaction by the user on the site for 1 hour

Has added more than $30 worth of products to the basket

Has not completed a transaction

You use Google Cloud Dataflow to process the data and decide if a message should be sent. How should
you design the pipeline?

• A.Use a sliding time window with a duration of 60 minutes.
• B.Use a fixed-time window with a duration of 60 minutes.
• C.Use a session window with a gap time duration of 60 minutes.
• D.Use a global window with a time based trigger with a delay of 60 minutes.

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