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Google Certified Professional - Cloud Architect (GCP) Sample Questions (Q133-Q138):

NEW QUESTION # 133
To reduce costs, the Director of Engineering has required all developers to move their development infrastructure resources from on-premises virtual machines (VMs) to Google Cloud Platform. These resources go through multiple start/stop events during the day and require state to persist. You have been asked to design the process of running a development environment in Google Cloud while providing cost visibility to the finance department.
Which two steps should you take? Choose 2 answers.

A. Store all state into local SSD, snapshot the persistent disks, and terminate the VM
B. Store all state in Google Cloud Storage, snapshot the persistent disks, and terminate the VM
C. Apply VM CPU utilization label and include it in the BigQuery billing export
D. Use the - -no-auto-delete flag on all persistent disks and stop the VM
E. Use the - -auto-delete flag on all persistent disks and terminate the VM
F. Use Google BigQuery billing export and labels to associate cost to groups

Answer: A,C

Explanation:
Explanation/Reference:
Explanation:
C: Billing export to BigQuery enables you to export your daily usage and cost estimates automatically throughout the day to a BigQuery dataset you specify.
Labels applied to resources that generate usage metrics are forwarded to the billing system so that you can break down your billing charges based upon label criteria. For example, the Compute Engine service reports metrics on VM instances. If you deploy a project with 2,000 VMs, each of which is labeled distinctly, then only the first 1,000 label maps seen within the 1 hour window will be preserved.
E: You cannot stop an instance that has a local SSD attached. Instead, you must migrate your critical data off of the local SSD to a persistent disk or to another instance before you delete the instance completely.
You can stop an instance temporarily so you can come back to it at a later time. A stopped instance does not incur charges, but all of the resources that are attached to the instance will still be charged.
Alternatively, if you are done using an instance, delete the instance and its resources to stop incurring charges.
References:
https://cloud.google.com/billing/docs/how-to/export-data-bigquery
https://cloud.google.com/compute/docs/instances/stopping-or-deleting-an-instance

NEW QUESTION # 134
Case Study: 7 - Mountkirk Games
Company Overview
Mountkirk Games makes online, session-based, multiplayer games for mobile platforms. They build all of their games using some server-side integration. Historically, they have used cloud providers to lease physical servers.
Due to the unexpected popularity of some of their games, they have had problems scaling their global audience, application servers, MySQL databases, and analytics tools.
Their current model is to write game statistics to files and send them through an ETL tool that loads them into a centralized MySQL database for reporting.
Solution Concept
Mountkirk Games is building a new game, which they expect to be very popular. They plan to deploy the game's backend on Google Compute Engine so they can capture streaming metrics, run intensive analytics, and take advantage of its autoscaling server environment and integrate with a managed NoSQL database.
Business Requirements
Increase to a global footprint.

Improve uptime - downtime is loss of players.

Increase efficiency of the cloud resources we use.

Reduce latency to all customers.

Technical Requirements
Requirements for Game Backend Platform
Dynamically scale up or down based on game activity.

Connect to a transactional database service to manage user profiles and game state.

Store game activity in a timeseries database service for future analysis.

As the system scales, ensure that data is not lost due to processing backlogs.

Run hardened Linux distro.

Requirements for Game Analytics Platform
Dynamically scale up or down based on game activity

Process incoming data on the fly directly from the game servers

Process data that arrives late because of slow mobile networks

Allow queries to access at least 10 TB of historical data

Process files that are regularly uploaded by users' mobile devices

Executive Statement
Our last successful game did not scale well with our previous cloud provider, resulting in lower user adoption and affecting the game's reputation. Our investors want more key performance indicators (KPIs) to evaluate the speed and stability of the game, as well as other metrics that provide deeper insight into usage patterns so we can adapt the game to target users.
Additionally, our current technology stack cannot provide the scale we need, so we want to replace MySQL and move to an environment that provides autoscaling, low latency load balancing, and frees us up from managing physical servers.
For this question, refer to the Mountkirk Games case study. Which managed storage option meets Mountkirk's technical requirement for storing game activity in a time series database service?

A. Cloud Spanner
B. Cloud Bigtable
C. BigQuery
D. Cloud Datastore

Answer: B

NEW QUESTION # 135
Your customer wants to capture multiple GBs of aggregate real-time key performance indicators (KPIs) from their game servers running on Google Cloud Platform and monitor the KPIs with low latency. How should they capture the KPIs?

A. Output custom metrics to Stackdriver from the game servers, and create a Dashboard in Stackdriver Monitoring Console to view them.
B. Schedule BigQuery load jobs to ingest analytics files uploaded to Cloud Storage every ten minutes, and visualize the results in Google Data Studio.
C. Insert the KPIs into Cloud Datastore entities, and run ad hoc analysis and visualizations of them in Cloud Datalab.
D. Store time-series data from the game servers in Google Bigtable, and view it using Google Data Studio.

Answer: D

NEW QUESTION # 136
Your company has an application that is running on multiple instances of Compute Engine. It generates 1 TB per day of logs. For compliance reasons, the logs need to be kept for at least two years. The logs need to be available for active query for 30 days. After that, they just need to be retained for audit purposes. You want to implement a storage solution that is compliant, minimizes costs, and follows Google-recommended practices.
What should you do?

A. 1. Install the Cloud Ops agent on all instances.
2. Create a sink to export logs into a partitioned BigQuery table.
3. Set a time_partitioning_expiration of 30 days.
B. 1. Write a daily cron job, running on all instances, that uploads logs into a Cloud Storage bucket.
2. Create a sink to export logs into a regional Cloud Storage bucket.
3. Create an Object Lifecycle rule to move files into a Coldline Cloud Storage bucket after one month.
C. 1. Install the Cloud Ops agent on all instances.
2. Create a sink to export logs into a regional Cloud Storage bucket.
3. Create an Object Lifecycle rule to move files into a Coldline Cloud Storage bucket after one month.
4. Configure a retention policy at the bucket level to create a lock.
D. 1. Create a daily cron job, running on all instances, that uploads logs into a partitioned BigQuery table. 2. Set a time_partitioning_expiration of 30 days.

Answer: C

Explanation:
The practice for managing logs generated on Compute Engine on Google Cloud is to install the Cloud Logging agent and send them to Cloud Logging.
The sent logs will be aggregated into a Cloud Logging sink and exported to Cloud Storage.
The reason for using Cloud Storage as the destination for the logs is that the requirement in question requires setting up a lifecycle based on the storage period.
In this case, the log will be used for active queries for 30 days after it is saved, but after that, it needs to be stored for a longer period of time for auditing purposes.
If the data is to be used for active queries, we can use BigQuery's Cloud Storage data query feature and move the data past 30 days to Coldline to build a cost-optimal solution.
Therefore, the correct answer is as follows
1. Install the Cloud Logging agent on all instances.
Create a sync that exports the logs to the region's Cloud Storage bucket.
3. Create an Object Lifecycle rule to move the files to the Coldline Cloud Storage bucket after one month. 4.
4. set up a bucket-level retention policy using bucket locking."

NEW QUESTION # 137
A news teed web service has the following code running on Google App Engine. During peak load, users report that they can see news articles they already viewed. What is the most likely cause of this problem?

A. The session variable is being overwritten in Cloud Datastore.
B. The HTTP Expires header needs to be set to -1 to stop caching.
C. The session variable is local to just a single instance.
D. The URL of the API needs to be modified to prevent caching.

Answer: C

Explanation:
Reference:
https://stackoverflow.com/questions/3164280/google-app-engine-cache-list-in-session-variable?rq=1

NEW QUESTION # 138
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