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Designing for Compliance and Security

Design for compliance: this covers one’s knowledge of legislation (health record privacy, data privacy, ownership, and children’s privacy); commercial (sensitive data handling and personally identifiable information); industry certifications (SOC 2); audits (such as logs).
Design for security: the learners need to gain knowledge of penetration testing; identity and access management; resource hierarchy; separation of duties; security control; data security; customer-managed encryption key management with Cloud KMS;

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Google Certified Professional - Cloud Architect (GCP) Sample Questions (Q73-Q78):

NEW QUESTION # 73
For this question, refer to the TerramEarth case study. To be compliant with European GDPR regulation, TerramEarth is required to delete data generated from its European customers after a period of 36 months when it contains personal data. In the new architecture, this data will be stored in both Cloud Storage and BigQuery. What should you do?

A. Create a BigQuery time-partitioned table for the European data, and set the partition expiration period to
36 months. For Cloud Storage, use gsutil to enable lifecycle management using a DELETE action with an Age condition of 36 months.
B. Create a BigQuery table for the European data, and set the table retention period to 36 months. For Cloud Storage, use gsutil to enable lifecycle management using a DELETE action with an Age condition of 36 months.
C. Create a BigQuery time-partitioned table for the European data, and set the partition period to 36 months. For Cloud Storage, use gsutil to create a SetStorageClass to NONE action with an Age condition of 36 months.
D. Create a BigQuery table for the European data, and set the table retention period to 36 months. For Cloud Storage, use gsutil to create a SetStorageClass to NONE action when with an Age condition of 36 months.

Answer: A

Explanation:
Explanation
https://cloud.google.com/bigquery/docs/managing-partitioned-tables#partition-expiration
https://cloud.google.com/storage/docs/lifecycle
Topic 7, Mountkrik Games Case 2
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.

NEW QUESTION # 74
You need to reduce the number of unplanned rollbacks of erroneous production deployments in your
company's web hosting platform. Improvement to the QA/Test processes accomplished an 80% reduction.
Which additional two approaches can you take to further reduce the rollbacks? Choose 2 answers.

A. Replace the QA environment with canary releases
B. Introduce a green-blue deployment model
C. Reduce the platform's dependency on relational database systems
D. Fragment the monolithic platform into microservices
E. Replace the platform's relational database systems with a NoSQL database

Answer: B,D

NEW QUESTION # 75
For this question, refer to the TerramEarth case study. You need to implement a reliable, scalable GCP solution for the data warehouse for your company, TerramEarth. Considering the TerramEarth business and technical requirements, what should you do?

A. Replace the existing data warehouse with BigQuery. Use table partitioning.
B. Replace the existing data warehouse with BigQuery. Use federated data sources.
C. Replace the existing data warehouse with a Compute Engine instance with 96 CPUs. Add an additional Compute Engine pre-emptible instance with 32 CPUs.
D. Replace the existing data warehouse with a Compute Engine instance with 96 CPUs.

Answer: B

Explanation:
Reference:
https://cloud.google.com/solutions/bigquery-data-warehouse#external_sources
https://cloud.google.com/solutions/bigquery-data-warehouse

NEW QUESTION # 76
For this question, refer to the Mountkirk Games case study.
Mountkirk Games has deployed their new backend on Google Cloud Platform (GCP). You want to create a thorough testing process for new versions of the backend before they are released to the public. You want the testing environment to scale in an economical way. How should you design the process?

A. Create a scalable environment in GCP for simulating production load.
B. Create a set of static environments in GCP to test different levels of load - for example, high, medium, and low.
C. Build stress tests into each component of your application using resources internal to GCP to simulate load.
D. Use the existing infrastructure to test the GCP-based backend at scale.

Answer: A

Explanation:
From scenario: Requirements for Game Backend Platform
* Dynamically scale up or down based on game activity
* Connect to a managed NoSQL database service
* Run customize Linux distro

NEW QUESTION # 77
You want to optimize the performance of an accurate, real-time, weather-charting application. The data comes from 50,000 sensors sending 10 readings a second, in the format of a timestamp and sensor reading. Where should you store the data?

A. Google Cloud Bigtable
B. Google BigQuery
C. Google Cloud SQL
D. Google Cloud Storage

Answer: D

NEW QUESTION # 78
......

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