Professional-Cloud-Architect Exam Study Guide Free Practice Test LAST UPDATED DATE Feb 25, 2023 [Q83-Q102]

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Professional-Cloud-Architect Exam Study Guide Free Practice Test LAST UPDATED DATE Feb 25, 2023

The New Professional-Cloud-Architect 2023 Updated Verified Study Guides & Best Courses


Before attending the exam for the Google Professional Cloud Architect certification, the individuals need to develop a good comprehension of its topics. The syllabus of the test is divided into five sections, each including several subtopics. The detailed outline of the exam domains can be viewed on the vendor’s website. A brief overview of the content is provided below:

  • Ensuring of Solution & Operations Reliability

    To tackle the questions related to the last domain, the applicants are required to be conversant with monitoring/logging/profiling/alerting solutions. They should know how to perform deployment & release management as well as evaluate quality control measures. IN addition, the specialists must be able to assist with the support of deployed solutions.

  • Implementation Management

    The aim of this module is to evaluate the ability of the individuals to advise operation or development team(s) to ensure the successful deployment of the solution. This includes application development, API best practices, testing frameworks, as well as data & system migration and management tooling. The examinees should also be capable of interacting with Google Cloud programmatically. This requires their understanding of Google Cloud Shell, Google Cloud SDK, and Cloud Emulators.

  • Cloud Solution Architecture Design & Planning

    Here the candidates need to demonstrate their skills in designing a solution infrastructure that satisfies the business needs; envisioning future solution improvements; creating a migration plan; designing network, compute, and storage resources; designing a solution infrastructure that satisfies the technical needs.

  • Analysis & Optimization of Technical & Business Processes

    Within this subject area, the students need to demonstrate their proficiency in analyzing and determining technical as well as business processes. It also requires their skills in developing procedures to guarantee the reliability of solutions in production.

During the exam for the Google Professional Cloud Architect certification, some of the questions will refer you to a case study describing a fictitious business & solution concept. These case studies are designed to provide the students with additional context to help them choose the right answer(s). The candidates can review the examples of possible case studies in the official guide.


Career Benefits

The Google Professional Cloud Architect certification demonstrates the ability of the specialists to design, develop, and manage robust, scalable, secure, highly available, and dynamic solutions to meet the business objectives. Earning this certificate allows the successful candidates to apply for Cloud architect jobs in a variety of companies all over the world. Some of the titles that these individuals can consider include a Cloud Infrastructure Engineer, a Cloud Operations Engineer, a Google Cloud Platform Data Architect, a Google Cloud Platform Solutions Architect, a Google Cloud Senior Analyst, and a Google Cloud Platform Data Warehouse Architect, among others. Another advantage associated with this certification is that it significantly boosts your earning potential. In 2020, this Google qualification was named the highest paying IT certificate. The average salary that you can count on holding it is $139,529 per annum.

 

NEW QUESTION 83
You deploy your custom Java application to Google App Engine.
It fails to deploy and gives you the following stack trace.

What should you do?

  • A. Upload missing JAR files and redeploy your application.
  • B. Recompile the CLoakedServlet class using and MD5 hash instead of SHA1
  • C. Digitally sign all of your JAR files and redeploy your application

Answer: C

 

NEW QUESTION 84
You are working at a financial institution that stores mortgage loan approval documents on Cloud Storage.
Any change to these approval documents must be uploaded as a separate approval file, so you want to ensure that these documents cannot be deleted or overwritten for the next 5 years. What should you do?

  • A. Use a customer-managed key for the encryption of the bucket. Rotate the key after 5 years.
  • B. Create the bucket with fine-grained access control, and grant a service account the role of Object Writer.Use the service account to upload new files.
  • C. Create the bucket with uniform bucket-level access, and grant a service account the role of Object Writer. Use the service account to upload new files.
  • D. Create a retention policy on the bucket for the duration of 5 years. Create a lock on the retention policy.

Answer: D

Explanation:
Reference: https://cloud.google.com/storage/docs/using-bucket-lock

 

NEW QUESTION 85
For this question, refer to the JencoMart case study.
JencoMart has built a version of their application on Google Cloud Platform that serves traffic to Asia. You want to measure success against their business and technical goals. Which metrics should you track?

  • A. The number of character sets present in the database
  • B. Latency difference between US and Asia
  • C. Error rates for requests from Asia
  • D. Total visits, error rates, and latency from Asia
  • E. Total visits and average latency for users in Asia

Answer: E

 

NEW QUESTION 86
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 a Cloud Storage bucket. Use Cloud Functions to host the APIs and save the user data in Firestore.
  • B. 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.
  • 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. Host the APIs on a zonal Google Kubernetes Engine cluster with worker nodes in multiple zones, and save the user data in Cloud Spanner.

Answer: D

 

NEW QUESTION 87
Your company wants to start using Google Cloud resources but wants to retain their on-premises Active Directory domain controller for identity management. What should you do?

  • A. Use Compute Engine to create an Active Directory (AD) domain controller that is a replica of the on- premises AD domain controller using Google Cloud Directory Sync.
  • B. Use Google Cloud Directory Sync to synchronize Active Directory usernames with cloud identities and configure SAML SSO.
  • C. Use Cloud Identity-Aware Proxy configured to use the on-premises Active Directory domain controller as an identity provider.
  • D. Use the Admin Directory API to authenticate against the Active Directory domain controller.

Answer: C

 

NEW QUESTION 88
Your company has successfully migrated to the cloud and wants to analyze their data stream to optimize operations. They do not have any existing code for this analysis, so they are exploring all their options.
These options include a mix of batch and stream processing, as they are running some hourly jobs and live-processing some data as it comes in.
Which technology should they use for this?

  • A. Google Cloud Dataproc
  • B. Google Cloud Dataflow
  • C. Google Compute Engine with Google BigQuery
  • D. Google Container Engine with Bigtable

Answer: B

Explanation:
Explanation/Reference:
Explanation:
Cloud Dataflow is a fully-managed service for transforming and enriching data in stream (real time) and batch (historical) modes with equal reliability and expressiveness -- no more complex workarounds or compromises needed.
References: https://cloud.google.com/dataflow/

 

NEW QUESTION 89
One of the developers on your team deployed their application In Google Container Engine with the Dockerfile below. They report that their application deployments are taking too long.

You want to optimize this Dockerfile for faster deployment times without adversely affecting the app's functionality. Which two actions should you take? Choose 2 answers

  • A. Use larger machine types for your Google Container Engine node pools.
  • B. Remove Python after running pip.
  • C. Copy the source after the package dependencies (Python and pip) are installed.
  • D. Use a slimmed-down base image like Alpine linux.
  • E. Remove dependencies from requirements.txt.

Answer: C,D

Explanation:
The speed of deployment can be changed by limiting the size of the uploaded app, limiting the complexity of the build necessary in the Dockerfile, if present, and by ensuring a fast and reliable internet connection.
Note: Alpine Linux is built around musl libc and busybox. This makes it smaller and more resource efficient than traditional GNU/Linux distributions. A container requires no more than 8 MB and a minimal installation to disk requires around 130 MB of storage. Not only do you get a fully-fledged Linux environment but a large selection of packages from the repository.
References: https://groups.google.com/forum/#!topic/google-appengine/hZMEkmmObDU
https://www.alpinelinux.org/about/

 

NEW QUESTION 90
During a high traffic portion of the day, one of your relational databases crashes, but the replica is never promoted to a master. You want to avoid this in the future. What should you do?

  • A. Implement routinely scheduled failovers of your databases.
  • B. Choose larger instances for your database.
  • C. Use a different database.
  • D. Create snapshots of your database more regularly.

Answer: B

 

NEW QUESTION 91
Operational parameters such as oil pressure are adjustable on each of TerramEarth's vehicles to increase their efficiency, depending on their environmental conditions. Your primary goal is to increase the operating efficiency of all 20 million cellular and unconnected vehicles in the field.
How can you accomplish this goal?

  • A. Capture all operating data, train machine learning models that identify ideal operations, and run locally to make operational adjustments automatically
  • B. Implement a Google Cloud Dataflow streaming job with a sliding window, and use Google Cloud Messaging (GCM) to make operational adjustments automatically
  • C. Have you engineers inspect the data for patterns, and then create an algorithm with rules that make operational adjustments automatically
  • D. Capture all operating data, train machine learning models that identify ideal operations, and host in Google Cloud Machine Learning (ML) Platform to make operational adjustments automatically

Answer: D

Explanation:
Explanation/Reference: https://cloud.google.com/customers/ocado/
TerramEarth, B
Testlet 1
Company Overview
TerramEarth manufactures heavy equipment for the mining and agricultural industries. About 80% of their business is from mining and 20% from agriculture. They currently have over 500 dealers and service centers in
100 countries. Their mission is to build products that make their customers more productive.
Solution Concept
There are 20 million TerramEarth vehicles in operation that collect 120 fields of data per second. Data is stored locally on the vehicle and can be accessed for analysis when a vehicle is serviced. The data is downloaded via a maintenance port. This same port can be used to adjust operational parameters, allowing the vehicles to be upgraded in the field with new computing modules.
Approximately 200,000 vehicles are connected to a cellular network, allowing TerramEarth to collect data directly. At a rate of 120 fields of data per second, with 22 hours of operation per day, TerramEarth collects a total of about 9 TB/day from these connected vehicles.
Existing Technical Environment
TerramEarth's existing architecture is composed of Linux and Windows-based systems that reside in a single
U.S, west coast based data center. These systems gzip CSV files from the field and upload via FTP, and place the data in their data warehouse. Because this process takes time, aggregated reports are based on data that is 3 weeks old.
With this data, TerramEarth has been able to preemptively stock replacement parts and reduce unplanned downtime of their vehicles by 60%. However, because the data is stale, some customers are without their vehicles for up to 4 weeks while they wait for replacement parts.
Business Requirements
* Decrease unplanned vehicle downtime to less than 1 week
* Support the dealer network with more data on how their customers use their equipment to better position new products and services
* Have the ability to partner with different companies - especially with seed and fertilizer suppliers in the fast- growing agricultural business - to create compelling joint offerings for their customers Technical Requirements
* Expand beyond a single datacenter to decrease latency to the American Midwest and east coast
* Create a backup strategy
* Increase security of data transfer from equipment to the datacenter
* Improve data in the data warehouse
* Use customer and equipment data to anticipate customer needs
Application 1: Data ingest
A custom Python application reads uploaded datafiles from a single server, writes to the data warehouse.
Compute:
* Windows Server 2008 R2
- 16 CPUs
- 128 GB of RAM
- 10 TB local HDD storage
Application 2: Reporting
An off the shelf application that business analysts use to run a daily report to see what equipment needs repair.
Only 2 analysts of a team of 10 (5 west coast, 5 east coast) can connect to the reporting application at a time.
Compute:
* Off the shelf application. License tied to number of physical CPUs
- Windows Server 2008 R2
- 16 CPUs
- 32 GB of RAM
- 500 GB HDD
Data warehouse:
* A single PostgreSQL server
- RedHat Linux
- 64 CPUs
- 128 GB of RAM
- 4x 6TB HDD in RAID 0
Executive Statement
Our competitive advantage has always been in our manufacturing process, with our ability to build better vehicles for lower cost than our competitors. However, new products with different approaches are constantly being developed, and I'm concerned that we lack the skills to undergo the next wave of transformations in our industry. My goals are to build our skills while addressing immediate market needs through incremental innovations.

 

NEW QUESTION 92
For this question, refer to the Mountkirk Games case study.
Mountkirk Games wants to set up a continuous delivery pipeline. Their architecture includes many small services that they want to be able to update and roll back quickly.
Mountkirk Games has the following requirements:
* Services are deployed redundantly across multiple regions in the US and Europe.
* Only frontend services are exposed on the public internet.
* They can provide a single frontend IP for their fleet of services.
* Deployment artifacts are immutable.
Which set of products should they use?

  • A. Google Cloud Storage, Google Cloud Dataflow, Google Compute Engine
  • B. Google Cloud Storage, Google App Engine, Google Network Load Balancer
  • C. Google Cloud Functions, Google Cloud Pub/Sub, Google Cloud Deployment Manager
  • D. Google Container Registry, Google Container Engine, Google HTTP(s) Load Balancer

Answer: D

Explanation:
Topic 2, TerramEarth Case Study
Company Overview
TerramEarth manufactures heavy equipment for the mining and agricultural industries:
About 80% of their business is from mining and 20% from agriculture. They currently have over 500 dealers and service centers in 100 countries. Their mission is to build products that make their customers more productive.
Company Background
TerramEarth formed in 1946, when several small, family owned companies combined to retool after World War II. The company cares about their employees and customers and considers them to be extended members of their family.
TerramEarth is proud of their ability to innovate on their core products and find new markets as their customers' needs change. For the past 20 years trends in the industry have been largely toward increasing productivity by using larger vehicles with a human operator.
Solution Concept
There are 20 million TerramEarth vehicles in operation that collect 120 fields of data per second. Data is stored locally on the vehicle and can be accessed for analysis when a vehicle is serviced. The data is downloaded via a maintenance port. This same port can be used to adjust operational parameters, allowing the vehicles to be upgraded in the field with new computing modules.
Approximately 200,000 vehicles are connected to a cellular network, allowing TerramEarth to collect data directly. At a rate of 120 fields of data per second, with 22 hours of operation per day. TerramEarth collects a total of about 9 TB/day from these connected vehicles.
Existing Technical Environment

TerramEarth's existing architecture is composed of Linux-based systems that reside in a data center. These systems gzip CSV files from the field and upload via FTP, transform and aggregate them, and place the data in their data warehouse. Because this process takes time, aggregated reports are based on data that is 3 weeks old.
With this data, TerramEarth has been able to preemptively stock replacement parts and reduce unplanned downtime of their vehicles by 60%. However, because the data is stale, some customers are without their vehicles for up to 4 weeks while they wait for replacement parts.
Business Requirements
* Decrease unplanned vehicle downtime to less than 1 week, without increasing the cost of carrying surplus inventory
* Support the dealer network with more data on how their customers use their equipment IP better position new products and services.
* Have the ability to partner with different companies-especially with seed and fertilizer suppliers in the fast-growing agricultural business-to create compelling joint offerings for their customers CEO Statement We have been successful in capitalizing on the trend toward larger vehicles to increase the productivity of our customers. Technological change is occurring rapidly and TerramEarth has taken advantage of connected devices technology to provide our customers with better services, such as our intelligent farming equipment. With this technology, we have been able to increase farmers' yields by 25%, by using past trends to adjust how our vehicles operate. These advances have led to the rapid growth of our agricultural product line, which we expect will generate 50% of our revenues by 2020.
CTO Statement
Our competitive advantage has always been in the manufacturing process with our ability to build better vehicles for tower cost than our competitors. However, new products with different approaches are constantly being developed, and I'm concerned that we lack the skills to undergo the next wave of transformations in our industry. Unfortunately, our CEO doesn't take technology obsolescence seriously and he considers the many new companies in our industry to be niche players. My goals are to build our skills while addressing immediate market needs through incremental innovations.

 

NEW QUESTION 93
Your company wants to try out the cloud with low risk. They want to archive approximately 100 TB of their log data to the cloud and test the analytics features available to them there, while also retaining that data as a long-term disaster recovery backup. Which two steps should they take? Choose 2 answers

  • A. Load logs into Google Cloud SQL.
  • B. Import logs into Google Stackdriver.
  • C. Insert logs into Google Cloud Bigtable.
  • D. Upload log files into Google Cloud Storage.
  • E. Load logs into Google BigQuery.

Answer: B,E

 

NEW QUESTION 94
You are designing an application for use only during business hours. For the minimum viable product release, you'd like to use a managed product that automatically "scales to zero" so you don't incur costs when there is no activity.
Which primary compute resource should you choose?

  • A. AppEngine flexible environment
  • B. Compute Engine
  • C. Cloud Functions
  • D. Google Kubernetes Engine

Answer: C

 

NEW QUESTION 95
JencoMart has decided to migrate user profile storage to Google Cloud Datastore and the application servers to Google Compute Engine (GCE). During the migration, the existing infrastructure will need access to Datastore to upload the data.
What service account key-management strategy should you recommend?

  • A. Provision service account keys for the on-premises infrastructure and for the GCE virtual machines (VMs)
  • B. Authenticate the on-premises infrastructure with a user account and provision service account keys for the VMs
  • C. Deploy a custom authentication service on GCE/Google Kubernetes Engine (GKE) for the on-premises infrastructure and use GCP managed keys for the VMs
  • D. Provision service account keys for the on-premises infrastructure and use Google Cloud Platform (GCP) managed keys for the VMs

Answer: D

Explanation:
Migrating data to Google Cloud Platform
Let's say that you have some data processing that happens on another cloud provider and you want to transfer the processed data to Google Cloud Platform. You can use a service account from the virtual machines on the external cloud to push the data to Google Cloud Platform. To do this, you must create and download a service account key when you create the service account and then use that key from the external process to call the Cloud Platform APIs.
Reference:
https://cloud.google.com/iam/docs/understanding-service-accounts#migrating_data_to_google_cloud_platform

 

NEW QUESTION 96
Mountkirk Games wants to limit the physical location of resources to their operating Google Cloud regions.
What should you do?

  • A. Configure the quotas for resources in the regions not being used to 0.
  • B. Configure a custom alert in Cloud Monitoring so you can disable resources as they are created in other regions.
  • C. Configure IAM conditions to limit what resources can be configured.
  • D. Configure an organizational policy which constrains where resources can be deployed.

Answer: A

 

NEW QUESTION 97
You are moving an application that uses MySQL from on-premises to Google Cloud. The application will run on Compute Engine and will use Cloud SQL. You want to cut over to the Compute Engine deployment of the application with minimal downtime and no data loss to your customers. You want to migrate the application with minimal modification. You also need to determine the cutover strategy. What should you do?

  • A. 1. Stop the on-premises application.
    2. Create a mysqldump of the on-premises MySQL server.
    3. Upload the dump to a Cloud Storage bucket.
    4. Import the dump into Cloud SQL.
    5. Start the application on Compute Engine.
  • B. 1. Set up Cloud VPN to provide private network connectivity between the Compute Engine application and the on-premises MySQL server.
    2. Stop the on-premises application.
    3. Start the Compute Engine application, configured to read and write to the on-premises MySQL server.
    4. Create the replication configuration in Cloud SQL.
    5. Configure the source database server to accept connections from the Cloud SQL replica.
    6. Finalize the Cloud SQL replica configuration.
    7. When replication has been completed, stop the Compute Engine application.
    8. Promote the Cloud SQL replica to a standalone instance.
    9. Restart the Compute Engine application, configured to read and write to the Cloud SQL standalone instance.
  • C. 1. Set up Cloud SQL proxy and MySQL proxy.
    2. Create a mysqldump of the on-premises MySQL server.
    3. Upload the dump to a Cloud Storage bucket.
    4. Import the dump into Cloud SQL.
    5. Stop the on-premises application.
    6. Start the Compute Engine application.
  • D. 1. Set up Cloud VPN to provide private network connectivity between the Compute Engine application and the on-premises MySQL server.
    2. Stop the on-premises application.
    3. Create a mysqldump of the on-premises MySQL server.
    4. Upload the dump to a Cloud Storage bucket.
    5. Import the dump into Cloud SQL.
    6. Modify the source code of the application to write queries to both databases and read from its local database.
    7. Start the Compute Engine application.
    8. Stop the on-premises application.

Answer: B

Explanation:
External replica promotion migration In the migration strategy of external replica promotion, you create an external database replica and synchronize the existing data to that replica. This can happen with minimal downtime to the existing database. When you have a replica database, the two databases have different roles that are referred to in this document as primary and replica. After the data is synchronized, you promote the replica to be the primary in order to move the management layer with minimal impact to database uptime. In Cloud SQL, an easy way to accomplish the external replica promotion is to use the automated migration workflow. This process automates many of the steps that are needed for this type of migration.
https://cloud.google.com/architecture/migrating-mysql-to-cloudsql-concept
- The best option for migrating your MySQL database is to use an external replica promotion. In this strategy, you create a replica database and set your existing database as the primary. You wait until the two databases are in sync, and you then promote your MySQL replica database to be the primary. This process minimizes database downtime related to the database migration. - https://cloud.google.com/architecture/migrating-mysql-to-cloudsql-concept#external_replica_promotion_migration

 

NEW QUESTION 98
An application development team believes their current logging tool will not meet their needs for their new cloud-based product. They want a better tool to capture errors and help them analyze their historical log data. You want to help them find a solution that meets their needs.
What should you do?

  • A. Direct them to download and install the Google StackDriver logging agent
  • B. Send them a list of online resources about logging best practices
  • C. Help them upgrade their current tool to take advantage of any new features
  • D. Help them define their requirements and assess viable logging tools

Answer: D

 

NEW QUESTION 99
For this question, refer to the Mountkirk Games case study.
Mountkirk Games wants to set up a continuous delivery pipeline. Their architecture includes many small services that they want to be able to update and roll back quickly. Mountkirk Games has the following requirements:
* Services are deployed redundantly across multiple regions in the US and Europe.
* Only frontend services are exposed on the public internet.
* They can provide a single frontend IP for their fleet of services.
* Deployment artifacts are immutable.
Which set of products should they use?

  • A. Google Kubernetes Registry, Google Container Engine, Google HTTP(S) Load Balancer
  • B. Google Cloud Storage, Google Cloud Dataflow, Google Compute Engine
  • C. Google Cloud Storage, Google App Engine, Google Network Load Balancer
  • D. Google Cloud Functions, Google Cloud Pub/Sub, Google Cloud Deployment Manager

Answer: A

Explanation:
Topic 1, Mountkirk Games Case Study 1
Company Overview
Mountkirk Games makes online, session-based. multiplayer games for the most popular mobile platforms.
Company Background
Mountkirk Games builds all of their games with some server-side integration and has historically used cloud providers to lease physical servers. A few of their games were more popular than expected, and they had problems scaling their application servers, MySQL databases, and analytics tools.
Mountkirk's 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.
Technical Requirements
Requirements for Game Backend Platform
1. Dynamically scale up or down based on game activity.
2. Connect to a managed NoSQL database service.
3. Run customized Linx distro.
Requirements for Game Analytics Platform
1. Dynamically scale up or down based on game activity.
2. Process incoming data on the fly directly from the game servers.
3. Process data that arrives late because of slow mobile networks.
4. Allow SQL queries to access at least 10 TB of historical data.
5. Process files that are regularly uploaded by users' mobile devices.
6. Use only fully managed services
CEO Statement
Our last successful game did not scale well with our previous cloud provider, resuming 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 gams to target users.
CTO Statement
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.
CFO Statement
We are not capturing enough user demographic data usage metrics, and other KPIs. As a result, we do not engage the right users. We are not confident that our marketing is targeting the right users, and we are not selling enough premium Blast-Ups inside the games, which dramatically impacts our revenue.

 

NEW QUESTION 100
Your organization has a 3-tier web application deployed in the same network on Google Cloud Platform. Each tier (web, API, and database) scales independently of the others. Network traffic should flow through the web to the API tier and then on to the database tier. Traffic should not flow between the web and the database tier.
How should you configure the network?

  • A. Add each tier to a different subnetwork
  • B. Set up software based firewalls on individual VMs
  • C. Add tags to each tier and set up routes to allow the desired traffic flow
  • D. Add tags to each tier and set up firewall rules to allow the desired traffic flow

Answer: D

Explanation:
Google Cloud Platform(GCP) enforces firewall rules through rules and tags. GCP rules and tags can be defined once and used across all regions.
Reference: https://cloud.google.com/docs/compare/openstack/
https://aws.amazon.com/it/blogs/aws/building-three-tier-architectures-with-security-groups/

 

NEW QUESTION 101
Mountkirk Games has deployed their new backend on Google Cloud Platform (GCP). You want to create a through 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
1. Dynamically scale up or down based on game activity
2. Connect to a managed NoSQL database service
3. Run customize Linux distro

 

NEW QUESTION 102
......

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