Pass Your Google Cloud Certified Professional-Cloud-Architect Exam on Apr 25, 2024 with 278 Questions
Professional-Cloud-Architect Free Exam Study Guide! (Updated 278 Questions)
Managing Implementation
- Advice development and operation team to ensure the successful deployment of solutions: the areas of focus include application development; AIP best practices; data and system migration tool; testing framework;
- Interact with Google Cloud with the use of GCP SDK: this requires the test takers’ understanding of Google Cloud Shell and local installation.
The Google Professional-Cloud-Architect exam is designed to test the candidate's knowledge of GCP, including its features, services, and capabilities. Professional-Cloud-Architect exam evaluates the candidate's abilities in designing, planning, and managing GCP solutions. To pass the exam, the candidate must have a deep understanding of GCP architecture and be able to design and implement solutions that are reliable, scalable, and secure.
The Google Certified Professional - Cloud Architect (GCP) certification is valid for two years and can be renewed by passing the current version of the Professional-Cloud-Architect exam. In addition to demonstrating expertise in GCP, the certification also demonstrates the candidate's ability to work with cloud technologies and solutions in general, making it a valuable asset for IT professionals who work in cloud-related fields.
NEW QUESTION # 27
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 App Engine, Google Network Load Balancer
- B. Google Cloud Functions, Google Cloud Pub/Sub, Google Cloud Deployment Manager
- C. Google Cloud Storage, Google Cloud Dataflow, Google Compute Engine
- D. Google Kubernetes Registry, Google Container Engine, Google HTTP(S) Load Balancer
Answer: D
Explanation:
Topic 3, TerramEarth
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 # 28
The Dress4Win security team has disabled external SSH access into production virtual machines (VMs) on
Google Cloud Platform (GCP).
The operations team needs to remotely manage the VMs, build and push Docker containers, and manage
Google Cloud Storage objects.
What can they do?
- A. Have the development team build an API service that allows the operations team to execute specific
remote procedure calls to accomplish their tasks. - B. Develop a new access request process that grants temporary SSH access to cloud VMs when an
operations engineer needs to perform a task. - C. Configure a VPN connection to GCP to allow SSH access to the cloud VMs.
- D. Grant the operations engineer access to use Google Cloud Shell.
Answer: C
NEW QUESTION # 29
Your organization has 5 TB of private data on premises. You need to migrate the data to Cloud Storage. You want to maximize the data transfer speed. How should you migrate the data?
- A. Use gsutil.
- B. Use Storage Transfer Service.
- C. Use GCS REST API.
- D. Use gcloud.
Answer: A
Explanation:
A is correct because gsutil gives you access to write data to Cloud Storage.
B is not correct because gcloud is the command-line interface for common platform tasks and does not include accessing Cloud Storage.
C is not correct because the data size would require a resumable upload, and that does not meet the requirement of maximizing the data transfer speed.
D is not correct because Storage Transfer Service is for importing online data, not on-premises.
Your data source can be an Amazon Simple Storage Service (Amazon S3) bucket, an HTTP/HTTPS location, or a Cloud Storage bucket.
https://cloud.google.com/storage/docs/gsutil
https://cloud.google.com/sdk/gcloud/
https://cloud.google.com/storage/docs/json_api/v1/how-tos/upload
https://cloud.google.com/storage/docs/uploading-objects
https://cloud.google.com/storage-transfer/docs/overview
NEW QUESTION # 30
You are responsible for the Google Cloud environment in your company Multiple departments need access to their own projects and the members within each department will have the same project responsibilities You want to structure your Google Cloud environment for minimal maintenance and maximum overview of 1AM permissions as each department's projects start and end You want to follow Google-recommended practices What should you do?
- A. Grant all department members the required 1AM permissions for their respective projects
- B. Create a Google Group per department and add all department members to their respective groups Grant each group the required I AM permissions for their respective projects
- C. Create a Google Group per department and add all department members to their respective groups Create a folder per department and grant the respective group the required 1AM permissions at the folder level Add the projects under the respective folders
- D. Create a folder per department and grant the respective members of the department the required 1AM permissions at the folder level. Structure all projects for each department under the respective folders
Answer: C
Explanation:
This option follows the Google-recommended practices for structuring a Google Cloud environment for minimal maintenance and maximum overview of IAM permissions. By creating a Google Group per department and adding all department members to their respective groups, you can simplify user management and avoid granting IAM permissions to individual users. By creating a folder per department and granting the respective group the required IAM permissions at the folder level, you can enforce consistent policies across all projects within each department and avoid granting IAM permissions at the project level. By adding the projects under the respective folders, you can organize your resources hierarchically and leverage inheritance of IAM policies from folders to projects. The other options are not optimal for this scenario, because they either require granting IAM permissions to individual users (B, C), or do not use Google Groups to manage users (D). Reference:
https://cloud.google.com/architecture/framework/system-design
https://cloud.google.com/architecture/identity/best-practices-for-planning
https://cloud.google.com/resource-manager/docs/creating-managing-folders
NEW QUESTION # 31
Your company plans to migrate a multi-petabyte data set to the cloud. The data set must be available 24hrs a day. Your business analysts have experience only with using a SQL interface.
How should you store the data to optimize it for ease of analysis?
- A. Load data into Google BigQuery
- B. Stream data into Google Cloud Datastore
- C. Put flat files into Google Cloud Storage
- D. Insert data into Google Cloud SQL
Answer: A
Explanation:
Explanation
Explanation:
BigQuery is Google's serverless, highly scalable, low cost enterprise data warehouse designed to make all your data analysts productive. Because there is no infrastructure to manage, you can focus on analyzing data to find meaningful insights using familiar SQL and you don't need a database administrator.
BigQuery enables you to analyze all your data by creating a logical data warehouse over managed, columnar storage as well as data from object storage, and spreadsheets.
Reference: https://cloud.google.com/bigquery/
NEW QUESTION # 32
For this question, refer to the TerramEarth case study.
TerramEarth plans to connect all 20 million vehicles in the field to the cloud. This increases the volume to 20 million 600 byte records a second for 40 TB an hour. How should you design the data ingestion?
- A. Vehicles write data directly to GCS.
- B. Vehicles stream data directly to Google BigQuery.
- C. Vehicles continue to write data using the existing system (FTP).
- D. Vehicles write data directly to Google Cloud Pub/Sub.
Answer: D
Explanation:
Explanation: Scale to hundreds of millions of messages per second and pay only for the resources you use. There are no partitions or local instances to manage, reducing operational overhead. Data is automatically and intelligently distributed across data centers over our unique, high-speed private network.
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.
https://cloud.google.com/pubsub/
NEW QUESTION # 33
You need to deploy an application to Google Cloud. The application receives traffic via TCP and reads and writes data to the filesystem. The application does not support horizontal scaling. The application process requires full control over the data on the file system because concurrent access causes corruption. The business is willing to accept a downtime when an incident occurs, but the application must be available 24/7 to support their business operations. You need to design the architecture of this application on Google Cloud.
What should you do?
- A. Use an unmanaged instance group with an active and standby instance in different zones, use a regional persistent disk, and use a network load balancer in front of the instances.
- B. Use a managed instance group with instances in multiple zones, use Cloud Filestore, and use an HTTP load balancer in front of the instances.
- C. Use a managed instance group with instances in multiple zones, use Cloud Filestore, and use a network load balancer in front of the instances.
- D. Use an unmanaged instance group with an active and standby instance in different zones, use a regional persistent disk, and use an HTTP load balancer in front of the instances.
Answer: A
Explanation:
Reference: https://cloud.google.com/compute/docs/instance-groups
NEW QUESTION # 34
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 Functions, Google Cloud Pub/Sub, Google Cloud Deployment Manager
- B. Google Cloud Storage, Google App Engine, Google Network Load Balancer
- C. Google Kubernetes Registry, Google Container Engine, Google HTTP(S) Load Balancer
- D. Google Cloud Storage, Google Cloud Dataflow, Google Compute Engine
Answer: A
Explanation:
Explanation/Reference:
Explanation:
Google Cloud Functions is a serverless environment to build and connect cloud services.
Google Cloud Pub/Sub brings the scalability, flexibility, and reliability of enterprise message-oriented
middleware to the cloud. By providing many-to-many, asynchronous messaging that decouples senders
and receivers, it allows for secure and highly available communication between independently written
applications. Google Cloud Pub/Sub delivers low-latency, durable messaging that helps developers quickly
integrate systems hosted on the Google Cloud Platform and externally.
Incorrect Answers:
A: Cloud Dataflow is a fully-managed service for transforming and enriching data in stream (real time) and
batch (historical) modes.
C: Store your private Docker container images on Cloud Platform for fast, scalable retrieval and
deployment. Container Registry is a private Docker repository that works with popular continuous delivery
systems. It runs on Cloud Platform to provide consistent uptime on an infrastructure protected by Google's
security. You pay only for storage and internet egress you use, there is no per-image fee.
Reference: https://cloud.google.com/load-balancing/
https://cloud.google.com/solutions/ansible-with-spinnaker-tutorial
http://blog.armory.io/what-is-immutable-infrastructure/
https://cloud.google.com/compute/docs/load-balancing/http/
NEW QUESTION # 35
TerramEarth's 20 million vehicles are scattered around the world. Based on the vehicle's location, its telemetry data is stored in a Google Cloud Storage (GCS) regional bucket (US, Europe, or Asia). The CTO has asked you to run a report on the raw telemetry data to determine why vehicles are breaking down after 100 K miles.
You want to run this job on all the data.
What is the most cost-effective way to run this job?
- A. Launch a cluster in each region to preprocess and compress the raw data, then move the data into a multi- region bucket and use a Dataproc cluster to finish the job
- B. Move all the data into 1 zone, then launch a Cloud Dataproc cluster to run the job
- C. Move all the data into 1 region, then launch a Google Cloud Dataproc cluster to run the job
- D. Launch a cluster in each region to preprocess and compress the raw data, then move the data into a region bucket and use a Cloud Dataproc cluster to finish the job
Answer: D
NEW QUESTION # 36
You are developing a globally scaled frontend for a legacy streaming backend data API. This API expects events in strict chronological order with no repeat data for proper processing.
Which products should you deploy to ensure guaranteed-once FIFO (first-in, first-out) delivery of data?
- A. Cloud Pub/Sub to Stackdriver
- B. Cloud Pub/Sub to Cloud DataFlow
- C. Cloud Pub/Sub alone
- D. Cloud Pub/Sub to Cloud SQL
Answer: B
Explanation:
Explanation
Reference https://cloud.google.com/pubsub/docs/ordering
NEW QUESTION # 37
For this question, refer to the TerramEarth case study.
You start to build a new application that uses a few Cloud Functions for the backend. One use case requires a Cloud Function func_display to invoke another Cloud Function func_query. You want func_query only to accept invocations from func_display. You also want to follow Google's recommended best practices. What should you do?
- A. Create a token and pass it in as an environment variable to func_display. When invoking func_query, include the token in the request Pass the same token to func _query and reject the invocation if the tokens are different.
- B. Make func _query 'Require authentication' and only accept internal traffic. Create those two functions in the same VPC. Create an ingress firewall rule for func_query to only allow traffic from func_display.
- C. Make func_query 'Require authentication.' Create a unique service account and associate it to func_display. Grant the service account invoker role for func_query. Create an id token in func_display and include the token to the request when invoking func_query.
- D. Create those two functions in the same project and VPC. Make func_query only accept internal traffic. Create an ingress firewall for func_query to only allow traffic from func_display. Also, make sure both functions use the same service account.
Answer: C
Explanation:
https://cloud.google.com/functions/docs/securing/authenticating#authenticating_function_to_function_calls
NEW QUESTION # 38
A production database virtual machine on Google Compute Engine has an ext4-formatted persistent disk for data files The database is about to run out of storage space How can you remediate the problem with the least amount of downtime?
- A. In the Cloud Platform Console, increase the size of the persistent disk and use the resize2fs command in Linux.
- B. In the Cloud Platform Console, create a new persistent disk attached to the virtual machine, format and mount it, and configure the database service to move the files to the new disk.
- C. Shut down the virtual machine, use the Cloud Platform Console to increase the persistent disk size, then restart the virtual machine.
- D. In the Cloud Platform Console, create a snapshot of the persistent disk, restore the snapshot to a new larger disk, unmount the old disk, mount the new disk, and restart the database service.
- E. In the Cloud Platform Console, increase the size of the persistent disk and verify the new space is ready to use with the fdisk command in Linux.
Answer: A
Explanation:
On Linux instances, connect to your instance and manually resize your partitions and file systems to use the additional disk space that you added.
Extend the file system on the disk or the partition to use the added space. If you grew a partition on your disk, specify the partition. If your disk does not have a partition table, specify only the disk ID.
sudo resize2fs /dev/[DISK_ID][PARTITION_NUMBER]
where [DISK_ID] is the device name and [PARTITION_NUMBER] is the partition number for the device where you are resizing the file system.
NEW QUESTION # 39
Mountkirk Games' gaming servers are not automatically scaling properly. Last month, they rolled out a new feature, which suddenly became very popular. A record number of users are trying to use the service, but many of them are getting 503 errors and very slow response times. What should they investigate first?
- A. Verify that the new feature code did not introduce any performance bugs
- B. Verify that the database is online
- C. Verify that the load-testing team is not running their tool against production
- D. Verify that the project quota hasn't been exceeded
Answer: D
Explanation:
Explanation: 503 is service unavailable error. If the database was online everyone would get the 503 error.
NEW QUESTION # 40
Your solution is producing performance bugs in production that you did not see in staging and test environments. You want to adjust your test and deployment procedures to avoid this problem in the future.
What should you do?
- A. Deploy smaller changes to production
- B. Deploy changes to a small subset of users before rolling out to production
- C. Deploy fewer changes to production
- D. Increase the load on your test and staging environments
Answer: B
Explanation:
Explanation
NEW QUESTION # 41
For this question, refer to the Mountkirk Games case study.
Mountkirk Games wants to set up a real-time analytics platform for their new game. The new platform must meet their technical requirements. Which combination of Google technologies will meet all of their requirements?
- A. Cloud Pub/Sub, Compute Engine, Cloud Storage, and Cloud Dataproc
- B. Cloud SQL, Cloud Storage, Cloud Pub/Sub, and Cloud Dataflow
- C. Cloud Dataproc, Cloud Pub/Sub, Cloud SQL, and Cloud Dataflow
- D. Container Engine, Cloud Pub/Sub, and Cloud SQL
- E. Cloud Dataflow, Cloud Storage, Cloud Pub/Sub, and BigQuery
Answer: E
Explanation:
A real time requires Stream / Messaging so Pub/Sub, Analytics by Big Query.
Ingest millions of streaming events per second from anywhere in the world with Cloud Pub/Sub, powered by Google's unique, high-speed private network. Process the streams with Cloud Dataflow to ensure reliable, exactly-once, low-latency data transformation. Stream the transformed data into BigQuery, the cloud-native data warehousing service, for immediate analysis via SQL or popular visualization tools.
From scenario: They plan to deploy the game's backend on Google Compute Engine so they can capture streaming metrics, run intensive analytics.
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 SQL queries to access at least 10 TB of historical data
* Process files that are regularly uploaded by users' mobile devices
* Use only fully managed services
References:
https://cloud.google.com/solutions/big-data/stream-analytics/
NEW QUESTION # 42
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. You need to analyze and define the technical architecture for the database workloads for your company, Mountkirk Games.
Considering the business and technical requirements, what should you do?
- A. Use Cloud Bigtable for time series data, use Cloud Spanner for transactional data, and use BigQuery for historical data queries.
- B. Use Cloud SQL to replace MySQL, and use Cloud Spanner for historical data queries.
- C. Use Cloud SQL for time series data, and use Cloud Bigtable for historical data queries.
- D. Use Cloud Bigtable to replace MySQL, and use BigQuery for historical data queries.
Answer: A
NEW QUESTION # 43
Your company is building a new architecture to support its data-centric business focus. You are responsible for setting up the network. Your company's mobile and web-facing applications will be deployed on-premises, and all data analysis will be conducted in GCP. The plan is to process and load 7 years of archived .csv files totaling 900 TB of data and then continue loading 10 TB of data daily. You currently have an existing 100-MB internet connection.
What actions will meet your company's needs?
- A. Lease a Transfer Appliance, upload archived files to it, and send it, and send it to Google to transfer archived data to Cloud Storage. Establish one Cloud VPN Tunnel to VPC networks over the public internet, and compares and upload files daily using the gsutil -m option.
- B. Lease a Transfer Appliance, upload archived files to it, and send it, and send it to Google to transfer archived data to Cloud Storage. Establish a connection with Google using a Dedicated Interconnect or Direct Peering connection and use it to upload files daily.
- C. Compress and upload both achieved files and files uploaded daily using the qsutil -m option.
- D. Lease a Transfer Appliance, upload archived files to it, and send it to Google to transfer archived data to Cloud Storage. Establish a Cloud VPN Tunnel to VPC networks over the public internet, and compress and upload files daily.
Answer: B
Explanation:
Explanation
https://cloud.google.com/interconnect/docs/how-to/direct-peering
NEW QUESTION # 44
You are implementing the infrastructure for a web service on Google Cloud. The web service needs to receive and store the data from 500,000 requests per second. The data will be queried later in real time, based on exact matches of a known set of attributes. There will be periods where the web service will not receive any requests. The business wants to keep costs low. Which web service platform and database should you use for the application?
- A. Cloud Run and BigQuery
- B. A Compute Engine autoscaling managed instance group and BigQuery
- C. Cloud Run and Cloud Bigtable
- D. A Compute Engine autoscaling managed instance group and Cloud Bigtable
Answer: D
NEW QUESTION # 45
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 App Engine, Google Network Load Balancer
- B. Google Cloud Functions, Google Cloud Pub/Sub, Google Cloud Deployment Manager
- C. Google Cloud Storage, Google Cloud Dataflow, Google Compute Engine
- D. Google Kubernetes Registry, Google Container Engine, Google HTTP(S) Load Balancer
Answer: D
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 # 46
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 Container Engine with Bigtable
- B. Google Cloud Dataflow
- C. Google Cloud Dataproc
- D. Google Compute Engine with Google BigQuery
Answer: B
NEW QUESTION # 47
A lead engineer wrote a custom tool that deploys virtual machines in the legacy data center. He wants to migrate the custom tool to the new cloud environment. You want to advocate for the adoption of Google Cloud Deployment Manager.
What are two business risks of migrating to Cloud Deployment Manager? Choose 2 answers.
- A. Cloud Deployment Manager APIs could be deprecated in the future
- B. Cloud Deployment Manager uses Python
- C. Cloud Deployment Manager requires a Google APIs service account to run
- D. Cloud Deployment Manager can be used to permanently delete cloud resources
- E. Cloud Deployment Manager only supports automation of Google Cloud resources
- F. Cloud Deployment Manager is unfamiliar to the company's engineers
Answer: A,E
Explanation:
Explanation/Reference:
NEW QUESTION # 48
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