2022 Updated Google Professional-Cloud-Architect Dumps PDF - Want To Pass Professional-Cloud-Architect Fast
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Ensuring Operations and Solution Reliability
- Monitor, log, profile, and alert solutions;
- Evaluate quality control measures.
- Assist with solutions support within the operation;
- Deploy and release management;
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NEW QUESTION 135
You need to ensure reliability for your application and operations by supporting reliable task a scheduling for compute on GCP. Leveraging Google best practices, what should you do?
- A. Using the Cron service provided by GKE, publish messages to a Cloud Pub/Sub topic. Subscribe to that topic using a message-processing utility service running on Compute Engine instances.
- B. Using the Cron service provided by App Engine, publish messages to a Cloud Pub/Sub topic. Subscribe to that topic using a message-processing utility service running on Compute Engine instances.
- C. Using the Cron service provided by Google Kubernetes Engine (GKE), publish messages directly to a message-processing utility service running on Compute Engine instances.
- D. Using the Cron service provided by App Engine, publishing messages directly to a message-processing utility service running on Compute Engine instances.
Answer: D
NEW QUESTION 136
You have developed an application using Cloud ML Engine that recognizes famous paintings from uploaded images. You want to test the application and allow specific people to upload images for the next 24 hours. Not all users have a Google Account. How should you have users upload images?
- A. Have users upload the images to Cloud Storage. Protect the bucket with a password that expires after 24 hours.
- B. Create an App Engine web application where users can upload images for the next 24 hours. Authenticate users via Cloud Identity.
- C. Have users upload the images to Cloud Storage using a signed URL that expires after 24 hours.
- D. Create an App Engine web application where users can upload images. Configure App Engine to disable the application after 24 hours. Authenticate users via Cloud Identity.
Answer: A
NEW QUESTION 137
A recent audit revealed that a new network was created in your GCP project. In this network, a GCE instance has an SSH port open to the world. You want to discover this network's origin.
What should you do?
- A. Search for Create VM entry in the Stackdriver alerting console
- B. Connect to the GCE instance using project SSH keys. Identify previous logins in system logs, and match these with the project owners list
- C. In the Logging section of the console, specify GCE Network as the logging section. Search for the Create Insert entry
- D. Navigate to the Activity page in the Home section. Set category to Data Access and search for Create VM entry
Answer: C
Explanation:
Incorrect Answers:
A: To use the Stackdriver alerting console we must first set up alerting policies.
B: Data access logs only contain read-only operations.
Audit logs help you determine who did what, where, and when.
Cloud Audit Logging returns two types of logs:
Admin activity logs
Data access logs: Contains log entries for operations that perform read-only operations do not modify any data, such as get, list, and aggregated list methods.
NEW QUESTION 138
You need to implement a network ingress for a new game that meets the defined business and technical requirements. Mountkirk Games wants each regional game instance to be located in multiple Google Cloud regions. What should you do?
- A. Configure a global load balancer with Google Kubernetes Engine.
- B. Configure a global load balancer connected to a managed instance group running Compute Engine instances.
- C. Configure kubemci with a global load balancer and Google Kubernetes Engine.
- D. Configure Ingress for Anthos with a global load balancer and Google Kubernetes Engine.
Answer: B
NEW QUESTION 139
You have found an error in your App Engine application caused by missing Cloud Datastore indexes. You have created a YAML file with the required indexes and want to deploy these new indexes to Cloud Datastore.
What should you do?
- A. Upload the configuration file the App Engine's default Cloud Storage bucket, and have App Engine detect the new indexes
- B. Point gcloud datastore create-indexes to your configuration file
- C. In the GCP Console, use Datastore Admin to delete the current indexes and upload the new configuration file
- D. Create an HTTP request to the built-in python module to send the index configuration file to your application
Answer: B
Explanation:
Explanation
https://cloud.google.com/datastore/docs/tools/indexconfig#Datastore_Updating_indexes
NEW QUESTION 140
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. Google Kubernetes Engine
- B. Compute Engine
- C. AppEngine flexible environment
- D. Cloud Functions
Answer: D
NEW QUESTION 141
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. Total visits, error rates, and latency from Asia
- B. The number of character sets present in the database
- C. Latency difference between US and Asia
- D. Total visits and average latency for users in Asia
- E. Error rates for requests from Asia
Answer: D
NEW QUESTION 142
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 143
Auditors visit your teams every 12 months and ask to review all the Google Cloud Identity and Access Management (Cloud IAM) policy changes in the previous 12 months. You want to streamline and expedite the analysis and audit process. What should you do?
- A. Use cloud functions to transfer log entries to Google Cloud SQL and use ACLS and views to limit an auditor's view.
- B. Enable Google Cloud Storage (GCS) log export to audit logs Into a GCS bucket and delegate access to the bucket.
- C. Enable Logging export to Google BigQuery and use ACLs and views to scope the data shared with the auditor.
- D. Create custom Google Stackdriver alerts and send them to the auditor.
Answer: C
NEW QUESTION 144
You need to optimize batch file transfers into Cloud Storage for Mountkirk Games' new Google Cloud solution.
The batch files contain game statistics that need to be staged in Cloud Storage and be processed by an extract transform load (ETL) tool. What should you do?
- A. Use gsutil to batch copy the files in parallel.
- B. Use gsutil to extract the files as the first part of ETL.
- C. Use gsutil to load the files as the last part of ETL.
- D. Use gsutil to batch move files in sequence.
Answer: A
NEW QUESTION 145
Your company is migrating its on-premises data center into the cloud. As part of the migration, you want to integrate Kubernetes Engine for workload orchestration. Parts of your architecture must also be PCI DSScompliant.
Which of the following is most accurate?
- A. All Google Cloud services are usable because Google Cloud Platform is certified PCI-compliant.
- B. Kubernetes Engine cannot be used under PCI DSS because it is considered shared hosting.
- C. Kubernetes Engine and GCP provide the tools you need to build a PCI DSS-compliant environment.
- D. App Engine is the only compute platform on GCP that is certified for PCI DSS hosting.
Answer: A
Explanation:
Explanation
https://cloud.google.com/security/compliance/pci-dss
NEW QUESTION 146
For this question, refer to the TerramEarth case study. You are asked to design a new architecture for the ingestion of the data of the 200,000 vehicles that are connected to a cellular network. You want to follow Google-recommended practices.
Considering the technical requirements, which components should you use for the ingestion of the data?
- A. Compute Engine with project-wide SSH keys
- B. Compute Engine with specific SSH keys
- C. Cloud IoT Core with public/private key pairs
- D. Google Kubernetes Engine with an SSL Ingress
Answer: C
Explanation:
Explanation/Reference:
Dress4Win, A
Testlet 1
Company Overview
Dress4Win is a web-based company that helps their users organize and manage their personal wardrobe using a website and mobile application. The company also cultivates an active social network that connects their users with designers and retailers. They monetize their services through advertising, e-commerce, referrals, and a premium app model.
Company Background
Dress4Win's application has grown from a few servers in the founder's garage to several hundred servers and appliances in a collocated data center. However, the capacity of their infrastructure is now insufficient for the application's rapid growth. Because of this growth and the company's desire to innovate faster, Dress4Win is committing to a full migration to a public cloud.
Solution Concept
For the first phase of their migration to the cloud, Dress4Win is considering moving their development and test environments. They are also considering building a disaster recovery site, because their current infrastructure is at a single location. They are not sure which components of their architecture they can migrate as is and which components they need to change before migrating them.
Existing Technical Environment
The Dress4Win application is served out of a single data center location.
* Databases:
- MySQL - user data, inventory, static data
- Redis - metadata, social graph, caching
* Application servers:
- Tomcat - Java micro-services
- Nginx - static content
- Apache Beam - Batch processing
* Storage appliances:
- iSCSI for VM hosts
- Fiber channel SAN - MySQL databases
- NAS - image storage, logs, backups
* Apache Hadoop/Spark servers:
- Data analysis
- Real-time trending calculations
* MQ servers:
- Messaging
- Social notifications
- Events
* Miscellaneous servers:
- Jenkins, monitoring, bastion hosts, security scanners
Business Requirements
* Build a reliable and reproducible environment with scaled parity of production.
* Improve security by defining and adhering to a set of security and Identity and Access Management (IAM) best practices for cloud.
* Improve business agility and speed of innovation through rapid provisioning of new resources.
* Analyze and optimize architecture for performance in the cloud.
* Migrate fully to the cloud if all other requirements are met.
Technical Requirements
* Evaluate and choose an automation framework for provisioning resources in cloud.
* Support failover of the production environment to cloud during an emergency.
* Identify production services that can migrate to cloud to save capacity.
* Use managed services whenever possible.
* Encrypt data on the wire and at rest.
* Support multiple VPN connections between the production data center and cloud environment.
CEO Statement
Our investors are concerned about our ability to scale and contain costs with our current infrastructure. They are also concerned that a new competitor could use a public cloud platform to offset their up-front investment and freeing them to focus on developing better features.
CTO Statement
We have invested heavily in the current infrastructure, but much of the equipment is approaching the end of its useful life. We are consistently waiting weeks for new gear to be racked before we can start new projects. Our traffic patterns are highest in the mornings and weekend evenings; during other times, 80% of our capacity is sitting idle.
CFO Statement
Our capital expenditure is now exceeding our quarterly projections. Migrating to the cloud will likely cause an initial increase in spending, but we expect to fully transition before our next hardware refresh cycle. Our total cost of ownership (TCO) analysis over the next 5 years puts a cloud strategy between 30 to 50% lower than our current model.
NEW QUESTION 147
For this question, refer to the TerramEarth case study.
The TerramEarth development team wants to create an API to meet the company's business requirements. You want the development team to focus their development effort on business value versus creating a custom framework. Which method should they use?
- A. Use Google Container Engine with a Tomcat container with the Swagger (Open API Specification) framework. Focus on an API for dealers and partners.
- B. Use Google App Engine with a JAX-RS Jersey Java-based framework. Focus on an API for the public.
- C. Use Google App Engine with the Swagger (open API Specification) framework. Focus on an API for the public.
- D. Use Google App Engine with Google Cloud Endpoints. Focus on an API for dealers and partners.
- E. Use Google Container Engine with a Django Python container. Focus on an API for the public.
Answer: D
Explanation:
https://cloud.google.com/endpoints/docs/openapi/about-cloud-
endpoints?hl=en_US&_ga=2.21787131.-1712523161.1522785064
https://cloud.google.com/endpoints/docs/openapi/architecture-overview
https://cloud.google.com/storage/docs/gsutil/commands/test
NEW QUESTION 148
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 Kubernetes Registry, Google Container Engine, Google HTTP(S) Load Balancer
- C. Google Cloud Storage, Google Cloud Dataflow, Google Compute Engine
- D. Google Cloud Storage, Google App Engine, Google Network Load Balancer
Answer: D
NEW QUESTION 149
Your company is using BigQuery as its enterprise data warehouse. Data is distributed over several Google Cloud projects. All queries on BigQuery need to be billed on a single project. You want to make sure that no query costs are incurred on the projects that contain the data. Users should be able to query the datasets, but not edit them.
How should you configure users' access roles?
- A. Add all users to a group. Grant the group the roles of BigQuery jobUser on the billing project and BigQuery dataViewer on the projects that contain the data.
- B. Add all users to a group. Grant the group the roles of BigQuery dataViewer on the billing project and BigQuery user on the projects that contain the data.
- C. Add all users to a group. Grant the group the roles of BigQuery dataViewer on the billing project and BigQuery jobUser on the projects that contain the data.
- D. Add all users to a group. Grant the group the role of BigQuery user on the billing project and BigQuery dataViewer on the projects that contain the data.
Answer: A
Explanation:
Reference: https://cloud.google.com/bigquery/docs/running-queries
NEW QUESTION 150
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. Cloud Datastore
- D. BigQuery
Answer: B
Explanation:
Reference:
https://cloud.google.com/blog/products/databases/getting-started-with-time-series-trend-predictions-using-gcp
NEW QUESTION 151
Your organization requires that metrics from all applications be retained for 5 years for future analysis in possible legal proceedings. Which approach should you use?
- A. Configure Stackdriver Monitoring for all Projects with the default retention policies.
- B. Configure Stackdriver Monitoring for all Projects, and export to Google Cloud Storage.
- C. Grant the security team access to the logs in each Project.
- D. Configure Stackdriver Monitoring for all Projects, and export to BigQuery.
Answer: B
Explanation:
Reference:
Overview of storage classes, price, and use cases https://cloud.google.com/storage/docs/storage-classes Why export logs? https://cloud.google.com/logging/docs/export/ StackDriver Quotas and Limits for Monitoring https://cloud.google.com/monitoring/quotas The BigQuery pricing. https://cloud.google.com/bigquery/pricing
NEW QUESTION 152
For this question, refer to the Dress4Win case study. You want to ensure that your on-premises architecture meets business requirements before you migrate your solution.
What change in the on-premises architecture should you make?
- A. Downgrade MySQL to v5.7, which is supported by Cloud SQL for MySQL.
- B. Containerize the micro services and host them in Google Kubernetes Engine.
- C. Resize compute resources to match predefined Compute Engine machine types.
- D. Replace RabbitMQ with Google Pub/Sub.
Answer: C
Explanation:
Topic 6, TerramEarth Case 2
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 the 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 153
Your application needs to process credit card transactions. You want the smallest scope of Payment Card Industry (PCI) compliance without compromising the ability to analyze transactional data and trends relating to which payment methods are used. How should you design your architecture?
- A. Create a tokenizer service and store only tokenized data.
- B. Create separate projects that only process credit card data.
- C. Create separate subnetworks and isolate the components that process credit card data.
- D. Streamline the audit discovery phase by labeling all of the virtual machines (VMs) that process PCI data.
- E. Enable Logging export to Google BigQuery and use ACLs and views to scope the data shared with the auditor.
Answer: A
Explanation:
https://cloud.google.com/solutions/pci-dss-compliance-in-gcp
NEW QUESTION 154
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 a Compute Engine instance with 96 CPUs.
- B. Replace the existing data warehouse with a Compute Engine instance with 96 CPUs. Add an additional Compute Engine pre-emptible instance with 32 CPUs.
- C. Replace the existing data warehouse with BigQuery. Use table partitioning.
- D. Replace the existing data warehouse with BigQuery. Use federated data sources.
Answer: D
Explanation:
Reference:
https://cloud.google.com/solutions/bigquery-data-warehouse#external_sources
https://cloud.google.com/solutions/bigquery-data-warehouse
NEW QUESTION 155
Case Study: 3 - JencoMart Case Study
Company Overview
JencoMart is a global retailer with over 10,000 stores in 16 countries. The stores carry a range of goods, such as groceries, tires, and jewelry. One of the company's core values is excellent customer service. In addition, they recently introduced an environmental policy to reduce their carbon output by 50% over the next 5 years.
Company Background
JencoMart started as a general store in 1931, and has grown into one of the world's leading brands known for great value and customer service. Over time, the company transitioned from only physical stores to a stores and online hybrid model, with 25% of sales online. Currently, JencoMart has little presence in Asia, but considers that market key for future growth.
Solution Concept
JencoMart wants to migrate several critical applications to the cloud but has not completed a technical review to determine their suitability for the cloud and the engineering required for migration. They currently host all of these applications on infrastructure that is at its end of life and is no longer supported.
Existing Technical Environment
JencoMart hosts all of its applications in 4 data centers: 3 in North American and 1 in Europe, most applications are dual-homed.
JencoMart understands the dependencies and resource usage metrics of their on-premises architecture.
Application Customer loyalty portal
LAMP (Linux, Apache, MySQL and PHP) application served from the two JencoMart-owned U.S.
data centers.
Database
* Oracle Database stores user profiles
* PostgreSQL database stores user credentials
-homed in US West
Authenticates all users
Compute
* 30 machines in US West Coast, each machine has:
* 20 machines in US East Coast, each machine has:
-core CPU
Storage
* Access to shared 100 TB SAN in each location
* Tape backup every week
Business Requirements
* Optimize for capacity during peak periods and value during off-peak periods
* Guarantee service availably and support
* Reduce on-premises footprint and associated financial and environmental impact.
* Move to outsourcing model to avoid large upfront costs associated with infrastructure purchase
* Expand services into Asia.
Technical Requirements
* Assess key application for cloud suitability.
* Modify application for the cloud.
* Move applications to a new infrastructure.
* Leverage managed services wherever feasible
* Sunset 20% of capacity in existing data centers
* Decrease latency in Asia
CEO Statement
JencoMart will continue to develop personal relationships with our customers as more people access the web. The future of our retail business is in the global market and the connection between online and in-store experiences. As a large global company, we also have a responsibility to the environment through 'green' initiatives and polices.
CTO Statement
The challenges of operating data centers prevents focus on key technologies critical to our long- term success. Migrating our data services to a public cloud infrastructure will allow us to focus on big data and machine learning to improve our service customers.
CFO Statement
Since its founding JencoMart has invested heavily in our data services infrastructure. However, because of changing market trends, we need to outsource our infrastructure to ensure our long- term success. This model will allow us to respond to increasing customer demand during peak and reduce costs.
For this question, refer to the JencoMart case study.
JencoMart wants to move their User Profiles database to Google Cloud Platform. Which Google Database should they use?
- A. Cloud Spanner
- B. Google Cloud SQL
- C. Google Cloud Datastore
- D. Google BigQuery
Answer: C
Explanation:
Common workloads for Google Cloud Datastore:
User profiles
* Product catalogs
* Game state
* References: https://cloud.google.com/storage-options/
https://cloud.google.com/datastore/docs/concepts/overview
NEW QUESTION 156
Your company creates rendering software which users can download from the company website. Your company has customers all over the world. You want to minimize latency for all your customers. You want to follow Google-recommended practices.
How should you store the files?
- A. Save the files in multiple Regional Cloud Storage buckets, one bucket per zone per region.
- B. Save the files in a Regional Cloud Storage bucket, one bucket per zone of the region.
- C. Save the files in multiple Multi-Regional Cloud Storage buckets, one bucket per multi-region.
- D. Save the files in a Multi-Regional Cloud Storage bucket.
Answer: B
NEW QUESTION 157
For this question, refer to the Mountkirk Games case study
Mountkirk Games needs to create a repeatable and configurable mechanism for deploying isolated application environments. Developers and testers can access each other's environments and resources, but they cannot access staging or production resources. The staging environment needs access to some services from production.
What should you do to isolate development environments from staging and production?
- A. Create a network for development and test and another for staging and production.
- B. Create a project for development and test and another for staging and production.
- C. Create one subnetwork for development and another for staging and production.
- D. Create one project for development, a second for staging and a third for production.
Answer: D
Explanation:
Topic 6, Mountkrik Games Case 3
Company overview
Mountkirk Games makes online, session-based, multiplayer games for mobile platforms. They have recently started expanding to other platforms after successfully migrating their on-premises environments to Google Cloud.
Their most recent endeavor is to create a retro-style first-person shooter (FPS) game that allows hundreds of simultaneous players to join a geo-specific digital arena from multiple platforms and locations. A real-time digital banner will display a global leaderboard of all the top players across every active arena.
Solution concept
Mountkirk Games is building a new multiplayer game that they expect to be very popular. They plan to deploy the game's backend on Google Kubernetes Engine so they can scale rapidly and use Google's global load balancer to route players to the closest regional game arenas. In order to keep the global leader board in sync, they plan to use a multi-region Spanner cluster.
Existing technical environment
The existing environment was recently migrated to Google Cloud, and five games came across using lift-and-shift virtual machine migrations, with a few minor exceptions. Each new game exists in an isolated Google Cloud project nested below a folder that maintains most of the permissions and network policies. Legacy games with low traffic have been consolidated into a single project. There are also separate environments for development and testing.
Business requirements
Support multiple gaming platforms.
Support multiple regions.
Support rapid iteration of game features.
Minimize latency.
Optimize for dynamic scaling.
Use managed services and pooled resources.
Minimize costs.
Technical requirements
Dynamically scale based on game activity.
Publish scoring data on a near real-time global leaderboard.
Store game activity logs in structured files for future analysis.
Use GPU processing to render graphics server-side for multi-platform support.
Support eventual migration of legacy games to this new platform.
Executive statement
Our last game was the first time we used Google Cloud, and it was a tremendous success. We were able to analyze player behavior and game telemetry in ways that we never could before. This success allowed us to bet on a full migration to the cloud and to start building all-new games using cloud-native design principles. Our new game is our most ambitious to date and will open up doors for us to support more gaming platforms beyond mobile. Latency is our top priority, although cost management is the next most important challenge. As with our first cloud-based game, we have grown to expect the cloud to enable advanced analytics capabilities so we can rapidly iterate on our deployments of bug fixes and new functionality.
NEW QUESTION 158
Your customer is moving their corporate applications to Google Cloud Platform. The security team wants detailed visibility of all projects in the organization. You provision the Google Cloud Resource Manager and set up yourself as the org admin. What Google Cloud Identity and Access Management (Cloud IAM) roles should you give to the security team'?
- A. Org viewer, project owner
- B. Org admin, project browser
- C. Project owner, network admin
- D. Org viewer, project viewer
Answer: D
Explanation:
Explanation
https://cloud.google.com/iam/docs/using-iam-securely
NEW QUESTION 159
The operations manager asks you for a list of recommended practices that she should consider when migrating a J2EE application to the cloud. Which three practices should you recommend? Choose 3 answers
- A. Deploy a continuous integration tool with automated testing in a staging environment.
- B. Select an automation framework to reliably provision the cloud infrastructure.
- C. Migrate from MySQL to a managed NoSQL database like Google Cloud Datastore or Bigtable.
- D. Instrument the application with a monitoring tool like Stackdriver Debugger.
- E. Integrate Cloud Dataflow into the application to capture real-time metrics.
- F. Port the application code to run on Google App Engine.
Answer: A,C,F
Explanation:
Explanation
References: https://cloud.google.com/appengine/docs/standard/java/tools/uploadinganapp
https://cloud.google.com/appengine/docs/standard/java/building-app/cloud-sql
NEW QUESTION 160
......
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