[Oct 12, 2024] Dumps Collection Professional-Cloud-Architect Test Engine Dumps Training With 282 Questions
Google Professional-Cloud-Architect Dumps - 100% Cover Real Exam Questions
Earning the Google Professional-Cloud-Architect certification can demonstrate to potential employers and clients that you have the skills and knowledge needed to design and implement effective cloud solutions using GCP. Google Certified Professional - Cloud Architect (GCP) certification can also help you stand out in a competitive job market and potentially lead to higher salaries and career advancement opportunities.
The Google Professional-Cloud-Architect exam is made up of multiple-choice questions that cover a range of topics, including cloud architecture, security, networking, and data management. Candidates are expected to have a strong understanding of cloud computing technologies and best practices, as well as the ability to apply this knowledge to real-world scenarios. Professional-Cloud-Architect exam is designed to be challenging, with a passing score of 70% required to earn the certification.
NEW QUESTION # 105
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 SQL for time series data, and use Cloud Bigtable for historical data queries.
- B. Use Cloud SQL to replace MySQL, and use Cloud Spanner for historical data queries.
- C. Use Cloud Bigtable to replace MySQL, and use BigQuery for historical data queries.
- D. Use Cloud Bigtable for time series data, use Cloud Spanner for transactional data, and use BigQuery for historical data queries.
Answer: D
NEW QUESTION # 106
You want to enable your running Google Container Engine cluster to scale as demand for your application changes.
What should you do?
- A. Update the existing Container Engine cluster with the following command:
gcloud alpha container clusters
update mycluster - -enable-
autoscaling - -min-nodes=1 - -max-nodes=10 - B. Create a new Container Engine cluster with the following command:
gcloud alpha container clusters
create mycluster - -enable-
autoscaling - -min-nodes=1 - -max-nodes=10
and redeploy your application - C. Add a tag to the instances in the cluster with the following command:
gcloud compute instances add-tags
INSTANCE - -tags enable-
autoscaling max-nodes-10 - D. Add additional nodes to your Container Engine cluster using the following command:
gcloud container clusters resize
CLUSTER_Name - -size 10
Answer: C
Explanation:
Explanation/Reference:
Explanation:
Cluster autoscaling
--enable-autoscaling
Enables autoscaling for a node pool.
Enables autoscaling in the node pool specified by --node-pool or the default node pool if --node-pool is not provided.
Where:
--max-nodes=MAX_NODES
Maximum number of nodes in the node pool.
Maximum number of nodes to which the node pool specified by --node-pool (or default node pool if unspecified) can scale.
Incorrect Answers:
C, D: Warning: Do not use Alpha Clusters or alpha features for production workloads.
Note: You can experiment with Kubernetes alpha features by creating an alpha cluster. Alpha clusters are short-lived clusters that run stable Kubernetes releases with all Kubernetes APIs and features enabled.
Alpha clusters are designed for advanced users and early adopters to experiment with workloads that take advantage of new features before those features are production-ready. You can use Alpha clusters just like normal Kubernetes Engine clusters.
References: https://cloud.google.com/sdk/gcloud/reference/container/clusters/create
NEW QUESTION # 107
Case Study: 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.
For this question, refer to the TerramEarth case study. TerramEarth's CTO wants to use the raw data from connected vehicles to help identify approximately when a vehicle in the field will have a catastrophic failure. You want to allow analysts to centrally query the vehicle data. Which architecture should you recommend?
- A.
- B.
- C.
- D.
Answer: B
Explanation:
The push endpoint can be a load balancer.
A container cluster can be used.
Cloud Pub/Sub for Stream Analytics
References: https://cloud.google.com/pubsub/
https://cloud.google.com/solutions/iot/
https://cloud.google.com/solutions/designing-connected-vehicle-platform
https://cloud.google.com/solutions/designing-connected-vehicle-platform#data_ingestion
http://www.eweek.com/big-data-and-analytics/google-touts-value-of-cloud-iot-core-for-analyzing- connected-car-data
https://cloud.google.com/solutions/iot/
NEW QUESTION # 108
A development manager is building a new application He asks you to review his requirements and identify what cloud technologies he can use to meet them.
The application must:
1. Be based on open-source technology for cloud portability
2. Dynamically scale compute capacity based on demand
3. Support continuous software delivery
4. Run multiple segregated copies of the same application stack
5. Deploy application bundles using dynamic templates
6. Route network traffic to specific services based on URL
Which combination of technologies will meet all of his requirements?
- A. Google Container Engine, Jenkins, and Helm
- B. Google Container Engine and Cloud Load Balancing
- C. Google Compute Engine and Cloud Deployment Manager
- D. Google Compute Engine, Jenkins, and Cloud Load Balancing
Answer: D
Explanation:
Jenkins is an open-source automation server that lets you flexibly orchestrate your build, test, and deployment pipelines. Kubernetes Engine is a hosted version of Kubernetes, a powerful cluster manager and orchestration system for containers.
When you need to set up a continuous delivery (CD) pipeline, deploying Jenkins on Kubernetes Engine provides important benefits over a standard VM-based deployment Incorrect Answers:
A: Helm is a tool for managing Kubernetes charts. Charts are packages of pre-configured Kubernetes resources.
Use Helm to:
Find and use popular software packaged as Kubernetes charts
* Share your own applications as Kubernetes charts
* Create reproducible builds of your Kubernetes applications
* Intelligently manage your Kubernetes manifest files
* Manage releases of Helm packages
* References: https://cloud.google.com/solutions/jenkins-on-kubernetes-engine
NEW QUESTION # 109
For this question, refer to the Dress4Win case study. To be legally compliant during an audit, Dress4Win must be able to give insights in all administrative actions that modify the configuration or metadata of resources on Google Cloud.
What should you do?
- A. Use Stackdriver Trace to create a trace list analysis.
- B. Enable Cloud Identity-Aware Proxy in all projects, and add the group of Administrators as a member.
- C. Use Stackdriver Monitoring to create a dashboard on the project's activity.
- D. Use the Activity page in the GCP Console and Stackdriver Logging to provide the required insight.
Answer: A
Explanation:
Explanation
https://cloud.google.com/logging/docs/audit/
NEW QUESTION # 110
Your company has a Google Cloud project that uses BigQuery for data warehousing on a pay-per-use basis.
You want to monitor queries in real time to discover the most costly queries and which users spend the most.
What should you do?
- A. 1. Activate billing export into BigQuery.
2. Perform a BigQuery query on the billing table to extract the information you need. - B. 1. Create a Cloud Logging sink to export BigQuery data access logs to BigQuery.
2. Perform a BigQuery query on the generated table to extract the information you need. - C. 1. In the BigQuery dataset that contains all the tables to be queried, add a label for each user that can launch a query.
2. Open the Billing page of the project.
3. Select Reports.
4. Select BigQuery as the product and filter by the user you want to check. - D. 1. Create a Cloud Logging sink to export BigQuery data access logs to Cloud Storage. 2. Develop a Dataflow pipeline to compute the cost of queries split by users.
Answer: A
Explanation:
https://cloud.google.com/blog/products/data-analytics/taking-a-practical-approach-to-bigquery-cost-monitoring
NEW QUESTION # 111
The development team has provided you with a Kubernetes Deployment file. You have no infrastructure yet and need to deploy the application. What should you do?
- A. Use kubectl to create a Kubernetes cluster. Use kubectl to create the deployment.
- B. Use kubectl to create a Kubernetes cluster. Use Deployment Manager to create the deployment.
- C. Use gcloud to create a Kubernetes cluster. Use kubectl to create the deployment.
- D. Use gcloud to create a Kubernetes cluster. Use Deployment Manager to create the deployment.
Answer: C
Explanation:
Explanation
https://cloud.google.com/kubernetes-engine/docs/how-to/creating-a-cluster
NEW QUESTION # 112
Case Study: 1 - Mountkirk Games Case Study
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.
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 Functions, Google Cloud Pub/Sub, Google Cloud Deployment Manager
- C. Google Container Registry, Google Container Engine, Google HTTP(s) Load Balancer
- D. Google Cloud Storage, Google App Engine, Google Network Load Balancer
Answer: B
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 # 113
Your organization wants to control IAM policies for different departments independently, but centrally.
Which approach should you take?
- A. Multiple Organizations, one for each department
- B. A single Organization with Folders for each department
- C. Multiple Organizations with multiple Folders
- D. A single Organization with multiple projects, each with a central owner
Answer: B
Explanation:
Folders are nodes in the Cloud Platform Resource Hierarchy. A folder can contain projects, other folders, or a combination of both. You can use folders to group projects under an organization in a hierarchy. For example, your organization might contain multiple departments, each with its own set of GCP resources. Folders allow you to group these resources on a per-department basis. Folders are used to group resources that share common IAM policies. While a folder can contain multiple folders or resources, a given folder or resource can have exactly one parent.
References: https://cloud.google.com/resource-manager/docs/creating-managing-folders
NEW QUESTION # 114
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. 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. - B. 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. - C. 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. - D. 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.
Answer: C
NEW QUESTION # 115
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. 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. - B. 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. - C. 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. - D. 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.
Answer: C
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 # 116
A news teed web service has the following code running on Google App Engine. During peak load, users report that they can see news articles they already viewed. What is the most likely cause of this problem?
- A. The session variable is local to just a single instance.
- B. The session variable is being overwritten in Cloud Datastore.
- C. The HTTP Expires header needs to be set to -1 to stop caching.
- D. The URL of the API needs to be modified to prevent caching.
Answer: A
Explanation:
Reference:
https://stackoverflow.com/questions/3164280/google-app-engine-cache-list-in-session-variable?rq=1
NEW QUESTION # 117
You need to reduce the number of unplanned rollbacks of erroneous production deployments in your company's web hosting platform. Improvement to the QA/Test processes accomplished an
80% reduction. Which additional two approaches can you take to further reduce the rollbacks?
Choose 2 answers
- A. Reduce the platform's dependency on relational database systems.
- B. Fragment the monolithic platform into microservices.
- C. Replace the platform's relational database systems with a NoSQL database.
- D. Introduce a green-blue deployment model.
- E. Replace the QA environment with canary releases.
Answer: B,D
NEW QUESTION # 118
For this question, refer to the TerramEarth case study. You are building a microservice-based application for TerramEarth. The application is based on Docker containers. You want to follow Google-recommended practices to build the application continuously and store the build artifacts. What should you do?
- A. 1. Configure a trigger in Cloud Build for new source changes.
2. Invoke Cloud Build to build container images for each microservice, and tag them using the code commit hash.
3. Push the images to the Artifact Registry. - B. 1. Configure a trigger in Cloud Build for new source changes.
2. The trigger invokes build jobs and build container images for the microservices.
3. Tag the images with a version number, and push them to Cloud Storage. - C. 1. Configure a trigger in Cloud Build for new source changes.
2. Invoke Cloud Build to build one container image, and tag the image with the label 'latest.'
3. Push the image to the Artifact Registry. - D. 1 Create a Scheduler job to check the repo every minute.
2. For any new change, invoke Cloud Build to build container images for the microservices.
3. Tag the images using the current timestamp, and push them to the Artifact Registry.
Answer: D
NEW QUESTION # 119
Your development team has installed a new Linux kernel module on the batch servers in Google Compute Engine (GCE) virtual machines (VMs) to speed up the nightly batch process. Two days after the installation,
50% of web application deployed in the same
nightly batch run. You want to collect details on the failure to pass back to the development team. Which three actions should you take? Choose 3 answers
- A. Use Stackdriver Logging to search for the module log entries.
- B. Adjust the Google Stackdriver timeline to match the failure time, and observe the batch server metrics.
- C. Identify whether a live migration event of the failed server occurred, using in the activity log.
- D. Read the debug GCE Activity log using the API or Cloud Console.
- E. Use gcloud or Cloud Console to connect to the serial console and observe the logs.
- F. Export a debug VM into an image, and run the image on a local server where kernel log messages will be displayed on the native screen.
Answer: A,B,E
Explanation:
https://www.flexera.com/blog/cloud/2013/12/google-compute-engine-live-migration-passes-the-test/
"With live migration, the virtual machines are moved without any downtime or noticeable service degradation"
NEW QUESTION # 120
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. 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.
- B. Have users upload the images to Cloud Storage. Protect the bucket with a password that expires after 24 hours.
- C. Create an App Engine web application where users can upload images for the next 24 hours.
Authenticate users via Cloud Identity. - D. Have users upload the images to Cloud Storage using a signed URL that expires after 24 hours.
Answer: D
Explanation:
Explanation
https://cloud.google.com/blog/products/storage-data-transfer/uploading-images-directly-to-cloud-storage-by-usin
NEW QUESTION # 121
Case Study: 4 - Dress4Win case study
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 freemium 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 colocated 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.
For this question, refer to the Dress4Win case study.
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. Grant the operations engineers access to use Google Cloud Shell.
- B. Configure a VPN connection to GCP to allow SSH access to the cloud VMs.
- C. Develop a new access request process that grants temporary SSH access to cloud VMs when an operations engineer needs to perform a task.
- D. Have the development team build an API service that allows the operations team to execute specific remote procedure calls to accomplish their tasks.
Answer: B
NEW QUESTION # 122
To reduce costs, the Director of Engineering has required all developers to move their development infrastructure resources from on-premises virtual machines (VMs) to Google Cloud Platform. These resources go through multiple start/stop events during the day and require state to persist. You have been asked to design the process of running a development environment in Google Cloud while providing cost visibility to the finance department.
Which two steps should you take? (Choose two.)
- A. Use Google BigQuery billing export and labels to associate cost to groups
- B. Apply VM CPU utilization label and include it in the BigQuery billing export
- C. Use the - -auto-delete flag on all persistent disks and terminate the VM
- D. Use the - -no-auto-delete flag on all persistent disks and stop the VM
- E. Store all state in Google Cloud Storage, snapshot the persistent disks, and terminate the VM
- F. Store all state into local SSD, snapshot the persistent disks, and terminate the VM
Answer: A,D
NEW QUESTION # 123
You want to optimize the performance of an accurate, real-time, weather-charting application.
The data comes from 50,000 sensors sending 10 readings a second, in the format of a timestamp and sensor reading. Where should you store the data?
- A. Google Cloud Bigtable
- B. Google Cloud Storage
- C. Google Cloud SQL
- D. Google BigQuery
Answer: A
Explanation:
Google Cloud Bigtable is a scalable, fully-managed NoSQL wide-column database that is suitable for both real-time access and analytics workloads.
Good for:
Low-latency read/write access
High-throughput analytics
Native time series support
Common workloads:
IoT, finance, adtech
Personalization, recommendations
Monitoring
Geospatial datasets
Graphs
References: https://cloud.google.com/storage-options/
NEW QUESTION # 124
For this question, refer to the Helicopter Racing League (HRL) case study. HRL wants better prediction accuracy from their ML prediction models. They want you to use Google's AI Platform so HRL can understand and interpret the predictions. What should you do?
- A. Use Jupyter Notebooks.
- B. Use Google Cloud's operations suite.
- C. Use Explainable AI.
- D. Use Vision AI.
Answer: C
Explanation:
Reference: https://cloud.google.com/ai-platform/prediction/docs/ai-explanations/preparing-metadata
NEW QUESTION # 125
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