Practice with Professional-Cloud-Architect Dumps for Google Cloud Certified Certified Exam Questions & Answer
REAL Professional-Cloud-Architect Exam Questions With 100% Refund Guarantee
Google Professional-Cloud-Architect Exam Syllabus Topics:
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NEW QUESTION # 97
Your web application must comply with the requirements of the European Union's General Data Protection Regulation (GDPR). You are responsible for the technical architecture of your web application. What should you do?
- A. Ensure that Cloud Security Scanner is part of your test planning strategy in order to pick up any compliance gaps.
- B. Define a design for the security of data in your web application that meets GDPR requirements.
- C. Enable the relevant GDPR compliance setting within the GCPConsole for each of the services in use within your application.
- D. Ensure that your web application only uses native features and services of Google Cloud Platform, because Google already has various certifications and provides "pass-on" compliance when you use native features.
Answer: B
Explanation:
Explanation
https://cloud.google.com/security/gdpr/?tab=tab4
Reference: https://www.mobiloud.com/blog/gdpr-compliant-mobile-app/
NEW QUESTION # 98
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 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. Move all the data into 1 zone, then launch a Cloud Dataproc cluster to run the job.
- B. 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.
- C. Launch a cluster in each region to preprocess and compress the raw data, then move the data into a regional bucket and use a Cloud Dataproc cluster to finish the job.
- D. Move all the data into 1 region, then launch a Google Cloud Dataproc cluster to run the job.
Answer: C
Explanation:
Compressed Data save $$$
Region bucket cheaper than Multi Region
References: https://medium.com/google-cloud/google-cloud-storage-what-bucket-class-for-the- bestperformance-5c847ac8f9f2
NEW QUESTION # 99
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 Cloud DataFlow
- B. Cloud Pub/Sub to Cloud SQL
- C. Cloud Pub/Sub alone
- D. Cloud Pub/Sub to Stackdriver
Answer: A
Explanation:
Reference https://cloud.google.com/pubsub/docs/ordering
NEW QUESTION # 100
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 stream data directly to Google BigQuery.
- B. Vehicles continue to write data using the existing system (FTP).
- C. Vehicles write data directly to GCS.
- D. Vehicles write data directly to Google Cloud Pub/Sub.
Answer: D
Explanation:
Explanation
https://cloud.google.com/solutions/data-lifecycle-cloud-platform
https://cloud.google.com/solutions/designing-connected-vehicle-platform
Topic 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
* 20 TB
* Complex table structure
* Well maintained, clean data
* Strong backup strategy
* PostgreSQL database stores user credentials
* Single-homed in US West
No redundancy
Backed up every 12 hours
* 100% uptime service level agreement (SLA)
* Authenticates all users
Compute
* 30 machines in US West Coast, each machine has:
Twin, dual core CPUs
32GB of RAM
* Twin 250 GB HDD (RAID 1)
* 20 machines in US East Coast, each machine has:
Single dual-core CPU
24 GB of RAM
* Twin 250 GB HDD (RAID 1)
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.
NEW QUESTION # 101
Your company has decided to build a backup replica of their on-premises user authentication PostgreSQL database on Google Cloud Platform. The database is 4 TB, and large updates are frequent. Replication requires private address space communication. Which networking approach should you use?
- A. Google Cloud VPN connected to the data center network
- B. A NAT and TLS translation gateway installed on-premises
- C. Google Cloud Dedicated Interconnect
- D. A Google Compute Engine instance with a VPN server installed connected to the data center network
Answer: C
Explanation:
Google Cloud Dedicated Interconnect provides direct physical connections and RFC 1918 communication between your on-premises network and Google's network. Dedicated Interconnect enables you to transfer large amounts of data between networks, which can be more cost effective than purchasing additional bandwidth over the public Internet or using VPN tunnels.
Benefits:
Traffic between your on-premises network and your VPC network doesn't traverse the public
Internet. Traffic traverses a dedicated connection with fewer hops, meaning there are less points of failure where traffic might get dropped or disrupted.
Your VPC network's internal (RFC 1918) IP addresses are directly accessible from your on-
premises network. You don't need to use a NAT device or VPN tunnel to reach internal IP addresses. Currently, you can only reach internal IP addresses over a dedicated connection.
To reach Google external IP addresses, you must use a separate connection.
You can scale your connection to Google based on your needs. Connection capacity is
delivered over one or more 10 Gbps Ethernet connections, with a maximum of eight connections (80 Gbps total per interconnect).
The cost of egress traffic from your VPC network to your on-premises network is reduced. A
dedicated connection is generally the least expensive method if you have a high-volume of traffic to and from Google's network.
References: https://cloud.google.com/interconnect/docs/details/dedicated
NEW QUESTION # 102
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. 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 engineers access to use Google Cloud Shell.
Answer: C
NEW QUESTION # 103
You analyzed TerramEarth's business requirement to reduce downtime, and found that they can achieve a
majority of time saving by reducing customer's wait time for parts. You decided to focus on reduction of the
3 weeks aggregate reporting time.
Which modifications to the company's processes should you recommend?
- A. Migrate from FTP to SFTP transport, develop machine learning analysis of metrics, and increase dealer
local inventory by a fixed factor - B. Migrate from FTP to streaming transport, migrate from CSV to binary format, and develop machine
learning analysis of metrics - C. Migrate from CSV to binary format, migrate from FTP to SFTP transport, and develop machine learning
analysis of metrics - D. Increase fleet cellular connectivity to 80%, migrate from FTP to streaming transport, and develop
machine learning analysis of metrics
Answer: B
Explanation:
Explanation/Reference:
Explanation:
The Avro binary format is the preferred format for loading compressed data. Avro data is faster to load
because the data can be read in parallel, even when the data blocks are compressed.
Cloud Storage supports streaming transfers with the gsutil tool or boto library, based on HTTP chunked
transfer encoding. Streaming data lets you stream data to and from your Cloud Storage account as soon
as it becomes available without requiring that the data be first saved to a separate file. Streaming transfers
are useful if you have a process that generates data and you do not want to buffer it locally before
uploading it, or if you want to send the result from a computational pipeline directly into Cloud Storage.
References: https://cloud.google.com/storage/docs/streaming
https://cloud.google.com/bigquery/docs/loading-data
NEW QUESTION # 104
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-autocaling --min-nodes=1 --max-nodes=10 and redeploy your application. - C. Add additional nodes to your Container Engine cluster using the following command:
gcloud container clusters resize CLUSTER_NAME --size 10 - D. 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
Answer: D
Explanation:
Explanation
https://cloud.google.com/kubernetes-engine/docs/concepts/cluster-autoscaler 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.
NEW QUESTION # 105
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. Grant the security team access to the logs in each Project.
- B. Configure Stackdriver Monitoring for all Projects, and export to Google Cloud Storage.
- C. Configure Stackdriver Monitoring for all Projects, and export to BigQuery.
- D. Configure Stackdriver Monitoring for all Projects with the default retention policies.
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 # 106
For this question, refer to the Mountkirk Games case study.
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 load-testing team is not running their tool against production.
- B. Verify that the new feature code did not introduce any performance bugs.
- C. Verify that the project quota hasn't been exceeded.
- D. Verify that the database is online.
Answer: D
Explanation:
Topic 2, TerramEarth Case Study
Company Overview
TerramEarth manufactures heavy equipment for the mining and agricultural industries:
About 80% of their business is from mining and 20% from agriculture. They currently have over 500 dealers and service centers in 100 countries. Their mission is to build products that make their customers more productive.
Company Background
TerramEarth formed in 1946, when several small, family owned companies combined to retool after World War II. The company cares about their employees and customers and considers them to be extended members of their family.
TerramEarth is proud of their ability to innovate on their core products and find new markets as their customers' needs change. For the past 20 years trends in the industry have been largely toward increasing productivity by using larger vehicles with a human operator.
Solution Concept
There are 20 million TerramEarth vehicles in operation that collect 120 fields of data per second. Data is stored locally on the vehicle and can be accessed for analysis when a vehicle is serviced. The data is downloaded via a maintenance port. This same port can be used to adjust operational parameters, allowing the vehicles to be upgraded in the field with new computing modules.
Approximately 200,000 vehicles are connected to a cellular network, allowing TerramEarth to collect data directly. At a rate of 120 fields of data per second, with 22 hours of operation per day. TerramEarth collects a total of about 9 TB/day from these connected vehicles.
Existing Technical Environment
TerramEarth's existing architecture is composed of Linux-based systems that reside in a data center. These systems gzip CSV files from the field and upload via FTP, transform and aggregate them, and place the data in their data warehouse. Because this process takes time, aggregated reports are based on data that is 3 weeks old.
With this data, TerramEarth has been able to preemptively stock replacement parts and reduce unplanned downtime of their vehicles by 60%. However, because the data is stale, some customers are without their vehicles for up to 4 weeks while they wait for replacement parts.
Business Requirements
* Decrease unplanned vehicle downtime to less than 1 week, without increasing the cost of carrying surplus inventory
* Support the dealer network with more data on how their customers use their equipment IP better position new products and services.
* Have the ability to partner with different companies-especially with seed and fertilizer suppliers in the fast-growing agricultural business-to create compelling joint offerings for their customers CEO Statement We have been successful in capitalizing on the trend toward larger vehicles to increase the productivity of our customers. Technological change is occurring rapidly and TerramEarth has taken advantage of connected devices technology to provide our customers with better services, such as our intelligent farming equipment. With this technology, we have been able to increase farmers' yields by 25%, by using past trends to adjust how our vehicles operate. These advances have led to the rapid growth of our agricultural product line, which we expect will generate 50% of our revenues by 2020.
CTO Statement
Our competitive advantage has always been in the manufacturing process with our ability to build better vehicles for tower cost than our competitors. However, new products with different approaches are constantly being developed, and I'm concerned that we lack the skills to undergo the next wave of transformations in our industry. Unfortunately, our CEO doesn't take technology obsolescence seriously and he considers the many new companies in our industry to be niche players. My goals are to build our skills while addressing immediate market needs through incremental innovations.
NEW QUESTION # 107
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 Cloud DataFlow
- B. Cloud Pub/Sub to Cloud SQL
- C. Cloud Pub/Sub alone
- D. Cloud Pub/Sub to Stackdriver
Answer: A
Explanation:
Reference https://cloud.google.com/pubsub/docs/ordering
Topic 2, Mountkirk Games
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 # 108
The application reliability team at your company has added a debug feature to their backend service to send all server events to Google Cloud Storage for eventual analysis.
The event records are at least 50 KB and at most 15 MB and are expected to peak at 3,000 events per second. You want to minimize data loss.
Which process should you implement?
- A. * Batch every 10,000 events with a single manifest file for metadata.
* Compress event files and manifest file into a single archive file.
* Name files using serverName-EventSequence.
* Create a new bucket if bucket is older than 1 day and save the single archive file to the new bucket. Otherwise, save the single archive file to existing bucket. - B. * Compress individual files.
* Name files with serverName-EventSequence.
* Save files to one bucket
* Set custom metadata headers for each object after saving. - C. * Append metadata to file body.
* Compress individual files.
* Name files with a random prefix pattern.
* Save files to one bucket - D. * Append metadata to file body.
* Compress individual files.
* Name files with serverName-Timestamp.
* Create a new bucket if bucket is older than 1 hour and save individual files to the new bucket. Otherwise, save files to existing bucket
Answer: D
NEW QUESTION # 109
Your company wants you to build a highly reliable web application with a few public APIs as the backend. You don't expect a lot of user traffic, but traffic could spike occasionally. You want to leverage Cloud Load Balancing, and the solution must be cost-effective for users. What should you do?
- A. Store static content such as HTML and images in a Cloud Storage bucket. Host the APIs on a zonal Google Kubernetes Engine cluster with worker nodes in multiple zones, and save the user data in Cloud Spanner.
- B. Store static content such as HTML and images in a Cloud Storage bucket. Use Cloud Functions to host the APIs and save the user data in Firestore.
- C. Store static content such as HTML and images in Cloud CDN. Use Cloud Run to host the APIs and save the user data in Cloud SQL.
- D. Store static content such as HTML and images in Cloud CDN. Host the APIs on App Engine and store the user data in Cloud SQL.
Answer: B
NEW QUESTION # 110
You are running a cluster on Kubernetes Engine (GKE) to serve a web application. Users are reporting that a specific part of the application is not responding anymore. You notice that all pods of your deployment keep restarting after 2 seconds. The application writes logs to standard output. You want to inspect the logs to find the cause of the issue. Which approach can you take?
- A. Review the Serial Port logs for each Compute Engine instance that is serving as a node in the cluster.
- B. Connect to the cluster using gcloud credentials and connect to a container in one of the pods to read the logs.
- C. Review the Stackdriver logs for the specific GKE container that is serving the unresponsive part of the application.
- D. Review the Stackdriver logs for each Compute Engine instance that is serving as a node in the cluster.
Answer: B
NEW QUESTION # 111
Your company's user-feedback portal comprises a standard LAMP stack replicated across two zones. It is deployed in the us-central1 region and uses autoscaled managed instance groups on all layers, except the database. Currently, only a small group of select customers have access to the portal. The portal meets a
99,99% availability SLA under these conditions. However next quarter, your company will be making the portal available to all users, including unauthenticated users. You need to develop a resiliency testing strategy to ensure the system maintains the SLA once they introduce additional user load.
What should you do?
- A. Capture existing users input, and replay captured user load until autoscale is triggered on all layers. At the same time, terminate all resources in one of the zones
- B. Expose the new system to a larger group of users, and increase group size each day until autoscale logic is triggered on all layers. At the same time, terminate random resources on both zones
- C. Create synthetic random user input, replay synthetic load until autoscale logic is triggered on at least one layer, and introduce "chaos" to the system by terminating random resources on both zones
- D. Capture existing users input, and replay captured user load until resource utilization crosses 80%. Also, derive estimated number of users based on existing user's usage of the app, and deploy enough resources to handle 200% of expected load
Answer: D
NEW QUESTION # 112
You need to design a solution for global load balancing based on the URL path being requested. You need to ensure operations reliability and end-to-end in-transit encryption based on Google best practices.
What should you do?
- A. Create an HTTPS load balancer with URL maps.
- B. Create a cross-region load balancer with URL Maps.
- C. Create appropriate instance groups and instances. Configure SSL proxy load balancing.
- D. Create a global forwarding rule. Configure SSL proxy balancing.
Answer: A
Explanation:
Explanation
Reference https://cloud.google.com/load-balancing/docs/https/url-map
NEW QUESTION # 113
For this question, refer to the TerramEarth case study. To be compliant with European GDPR regulation, TerramEarth is required to delete data generated from its European customers after a period of 36 months when it contains personal data. In the new architecture, this data will be stored in both Cloud Storage and BigQuery. What should you do?
- A. Create a BigQuery time-partitioned table for the European data, and set the partition period to 36 months.
For Cloud Storage, use gsutil to create a SetStorageClass to NONE action with an Age condition of 36 months. - B. Create a BigQuery table for the European data, and set the table retention period to 36 months. For Cloud Storage, use gsutil to create a SetStorageClass to NONE action when with an Age condition of 36 months.
- C. Create a BigQuery table for the European data, and set the table retention period to 36 months. For Cloud Storage, use gsutil to enable lifecycle management using a DELETE action with an Age condition of 36 months.
- D. Create a BigQuery time-partitioned table for the European data, and set the partition expiration period to 36 months. For Cloud Storage, use gsutil to enable lifecycle management using a DELETE action with an Age condition of 36 months.
Answer: C
NEW QUESTION # 114
Your company wants to track whether someone is present in a meeting room reserved for a scheduled meeting. There are 1000 meeting rooms across 5 offices on 3 continents.
Each room is equipped with a motion sensor that reports its status every second. The data from the motion detector includes only a sensor ID and several different discrete items of information. Analysts will use this data, together with information about account owners and office locations. Which database type should you use?
- A. NoSQL
- B. Relational
- C. Flat file
- D. Blobstore
Answer: A
NEW QUESTION # 115
You need to deploy an application on Google Cloud that must run on a Debian Linux environment. The application requires extensive configuration in order to operate correctly. You want to ensure that you can install Debian distribution updates with minimal manual intervention whenever they become available. What should you do?
- A. Create a Compute Engine instance template using the most recent Debian image. Create an instance from this template, and install and configure the application as part of the startup script. Repeat this process whenever a new Google-managed Debian image becomes available.
- B. Create a Debian-based Compute Engine instance, install and configure the application, and use OS patch management to install available updates.
- C. Create an instance with the latest available Debian image. Connect to the instance via SSH, and install and configure the application on the instance. Repeat this process whenever a new Google-managed Debian image becomes available.
- D. Create a Docker container with Debian as the base image. Install and configure the application as part of the Docker image creation process. Host the container on Google Kubernetes Engine and restart the container whenever a new update is available.
Answer: B
Explanation:
Reference: https://cloud.google.com/compute/docs/os-patch-management
NEW QUESTION # 116
......
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