2025 Updated Google Professional-Cloud-Architect Certification Study Guide Pass Professional-Cloud-Architect Fast
Professional-Cloud-Architect Dumps PDF 2025 Program Your Preparation EXAM SUCCESS
NEW QUESTION # 99
Your company wants to start using Google Cloud resources but wants to retain their on-premises Active Directory domain controller for identity management. What should you do?
- A. Use Cloud Identity-Aware Proxy configured to use the on-premises Active Directory domain controller as an identity provider.
- B. Use Compute Engine to create an Active Directory (AD) domain controller that is a replica of the onpremises AD domain controller using Google Cloud Directory Sync.
- C. Use Google Cloud Directory Sync to synchronize Active Directory usernames with cloud identities and configure SAML SSO.
- D. Use the Admin Directory API to authenticate against the Active Directory domain controller.
Answer: C
Explanation:
https://cloud.google.com/solutions/federating-gcp-with-active-directory-introduction#implementing_federation
NEW QUESTION # 100
You want to enable your running Google Container Engine cluster to scale as demand for your application changes. What should you do?
- A. Option A
- B. Option C
- C. Option B
- D. Option D
Answer: B
NEW QUESTION # 101
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: B
NEW QUESTION # 102
Your applications will be writing their logs to BigQuery for analysis. Each application should have its own table.
Any logs older than 45 days should be removed. You want to optimize storage and follow Google recommended practices. What should you do?
- A. Rely on BigQuery's default behavior to prune application logs older than 45 days
- B. Create a script that uses the BigQuery command line tool (bq) to remove records older than 45 days
- C. Make the tables time-partitioned, and configure the partition expiration at 45 days
- D. Configure the expiration time for your tables at 45 days
Answer: C
Explanation:
Reference:
https://cloud.google.com/bigquery/docs/managing-partitioned-tables
NEW QUESTION # 103
You are using Cloud CDN to deliver static HTTP(S) website content hosted on a Compute Engine instance group. You want to improve the cache hit ratio.
What should you do?
- A. Make sure the HTTP(S) header "Cache-Region" points to the closest region of your users.
- B. Shorten the expiration time of the cached objects.
- C. Replicate the static content in a Cloud Storage bucket. Point CloudCDN toward a load balancer on that bucket.
- D. Customize the cache keys to omit the protocol from the key.
Answer: D
Explanation:
Reference:
https://cloud.google.com/cdn/docs/bestpractices#
using_custom_cache_keys_to_improve_cache_hit_ratio
NEW QUESTION # 104
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:
It is time-series data, So Big Table.
https://cloud.google.com/bigtable/docs/schema-design-time-series
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 # 105
Your company has just recently activated Cloud Identity to manage users. The Google Cloud Organization has been configured as wed. The security learn needs to secure protects that will be part of the Organization. They want to prohibit IAM users outside the domain from gaining permissions from now on. What should they do?
- A. Configure Cloud Scheduler to trigger a Cloud Function every hour that removes all users that don't belong to the Cloud identity domain from all projects.
- B. Configure an organization policy to block creation of service accounts
- C. Configure an organization policy to restrict identities by domain
Answer: C
Explanation:
An organization policy is a mechanism to configure constraints across your entire resource hierarchy1. By configuring an organization policy to restrict identities by domain, you can specify which domains are allowed or denied when granting IAM roles to users, groups, or service accounts2. This way, you can prohibit IAM users outside the domain from gaining permissions from now on2.
NEW QUESTION # 106
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. Point gcloud datastore create-indexes to your configuration file
- B. Upload the configuration file the App Engine's default Cloud Storage bucket, and have App Engine detect the new indexes
- C. Create an HTTP request to the built-in python module to send the index configuration file to your application
- D. In the GCP Console, use Datastore Admin to delete the current indexes and upload the new configuration file
Answer: A
Explanation:
Explanation
https://cloud.google.com/datastore/docs/tools/indexconfig#Datastore_Updating_indexes
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 You analyzed TerramEarth's business requirement to reduce downtime, and found that they can achieve a majority of time saving by reducing customers' 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:
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 # 108
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. Latency difference between US and Asia
- C. The number of character sets present in the database
- D. Error rates for requests from Asia
- E. Total visits and average latency for users in Asia
Answer: E
Explanation:
Topic 4, Dress4Win case studyCompany 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:
* Application servers:
* Storage appliances:
* Apache Hadoop/Spark servers:
* MQ servers:
* Miscellaneous servers:
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 # 109
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.
Dress4Win has asked you for advice on how to migrate their on-premises MySQL deployment to the cloud. They want to minimize downtime and performance impact to their on-premises solution during the migration. Which approach should you recommend?
- A. Create a dump of the MySQL replica server into the cloud environment, load it into: Google Cloud Datastore, and configure applications to read/write to Cloud Datastore at cutover.
- B. Create a dump of the on-premises MySQL master server, and then shut it down, upload it to the cloud environment, and load into a new MySQL cluster.
- C. Setup a MySQL replica server/slave in the cloud environment, and configure it for asynchronous replication from the MySQL master server on-premises until cutover.
- D. Create a new MySQL cluster in the cloud, configure applications to begin writing to both on- premises and cloud MySQL masters, and destroy the original cluster at cutover.
Answer: C
NEW QUESTION # 110
Your company has a stateless web API that performs scientific calculations. The web API runs on a single Google Kubernetes Engine (GKE) cluster. The cluster is currently deployed in us-central1. Your company has expanded to offer your API to customers in Asia. You want to reduce the latency for the users in Asia. What should you do?
- A. Use a global HTTP(s) load balancer with Cloud CDN enabled
- B. Create a second GKE cluster in asia-southeast1, and expose both API's using a Service of type Load Balancer. Add the public Ips to the Cloud DNS zone
- C. Create a second GKE cluster in asia-southeast1, and use kubemci to create a global HTTP(s) load balancer
- D. Increase the memory and CPU allocated to the application in the cluster
Answer: C
Explanation:
Explanation
https://cloud.google.com/kubernetes-engine/docs/concepts/multi-cluster-ingress#how_works
https://github.com/GoogleCloudPlatform/k8s-multicluster-ingress
https://cloud.google.com/blog/products/gcp/how-to-deploy-geographically-distributed-services-on-kubernetes-en
NEW QUESTION # 111
You deploy your custom java application to google app engine.
It fails to deploy and gives you the following stack trace:
- A. Digitally sign all of your JAR files and redeploy your application.
- B. Recompile the CLoakedServlet class using and MD5 hash instead of SHA1
- C. Upload missing JAR files and redeploy your application
Answer: A
NEW QUESTION # 112
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. Flat file
- B. Blobstore
- C. Relational
- D. NoSQL
Answer: D
Explanation:
Explanation
Relational databases were not designed to cope with the scale and agility challenges that face modern applications, nor were they built to take advantage of the commodity storage and processing power available today.
NoSQL fits well for:
Developers are working with applications that create massive volumes of new, rapidly changing data types - structured, semi-structured, unstructured and polymorphic data.
NEW QUESTION # 113
For this question, refer to the Dress4Win case study.
Dress4Win has configured a new uptime check with Google Stackdriver for several of their legacy services. The Stackdriver dashboard is not reporting the services as healthy. What should they do?
- A. Configure their legacy web servers to allow requests that contain user-Agent HTTP header when the value matches GoogleStackdriverMonitoring- UptimeChecks (https://cloud.google.com/monitoring)
- B. Configure their load balancer to pass through the User-Agent HTTP header when the value matches GoogleStackdriverMonitoring-UptimeChecks (https://cloud.google.com/monitoring)
- C. In the Cloud Platform Console download the list of the uptime servers' IP addresses and create an inbound firewall rule
- D. Install the Stackdriver agent on all of the legacy web servers.
Answer: C
NEW QUESTION # 114
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 # 115
For this question, refer to the Dress4Win case study.
At Dress4Win, an operations engineer wants to create a tow-cost solution to remotely archive copies of database backup files. The database files are compressed tar files stored in their current data center. How should he proceed?
- A. Create a Cloud Storage Transfer Service Job to copy the files to a Coldline Storage bucket.
- B. Create a cron script using gsutil to copy the files to a Coldline Storage bucket.
- C. Create a cron script using gsutil to copy the files to a Regional Storage bucket.
- D. Create a Cloud Storage Transfer Service job to copy the files to a Regional Storage bucket.
Answer: B
Explanation:
Reference:
Follow these rules of thumb when deciding whether to use gsutil or Storage Transfer Service:
When transferring data from an on-premises location, use gsutil.
When transferring data from another cloud storage provider, use Storage Transfer Service.
Otherwise, evaluate both tools with respect to your specific scenario.
Use this guidance as a starting point. The specific details of your transfer scenario will also help you determine which tool is more appropriate
https://cloud.google.com/storage-transfer/docs/overview
NEW QUESTION # 116
You are managing several internal applications that are deployed on Compute Engine. Business users inform you that an application has become very slow over the past few days. You want to find the underlying cause in order to solve the problem. What should you do first?
- A. Deploy the applications on a managed instance group with autoscaling enabled. Add a load balancer in front of the managed instance group, and have the users connect to the IP of the load balancer.
- B. Inspect the logs and metrics from the instances in Cloud Logging and Cloud Monitoring.
- C. Change the Compute Engine Instances behind the application to a machine type with more CPU and memory.
- D. Restore a backup of the application database from a time before the application became slow.
Answer: B
Explanation:
When an application becomes slow, the first step you should take is to gather information about the underlying cause of the problem. One way to do this is by inspecting the logs and metrics from the instances where the application is deployed. Google Cloud Platform (GCP) provides tools such as Cloud Logging and Cloud Monitoring that can help you to collect and analyze this information. By reviewing the logs and metrics from the instances, you may be able to identify issues such as resource shortages (e.g. CPU, memory, or disk), network problems, or application errors that are causing the performance issues. Once you have identified the underlying cause of the problem, you can take steps to resolve it.
NEW QUESTION # 117
For this question, refer to the TerramEarth case study.
TerramEarth has equipped unconnected trucks with servers and sensors to collet telemetry data. Next year they want to use the data to train machine learning models. They want to store this data in the cloud while reducing costs. What should they do?
- A. Push the telemetry data in real-time to a streaming dataflow job that compresses the data, and store it in Cloud Bigtable.
- B. Have the vehicle' computer compress the data in hourly snapshots, and store it in a Google Cloud storage (GCS) Nearline bucket.
- C. Push the telemetry data in Real-time to a streaming dataflow job that compresses the data, and store it in Google BigQuery.
- D. Have the vehicle's computer compress the data in hourly snapshots, a Store it in a GCS Coldline bucket.
Answer: D
Explanation:
Coldline Storage is the best choice for data that you plan to access at most once a year, due to its slightly lower availability, 90-day minimum storage duration, costs for data access, and higher per-operation costs. For example:
Cold Data Storage - Infrequently accessed data, such as data stored for legal or regulatory reasons, can be stored at low cost as Coldline Storage, and be available when you need it.
Disaster recovery - In the event of a disaster recovery event, recovery time is key. Cloud Storage provides low latency access to data stored as Coldline Storage.
References:
https://cloud.google.com/storage/docs/storage-classes
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
o No redundancy
o Backed up every 12 hours
* 100% uptime service level agreement (SLA)
* Authenticates all users
Compute
* 30 machines in US West Coast, each machine has:
o Twin, dual core CPUs
o 32GB of RAM
* Twin 250 GB HDD (RAID 1)
* 20 machines in US East Coast, each machine has:
o Single dual-core CPU
o 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 # 118
Your company's test suite is a custom C++ application that runs tests throughout each day on Linux virtual machines. The full test suite takes several hours to complete, running on a limited number of on premises servers reserved for testing. Your company wants to move the testing infrastructure to the cloud, to reduce the amount of time it takes to fully test a change to the system, while changing the tests as little as possible.
Which cloud infrastructure should you recommend?
- A. Google App Engine with Google Stackdriver for logging
- B. Google Compute Engine unmanaged instance groups and Network Load Balancer
- C. Google Cloud Dataproc to run Apache Hadoop jobs to process each test
- D. Google Compute Engine managed instance groups with auto-scaling
Answer: D
Explanation:
https://cloud.google.com/compute/docs/instance-groups/
Google Compute Engine enables users to launch virtual machines (VMs) on demand. VMs can be launched from the standard images or custom images created by users.
Managed instance groups offer autoscaling capabilities that allow you to automatically add or remove instances from a managed instance group based on increases or decreases in load. Autoscaling helps your applications gracefully handle increases in traffic and reduces cost when the need for resources is lower.
NEW QUESTION # 119
A lead engineer wrote a custom tool that deploys virtual machines in the legacy data center. He wants to migrate the custom tool to the new cloud environment You want to advocate for the adoption of Google Cloud Deployment Manager What are two business risks of migrating to Cloud Deployment Manager? Choose 2 answers
- A. Cloud Deployment Manager can be used to permanently delete cloud resources.
- B. Cloud Deployment Manager APIs could be deprecated in the future.
- C. Cloud Deployment Manager is unfamiliar to the company's engineers.
- D. Cloud Deployment Manager only supports automation of Google Cloud resources.
- E. Cloud Deployment Manager uses Python.
- F. Cloud Deployment Manager requires a Google APIs service account to run.
Answer: E,F
NEW QUESTION # 120
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 region 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
NEW QUESTION # 121
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