2021 100% Free Professional-Cloud-Architect Daily Practice Exam With 230 Questions
Professional-Cloud-Architect exam torrent Google study guide
Section #5. Managing implementation
This section has two major topics and assesses the candidates’ skills in application development, system migration, data management, API development/usage best practices, and testing frameworks. Interacting with Google Cloud programmatically is the key focus of the second sub-topic. The main considerations here are Cloud Emulators, Google Cloud Shell, and Cloud SDK.
NEW QUESTION 54
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: D
NEW QUESTION 55
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. * Compress individual files.
* Name files with serverName-EventSequence.
* Save files to one bucket
* Set custom metadata headers for each object after saving. - B. * 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 - C. * Append metadata to file body.
* Compress individual files.
* Name files with a random prefix pattern.
* Save files to one bucket - D. * 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.
Answer: C
Explanation:
Explanation
In order to maintain a high request rate, avoid using sequential names. Using completely random object names will give you the best load distribution. Randomness after a common prefix is effective under the prefix
https://cloud.google.com/storage/docs/request-rate
NEW QUESTION 56
For this question, refer to the Helicopter Racing League (HRL) case study. Recently HRL started a new regional racing league in Cape Town, South Afric a. In an effort to give customers in Cape Town a better user experience, HRL has partnered with the Content Delivery Network provider, Fastly. HRL needs to allow traffic coming from all of the Fastly IP address ranges into their Virtual Private Cloud network (VPC network). You are a member of the HRL security team and you need to configure the update that will allow only the Fastly IP address ranges through the External HTTP(S) load balancer. Which command should you use?
- A. gcloud compute priority-policies rules update
1000 \
security policy from fastly
--src- ip-ranges" - B. gcloud compute firewall rules update
sourceiplist-fastly \
priority 1000 \
allow tcp: 443 - C. glouc compute firewall rules update hlr-policy \
--priority 1000 \
target tags-sourceiplist fastly \
--allow tcp:443 - D. gcloud compute security policies rules update 1000 \
--security-policy hlr-policy \
--expression "evaluatePreconfiguredExpr('sourceiplist-fastly')" \
--action " allow"
Answer: D
Explanation:
-- action " allow"
Reference:
D18912E1457D5D1DDCBD40AB3BF70D5D
NEW QUESTION 57
Your company plans to migrate a multi-petabyte data set to the cloud. The data set must be available 24hrs a day. Your business analysts have experience only with using a SQL interface.
How should you store the data to optimize it for ease of analysis?
- A. Stream data into Google Cloud Datastore
- B. Insert data into Google Cloud SQL
- C. Put flat files into Google Cloud Storage
- D. Load data into Google BigQuery
Answer: D
Explanation:
BigQuery is Google's serverless, highly scalable, low cost enterprise data warehouse designed to make all your data analysts productive. Because there is no infrastructure to manage, you can focus on analyzing data to find meaningful insights using familiar SQL and you don't need a database administrator.
BigQuery enables you to analyze all your data by creating a logical data warehouse over managed, columnar storage as well as data from object storage, and spreadsheets.
Reference: https://cloud.google.com/bigquery/
NEW QUESTION 58
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 and Cloud Load Balancing
- B. Google Compute Engine, Jenkins, and Cloud Load Balancing
- C. Google Container Engine, Jenkins, and Helm
- D. Google Compute Engine and Cloud Deployment Manager
Answer: D
NEW QUESTION 59
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 load balancer to pass through the User-Agent HTTP header when the value matches GoogleStackdriverMonitoring-UptimeChecks (https://cloud.google.com/monitoring)
- B. In the Cloud Platform Console download the list of the uptime servers' IP addresses and create an inbound firewall rule
- C. Install the Stackdriver agent on all of the legacy web servers.
- D. 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)
Answer: D
NEW QUESTION 60
For this question, refer to the Mountkirk Games case study. Which managed storage option meets
Mountkirk's technical requirement for storing game activity in a time series database service?
- A. BigQuery
- B. Cloud Spanner
- C. Cloud Datastore
- D. Cloud Bigtable
Answer: D
NEW QUESTION 61
Your company is using BigQuery as its enterprise data warehouse. Data is distributed over several Google Cloud projects. All queries on BigQuery need to be billed on a single project. You want to make sure that no query costs are incurred on the projects that contain the data. Users should be able to query the datasets, but not edit them.
How should you configure users' access roles?
- A. Add all users to a group. Grant the group the roles of BigQuery jobUser on the billing project and BigQuery dataViewer on the projects that contain the data.
- B. Add all users to a group. Grant the group the roles of BigQuery dataViewer on the billing project and BigQuery jobUser on the projects that contain the data.
- C. Add all users to a group. Grant the group the roles of BigQuery dataViewer on the billing project and BigQuery user on the projects that contain the data.
- D. Add all users to a group. Grant the group the role of BigQuery user on the billing project and BigQuery dataViewer on the projects that contain the data.
Answer: D
NEW QUESTION 62
Your customer is moving their corporate applications to Google Cloud Platform. The security team wants detailed visibility of all projects in the organization. You provision the Google Cloud Resource Manager and set up yourself as the org admin. What Google Cloud Identity and Access Management (Cloud IAM) roles should you give to the security team'?
- A. Org viewer, project viewer
- B. Project owner, network admin
- C. Org viewer, project owner
- D. Org admin, project browser
Answer: A
NEW QUESTION 63
Your company has successfully migrated to the cloud and wants to analyze their data stream to optimize operations. They do not have any existing code for this analysis, so they are exploring all their options. These options include a mix of batch and stream processing, as they are running some hourly jobs and live-processing some data as it comes in. Which technology should they use for this?
- A. Google Cloud Dataflow
- B. Google Cloud Dataproc
- C. Google Compute Engine with Google BigQuery
- D. Google Container Engine with Bigtable
Answer: A
Explanation:
Dataflow is for processing both the Batch and Stream.
NEW QUESTION 64
You have a Python web application with many dependencies that requires 0.1 CPU cores and 128 MB of memory to operate in production. You want to monitor and maximize machine utilization. You also to reliably deploy new versions of the application. Which set of steps should you take?
- A. Perform the following:
1) Create a Kubernetes Engine cluster with n1-standard-1 type machines.
2) Build a Docker image from the production branch with all of the dependencies, and tag it with the
3) Create a Kubernetes Deployment with the imagePullPolicy set to "IfNotPresent" in the staging namespace, and then promote it to the production namespace after testing. - B. Perform the following:
1) Create a Kubernetes Engine (GKE) cluster with n1-standard-4 type machines.
2) Build a Docker image from the master branch will all of the dependencies, and tag it with "latest".
3) Create a Kubernetes Deployment in the default namespace with the imagePullPolicy set to "Always".
Restart the pods to automatically deploy new production releases. - C. Perform the following:
1) Create a managed instance group with n1-standard-1 type machines.
2) Build a Compute Engine image from the production branch that contains all of the dependencies and automatically starts the Python app.
3) Rebuild the Compute Engine image, and update the instance template to deploy new production releases. - D. Perform the following:
1) Create a managed instance group with f1-micro type machines.
2) Use a startup script to clone the repository, check out the production branch, install the dependencies, and start the Python app.
3) Restart the instances to automatically deploy new production releases.
Answer: B
Explanation:
Reference:
https://cloud.google.com/compute/docs/instance-templates
NEW QUESTION 65
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 to replace MySQL, and use Cloud Spanner for historical data queries.
- B. Use Cloud Bigtable to replace MySQL, and use BigQuery for historical data queries.
- C. Use Cloud SQL for time series data, and use Cloud Bigtable 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
Explanation:
https://cloud.google.com/bigtable/docs/schema-design-time-series
NEW QUESTION 66
You are designing a large distributed application with 30 microservices. Each of your distributed microservices needs to connect to a database back-end. You want to store the credentials securely. Where should you store the credentials?
- A. In the source code
- B. In an environment variable
- C. In a config file that has restricted access through ACLs
- D. In a secret management system
Answer: B
NEW QUESTION 67
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 project for development and test and another for staging and production.
- B. Create one subnetwork for development and another for staging and production.
- C. Create a network for development and test and another for staging and production.
- D. Create one project for development, a second for staging and a third for production.
Answer: A
NEW QUESTION 68
Your customer wants to capture multiple GBs of aggregate real-time key performance indicators (KPIs) from their game servers running on Google Cloud Platform and monitor the KPIs with low latency. How should they capture the KPIs?
- A. Schedule BigQuery load jobs to ingest analytics files uploaded to Cloud Storage every ten minutes, and visualize the results in Google Data Studio.
- B. Insert the KPIs into Cloud Datastore entities, and run ad hoc analysis and visualizations of them in Cloud Datalab.
- C. Output custom metrics to Stackdriver from the game servers, and create a Dashboard in Stackdriver Monitoring Console to view them.
- D. Store time-series data from the game servers in Google Bigtable, and view it using Google Data Studio.
Answer: D
Explanation:
Reference:
https://cloud.google.com/monitoring/api/v3/metrics-details#metric-kinds
NEW QUESTION 69
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. Replicate the static content in a Cloud Storage bucket. Point CloudCDN toward a load balancer on that
bucket. - C. Shorten the expiration time of the cached objects.
- D. Customize the cache keys to omit the protocol from the key.
Answer: D
Explanation:
Explanation/Reference:
Reference https://cloud.google.com/cdn/docs/best-
practices#using_custom_cache_keys_to_improve_cache_hit_ratio
NEW QUESTION 70
Your company has developed a monolithic, 3-tier application to allow external users to upload and share files.
The solution cannot be easily enhanced and lacks reliability. The development team would like to re-architect the application to adopt microservices and a fully managed service approach, but they need to convince their leadership that the effort is worthwhile. Which advantage(s) should they highlight to leadership?
- A. The new approach will be significantly less costly, make it easier to manage the underlying infrastructure, and automatically manage the CI/CD pipelines.
- B. The process can be automated with Migrate for Compute Engine.
- C. The monolithic solution can be converted to a container with Docker. The generated container can then be deployed into a Kubernetes cluster.
- D. The new approach will make it easier to decouple infrastructure from application, develop and release new features, manage the underlying infrastructure, manage CI/CD pipelines and perform A/B testing, and scale the solution if necessary.
Answer: D
NEW QUESTION 71
An application development team believes their current logging tool will not meet their needs for their new cloud-based product. They want a bettor tool to capture errors and help them analyze their historical log data. You want to help them find a solution that meets their needs, what should you do?
- A. Help them define their requirements and assess viable logging tools.
- B. Direct them to download and install the Google StackDriver logging agent.
- C. Send them a list of online resources about logging best practices.
- D. Help them upgrade their current tool to take advantage of any new features.
Answer: A
Explanation:
Help them define their requirements and assess viable logging tools. They know the requirements and the existing tools' problems. While it's true StackDriver Logging and Error Reporting possibly meet all their requirements, there might be other tools also meet their need. They need you to provide expertise to make assessment for new tools, specifically, logging tools that can "capture errors and help them analyze their historical log data"
NEW QUESTION 72
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:
- A. Option A
- B. Option B
- C. Option D
- D. Option C
Answer: A
Explanation:
Explanation/Reference:
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 73
Case Study: 3 - JencoMart Case Study
Company Overview
JencoMart is a global retailer with over 10,000 stores in 16 countries. The stores carry a range of goods, such as groceries, tires, and jewelry. One of the company's core values is excellent customer service. In addition, they recently introduced an environmental policy to reduce their carbon output by 50% over the next 5 years.
Company Background
JencoMart started as a general store in 1931, and has grown into one of the world's leading brands known for great value and customer service. Over time, the company transitioned from only physical stores to a stores and online hybrid model, with 25% of sales online. Currently, JencoMart has little presence in Asia, but considers that market key for future growth.
Solution Concept
JencoMart wants to migrate several critical applications to the cloud but has not completed a technical review to determine their suitability for the cloud and the engineering required for migration. They currently host all of these applications on infrastructure that is at its end of life and is no longer supported.
Existing Technical Environment
JencoMart hosts all of its applications in 4 data centers: 3 in North American and 1 in Europe, most applications are dual-homed.
JencoMart understands the dependencies and resource usage metrics of their on-premises architecture.
Application Customer loyalty portal
LAMP (Linux, Apache, MySQL and PHP) application served from the two JencoMart-owned U.S.
data centers.
Database
* Oracle Database stores user profiles
* PostgreSQL database stores user credentials
-homed in US West
Authenticates all users
Compute
* 30 machines in US West Coast, each machine has:
* 20 machines in US East Coast, each machine has:
-core CPU
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.
For this question, refer to the JencoMart case study.
The migration of JencoMart's application to Google Cloud Platform (GCP) is progressing too slowly. The infrastructure is shown in the diagram.
You want to maximize throughput.
What are three potential bottlenecks? (Choose 3 answers.)
- A. A single VPN tunnel, which limits throughput
- B. Complicated internet connectivity between the on-premises infrastructure and GCP
- C. A copy command that is not suited to operate over long distances
- D. Fewer virtual machines (VMs) in GCP than on-premises machines
- E. A tier of Google Cloud Storage that is not suited for this task
- F. A separate storage layer outside the VMs, which is not suited for this task
Answer: A,C,F
NEW QUESTION 74
Your marketing department wants to send out a promotional email campaign. The development team wants to minimize direct operation management. They project a wide range of possible customer responses, from 100 to 500,000 click-throughs per day. The link leads to a simple website that explains the promotion and collects user information and preferences. Which infrastructure should you recommend? (CHOOSE TWO)
- A. Use a single compute Engine virtual machine (VM) to host a web server, backed by Google Cloud SQL.
- B. Use Google App Engine to serve the website and Google Cloud Datastore to store user data.
- C. Use a managed instance group to serve the website and Google Cloud Bigtable to store user data.
- D. Use a Google Container Engine cluster to serve the website and store data to persistent disk.
Answer: B,C
Explanation:
Reference:
References: https://cloud.google.com/storage-options/
NEW QUESTION 75
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 Regional 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 Coldline Storage bucket.
Answer: B
Explanation:
Explanation
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
NEW QUESTION 76
Your company has successfully migrated to the cloud and wants to analyze their data stream to optimize operations. They do not have any existing code for this analysis, so they are exploring all their options. These options include a mix of batch and stream processing, as they are running some hourly jobs and live-processing some data as it comes in. Which technology should they use for this?
- A. Google Cloud Dataflow
- B. Google Cloud Dataproc
- C. Google Compute Engine with Google BigQuery
- D. Google Container Engine with Bigtable
Answer: A
Explanation:
Cloud Dataflow is a fully-managed service for transforming and enriching data in stream (real time) and batch (historical) modes with equal reliability and expressiveness -- no more complex workarounds or compromises needed.
References: https://cloud.google.com/dataflow/
NEW QUESTION 77
Operational parameters such as oil pressure are adjustable on each of TerramEarth's vehicles to increase
their efficiency, depending on their environmental conditions. Your primary goal is to increase the operating
efficiency of all 20 million cellular and unconnected vehicles in the field.
How can you accomplish this goal?
- A. Implement a Google Cloud Dataflow streaming job with a sliding window, and use Google Cloud
Messaging (GCM) to make operational adjustments automatically - B. Have you engineers inspect the data for patterns, and then create an algorithm with rules that make
operational adjustments automatically - C. Capture all operating data, train machine learning models that identify ideal operations, and run locally
to make operational adjustments automatically - D. Capture all operating data, train machine learning models that identify ideal operations, and host in
Google Cloud Machine Learning (ML) Platform to make operational adjustments automatically
Answer: D
Explanation:
Explanation/Reference:
References: https://cloud.google.com/customers/ocado/
Testlet 1
Company Overview
TerramEarth manufactures heavy equipment for the mining and agricultural industries. About 80% of their
business is from mining and 20% from agriculture. They currently have over 500 dealers and service
centers in 100 countries. Their mission is to build products that make their customers more productive.
Solution Concept
There are 20 million TerramEarth vehicles in operation that collect 120 fields of data per second. Data is
stored locally on the vehicle and can be accessed for analysis when a vehicle is serviced. The data is
downloaded via a maintenance port. This same port can be used to adjust operational parameters,
allowing the vehicles to be upgraded in the field with new computing modules.
Approximately 200,000 vehicles are connected to a cellular network, allowing TerramEarth to collect data
directly. At a rate of 120 fields of data per second with 22 hours of operation per day, TerramEarth collects
a total of about 9 TB/day from these connected vehicles.
Existing Technical Environment
TerramEarth's existing architecture is composed of Linux and Windows-based systems that reside in a
single U.S. west coast based data center. These systems gzip CSV files from the field and upload via FTP,
and place the data in their data warehouse. Because this process takes time, aggregated reports are
based on data that is 3 weeks old.
With this data, TerramEarth has been able to preemptively stock replacement parts and reduce unplanned
downtime of their vehicles by 60%. However, because the data is stale, some customers are without their
vehicles for up to 4 weeks while they wait for replacement parts.
Business Requirements
Decrease unplanned vehicle downtime to less than 1 week.
Support the dealer network with more data on how their customers use their equipment to better
position new products and services
Have the ability to partner with different companies - especially with seed and fertilizer suppliers in the
fast-growing agricultural business - to create compelling joint offerings for their customers.
Technical Requirements
Expand beyond a single datacenter to decrease latency to the American Midwest and east coast.
Create a backup strategy.
Increase security of data transfer from equipment to the datacenter.
Improve data in the data warehouse.
Use customer and equipment data to anticipate customer needs.
Application 1: Data ingest
A custom Python application reads uploaded datafiles from a single server, writes to the data warehouse.
Compute:
Windows Server 2008 R2
- 16 CPUs
- 128 GB of RAM
- 10 TB local HDD storage
Application 2: Reporting
An off the shelf application that business analysts use to run a daily report to see what equipment needs
repair. Only 2 analysts of a team of 10 (5 west coast, 5 east coast) can connect to the reporting application
at a time.
Compute:
Off the shelf application. License tied to number of physical CPUs
- Windows Server 2008 R2
- 16 CPUs
- 32 GB of RAM
- 500 GB HDD
Data warehouse:
A single PostgreSQL server
- RedHat Linux
- 64 CPUs
- 128 GB of RAM
- 4x 6TB HDD in RAID 0
Executive Statement
Our competitive advantage has always been in the manufacturing process, with our ability to build better
vehicles for lower cost than our competitors. However, new products with different approaches are
constantly being developed, and I'm concerned that we lack the skills to undergo the next wave of
transformations in our industry. My goals are to build our skills while addressing immediate market needs
through incremental innovations.
NEW QUESTION 78
Which of TerramEarth's legacy enterprise processes will experience significant change as a result of increased Google Cloud Platform adoption?
- A. Capacity planning, TCO calculations, opex/capex allocation
- B. Data Center expansion, TCO calculations, utilization measurement
- C. Opex/capex allocation, LAN changes, capacity planning
- D. Capacity planning, utilization measurement, data center expansion
Answer: A
NEW QUESTION 79
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