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100％合格率Professional-Cloud-Architect｜最高のProfessional-Cloud-Architect実際試験試験｜試験の準備方法Google Certified Professional - Cloud Architect (GCP)資格トレーリング

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Google Certified Professional - Cloud Architect (GCP) 認定 Professional-Cloud-Architect 試験問題 (Q357-Q362):

質問 # 357
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.
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. Total visits and average latency for users in Asia
D. The number of character sets present in the database
E. Error rates for requests from Asia

正解：C

解説：
From scenario:
Business Requirements include: Expand services into Asia
Technical Requirements include: Decrease latency in Asia

質問 # 358
A development team at your company has created a dockerized HTTPS web application. You need to deploy the application on Google Kubernetes Engine (GKE) and make sure that the application scales automatically. How should you deploy to GKE?

A. Enable autoscaling on the Compute Engine instance group. Use an Ingress resource to load balance the HTTPS traffic.
B. Use the Horizontal Pod Autoscaler and enable cluster autoscaling on the Kubernetes cluster. Use a Service resource of type LoadBalancer to load-balance the HTTPS traffic.
C. Use the Horizontal Pod Autoscaler and enable cluster autoscaling. Use an Ingress resource to load- balance the HTTPS traffic.
D. Enable autoscaling on the Compute Engine instance group. Use a Service resource of type LoadBalancer to load-balance the HTTPS traffic.

正解：C

解説：
When you specify kind: Ingress in a resource manifest, you instruct GKE to create an Ingress resource. By including annotations and supporting workloads and Services, you can create a custom Ingress controller. Otherwise, GKE makes appropriate Google Cloud API calls to create an external HTTP(S) load balancer.If you are exposing an HTTP(S) service hosted on GKE, HTTP(S) load balancing is the recommended method for load balancing.External Network Load Balancing.
When you specify kind: Service with type: LoadBalancer in a resources manifest, GKE creates a Service of type LoadBalancer. Although you can use either of these types of load balancers for HTTP(S) traffic, they operate in OSI layers 3/4 and are not aware of HTTP connections or individual HTTP requests and responses. Another important characteristic is that the requests are not proxied to the destination.
https://cloud.google.com/kubernetes-engine/docs/tutorials/http-balancerIngress

質問 # 359
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 managed instance group to serve the website and Google Cloud Bigtable to store user data.
B. Use a single compute Engine virtual machine (VM) to host a web server, backed by Google Cloud SQL.
C. Use a Google Container Engine cluster to serve the website and store data to persistent disk.
D. Use Google App Engine to serve the website and Google Cloud Datastore to store user data.

正解：A、D

解説：
Reference:

質問 # 360
One of the developers on your team deployed their application in Google Container Engine with the Dockerfile below. They report that their application deployments are taking too long.

You want to optimize this Dockerfile for faster deployment times without adversely affecting the app's functionality.
Which two actions should you take? Choose 2 answers.

A. Remove Python after running pip.
B. Remove dependencies from requirements.txt.
C. Use a slimmed-down base image like Alpine linux.
D. Copy the source after the package dependencies (Python and pip) are installed.
E. Use larger machine types for your Google Container Engine node pools.

正解：C、D

解説：
The speed of deployment can be changed by limiting the size of the uploaded app, limiting the complexity of the build necessary in the Dockerfile, if present, and by ensuring a fast and reliable internet connection.
Note: Alpine Linux is built around musl libc and busybox. This makes it smaller and more resource efficient than traditional GNU/Linux distributions. A container requires no more than 8 MB and a minimal installation to disk requires around 130 MB of storage. Not only do you get a fully-fledged Linux environment but a large selection of packages from the repository.
References: https://groups.google.com/forum/#!topic/google-appengine/hZMEkmmObDU
https://www.alpinelinux.org/about/

質問 # 361
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 Compute Engine managed instance groups with auto-scaling
B. Google Cloud Dataproc to run Apache Hadoop jobs to process each test
C. Google App Engine with Google Stackdriver for logging
D. Google Compute Engine unmanaged instance groups and Network Load Balancer

正解：A

解説：
https://cloud.google.com/compute/docs/instance-groups/

質問 # 362
......

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