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認定試験は、複数選択肢の問題から構成され、候補者のGCPに関する知識と理解力を評価します。試験は異なるセクションに分かれており、それぞれのセクションは特定のGCP領域に焦点を当てています。試験は、GCPインフラストラクチャ、ネットワーキング、セキュリティ、データストレージ、データ処理、およびアプリケーション開発などのトピックをカバーしています。試験に合格するためには、候補者は試験で少なくとも70％の点数を取る必要があります。
認定試験は、クラウドソリューションアーキテクチャの設計と計画、クラウドソリューションインフラストラクチャの管理とプロビジョニング、クラウドソリューション環境の最適化とセキュリティ、技術的およびビジネスプロセスの分析と最適化など、幅広いトピックをカバーしています。試験は、候補者が自己の組織のニーズを満たすスケーラブルで信頼性の高い、コスト効果の高いクラウドソリューションを設計・展開する能力を評価するために設計されています。
>> Google Professional-Cloud-Architect認定資格試験問題集 <<
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Google Professional-Cloud-Architect認定試験は、2時間以内に完了する必要がある50の複数選択と複数選択の質問で構成されています。この試験では、クラウドソリューションアーキテクチャの設計と計画、クラウドインフラストラクチャの管理とプロビジョニング、クラウドソリューションのセキュリティとコンプライアンスの確保など、いくつかの分野で候補者の習熟度を測定します。この試験では、クラウドネイティブアーキテクチャの原則、アプリケーション開発方法論、およびハイブリッドおよびマルチクラウドソリューションに関する候補者の理解もテストします。
質問 # 319
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?
正解：C
解説：
Explanation
https://cloud.google.com/solutions/federating-gcp-with-active-directory-introduction#implementing_federation
質問 # 320
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
service level agreement (SLA)
Authenticates all users
Compute
* 30 machines in US West Coast, each machine has:
* 20 machines in US East Coast, each machine has:
-core CPU
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 decided to migrate user profile storage to Google Cloud Datastore and the application servers to Google Compute Engine (GCE). During the migration, the existing infrastructure will need access to Datastore to upload the data. What service account key- management strategy should you recommend?
正解：C
解説：
A) (correct answer) This addresses both of data migration and application server migration properly.
"Provision service account keys for the on-premises infrastructure": For code running on systems outside Google, you cannot use GCP-managed keys. You need to create Service account for it and provision User-managed keys. These keys are created, downloadable, and managed by users - This is solution for on-premises access to GCP datastore during migration
"use Google Cloud Platform (GCP) managed keys for the VMs" - this is solution for Application server migration since there is no external access to GCP is required during the migration.
Answer B is incorrect: First, the applications running on-premises to access GCP Datastore assume the identity of the service account to call Google APIs, so that the users aren't directly involved.
Secondly, for the application server migration to GCP VMs, you can use GCP managed keys for the VMs. It's simple and effective. There is no need to provision and manage keys (User- managed keys) by yourself for the VMs.
GCP-managed keys are used by Cloud Platform services such as App Engine and Compute Engine. These keys cannot be downloaded. Google will keep the keys and automatically rotate them on an approximately weekly basis.
C) is incorrect in the solution for on-premises access to GCP Datastore - This is possible options that might require more setup than worthwhile for the requirements.
D) is incorrect for reason of application server migration: you can use GCP managed keys for the VMs. It's simple and effective. There is no need to provision and manage keys (User-managed keys) by yourself for the application VMs
質問 # 321
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?
正解：D
解説：
https://cloud.google.com/storage/docs/request-rate
Use a naming convention that distributes load evenly across key ranges
Auto-scaling of an index range can be slowed when using sequential names, such as object keys based on a sequence of numbers or timestamp. This occurs because requests are constantly shifting to a new index range, making redistributing the load harder and less effective.
In order to maintain a high request rate, avoid using sequential names. Using completely random object names will give you the best load distribution.
質問 # 322
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?
正解：C
解説：
Explanation/Reference:
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/
質問 # 323
For this question, refer to the TerramEarth case study. A new architecture that writes all incoming data to BigQuery has been introduced. You notice that the data is dirty, and want to ensure data quality on an automated daily basis while managing cost.
What should you do?
正解：D
解説：
Topic 8, Mountkrik Games Case 2
Company Overview
Mountkirk Games makes online, session-based, multiplayer games for mobile platforms. They build all of their games using some server-side integration. Historically, they have used cloud providers to lease physical servers.
Due to the unexpected popularity of some of their games, they have had problems scaling their global audience, application servers, MySQL databases, and analytics tools.
Their current model is to write game statistics to files and send them through an ETL tool that loads them into a centralized MySQL database for reporting.
Solution Concept
Mountkirk Games is building a new game, which they expect to be very popular. They plan to deploy the game's backend on Google Compute Engine so they can capture streaming metrics, run intensive analytics, and take advantage of its autoscaling server environment and integrate with a managed NoSQL database.
Business Requirements
Increase to a global footprint.
Improve uptime - downtime is loss of players.
Increase efficiency of the cloud resources we use.
Reduce latency to all customers.
Technical Requirements
Requirements for Game Backend Platform
Dynamically scale up or down based on game activity.
Connect to a transactional database service to manage user profiles and game state.
Store game activity in a timeseries database service for future analysis.
As the system scales, ensure that data is not lost due to processing backlogs.
Run hardened Linux distro.
Requirements for Game Analytics Platform
Dynamically scale up or down based on game activity
Process incoming data on the fly directly from the game servers
Process data that arrives late because of slow mobile networks
Allow queries to access at least 10 TB of historical data
Process files that are regularly uploaded by users' mobile devices
Executive Statement
Our last successful game did not scale well with our previous cloud provider, resulting in lower user adoption and affecting the game's reputation. Our investors want more key performance indicators (KPIs) to evaluate the speed and stability of the game, as well as other metrics that provide deeper insight into usage patterns so we can adapt the game to target users. Additionally, our current technology stack cannot provide the scale we need, so we want to replace MySQL and move to an environment that provides autoscaling, low latency load balancing, and frees us up from managing physical servers.
質問 # 324
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