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Nun gibt es viele IT-Profis in der ganzen Welt und die Konkurrenz der IT-Branche ist sehr hart. So viele IT-Profis entscheiden sich dafür, an der IT-Zertifizierungsprüfung teilzunehmen, um ihre Position in der IT-Branche zu verstärken. Die Professional-Cloud-Architect Prüfung ist eine sehr wichtige Google-Zertifizierungsprüfung. Aber wenn Sie eine Google-Zertifizierung erhalten wollen, müssen Sie die Prüfung bestehen.

Google Professional-Cloud-Architect Prüfungsplan:

Thema	Einzelheiten
Thema 1	Managing Implementation Ensuring Solution and Operations Reliability Deployment and Release Management
Thema 2	Designing a Solution Infrastructure that Meets Business Requirements Business Use Cases and Product Strategy
Thema 3	Designing for Security and Compliance Resource Hierarchy (organizations, folders, projects) Managing Customer-Supplied Encryption Keys with Cloud KMS
Thema 4	Cloud Native Networking (VPC, Peering, Firewalls, Container Networking) Identification of Data Processing Pipeline
Thema 5	Designing Network, Storage, and Compute Resources Integration with on Premises Multi-Cloud Environments
Thema 6	Data Processing Compute Provisioning Network Configuration for Data Transfer and Latency Data Growth Management
Thema 7	Analyzing and Pptimizing Technical and Business Processes Analyzing and Defining Technical Processes, Software Development Lifecycle Plan
Thema 8	Creating a Migration Plan (i.e., documents and architectural diagrams) Integrating Solution with Existing Systems
Thema 9	Designing a Solution Infrastructure that Meets Technical Requirements High Availability and Failover Design
Thema 10	Managing and Provisioning Solution Infrastructure Configuring Network Topologies, Extending to on-Premise|Extending to a Multi-Cloud Environment Which May Include GCP to GCP Communication Configuring Individual Storage Systems

>> Professional-Cloud-Architect Simulationsfragen <<

Professional-Cloud-Architect Online Prüfungen, Professional-Cloud-Architect Deutsche Prüfungsfragen

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Google Certified Professional - Cloud Architect (GCP) Professional-Cloud-Architect Prüfungsfragen mit Lösungen (Q87-Q92):

87. Frage
You have been asked to select the storage system for the click-data of your company's large portfolio of websites. This data is streamed in from a custom website analytics package at a typical rate of 6,000 clicks per minute. With bursts of up to 8,500 clicks per second. It must have been stored for future analysis by your data science and user experience teams.
Which storage infrastructure should you choose?

• A. Google Cloud Storage
• B. Google Cloud Bigtable
• C. Google Cloud Datastore
• D. Google Cloud SQL

Antwort: B Begründung:
Explanation/Reference:
Explanation:
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

Incorrect Answers:
C: Google Cloud Storage is a scalable, fully-managed, highly reliable, and cost-efficient object / blob store.
Is good for:
Images, pictures, and videos

Objects and blobs

Unstructured data

D: Google Cloud Datastore is a scalable, fully-managed NoSQL document database for your web and mobile applications.
Is good for:
Semi-structured application data

Hierarchical data

Durable key-value data

Common workloads:

User profiles

Product catalogs

Game state

References: https://cloud.google.com/storage-options/
88. Frage
You are creating a solution to remove backup files older than 90 days from your backup Cloud Storage bucket. You want to optimize ongoing Cloud Storage spend. What should you do?

• A. Write a lifecycle management rule in JSON and push it to the bucket with gsutil.
• B. Schedule a cron script using gsutil is -lr gs://backups/** to find and remove items older than
  90 days.
• C. Write a lifecycle management rule in XML and push it to the bucket with gsutil.
• D. Schedule a cron script using gsutil ls -1 gs://backups/** to find and remove items older than
  90 days and schedule it with cron.

Antwort: A Begründung:
https://cloud.google.com/storage/docs/gsutil/commands/lifecycle
89. Frage
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 would like to become familiar with deploying applications to the cloud by successfully deploying some applications quickly, as is. They have asked for your recommendation. What should you advise?

• A. Suggest moving their in-house databases to the cloud and continue serving requests to on- premise applications.
• B. Recommend moving their message queuing servers to the cloud and continue handling requests to on-premise applications.
• C. Identify enterprise applications with internal dependencies and recommend these as a first move to the cloud.
• D. Identify self-contained applications with external dependencies as a first move to the cloud.

Antwort: D
90. Frage
Your application needs to process credit card transactions. You want the smallest scope of Payment Card Industry (PCI) compliance without compromising the ability to analyze transactional data and trends relating to which payment methods are used. How should you design your architecture?

• A. Create a tokenizer service and store only tokenized data.
• B. Enable Logging export to Google BigQuery and use ACLs and views to scope the data shared with the auditor.
• C. Streamline the audit discovery phase by labeling all of the virtual machines (VMs) that process PCI data.
• D. Create separate subnetworks and isolate the components that process credit card data.
• E. Create separate projects that only process credit card data.

Antwort: B
91. Frage
You are helping the QA team to roll out a new load-testing tool to test the scalability of your primary cloud services that run on Google Compute Engine with Cloud Bigtable.
Which three requirements should they include? Choose 3 answers

• A. Instrument the load-testing tool and the target services with detailed logging and metrics collection.
• B. Ensure that the load tests validate the performance of Cloud Bigtable.
• C. Instrument the production services to record every transaction for replay by the load-testing tool.
• D. Ensure all third-party systems your services use are capable of handling high load.
• E. Schedule the load-testing tool to regularly run against the production environment.
• F. Create a separate Google Cloud project to use for the load-testing environment.

Antwort: A,B,F Begründung:
A (Correct answer) - Ensure that the load tests validate the performance of Cloud Bigtable.
At first thought, it seems Bigtable is managed service seamlessly scaling, there is no need to load test it. But you probably already know, there are many factors impacting the Bigtable performance. The common one of them, poorly designed table structure.
With poorly performed BigTable, the cluster would continue to scale, add more and more nodes, as the load increasing, cost more and more. Not matter how good is the cluster managed, this is exact situation that needs to prevent. In fact, tests validate the performance of Cloud Bigtable is one of the most important testing goals for BigTable performance.
B (Correct answer) - Create a separate Google Cloud project to use for the load-testing environment.
This is a good practice for least privileges and separation of responsibilities.
C - Schedule the load-testing tool to regularly run against the production environment.
You should not do load testing RGULARLY against production environment; In fact, somebody has suggested Load test in production should avoid entirely.
D - Ensure all third-party systems your services used are capable of handling high load This is out of scope - it's beyond your control. You may test them, but you cannot control them. If you have doubts the third-party dependencies causing the overall performance issue, you may use integration test to identify and isolate them. This should not be your focus.
E - Instrument the production services to record every transaction for replay by the load-testing tool.
This would be way too much: not only the detailed instrumentation may impact the production performance, it's also possible the instrumentation itself distorts the test results - remember, Bigtable is for multiple terabyte or even petabyte NoSQL database for high throughput with low latency read and write.
F (Correct answer) - Instrument the load-testing tool and the target services with detailed logging and metrics collection.
This is normal requirement and practice for load testing to collect testing results with detailed measurable metric and historical logs otherwise load testing would be meaningless More Resource Understanding Cloud Bigtable Performance
https://cloud.google.com/bigtable/docs/performance
92. Frage
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