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Google Professional-Cloud-Architect Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Analyzing and optimizing technical and business processes	15%	- Improving reliability and performance 1. SLO, SLA, and error budgeting 2. Latency reduction and throughput optimization - Optimizing cost and resource efficiency 1. Committed use discounts and pricing models 2. Resource right-sizing and usage monitoring - Streamlining operational workflows 1. Change management and incident response 2. Stakeholder communication and alignment
Topic 2: Designing and planning a cloud solution architecture	25%	- Evaluating and selecting Google Cloud services 1. Serverless and managed service adoption 2. Compute, storage, database, and networking service selection - Planning cloud migration and hybrid/multi-cloud environments 1. Data transfer and synchronization 2. Migration planning and execution 3. Interoperability and integration design - Designing cloud solution infrastructure aligned with business requirements 1. Compliance and regulatory requirements consideration 2. Cost optimization strategies 3. Scalability, high availability, and fault tolerance design
Topic 3: Ensuring solution and operations excellence	12.5%	- Planning for continuous improvement 1. Technology updates and architecture evolution 2. Feedback loops and optimization cycles - Implementing monitoring, logging, and observability 1. Alerting, dashboarding, and root cause analysis 2. Cloud Monitoring, Logging, and Error Reporting - Applying Well-Architected Framework principles 1. Operational excellence, reliability, security, cost, and performance pillars
Topic 4: Designing for security and compliance	17.5%	- Securing data and communications 1. Encryption at rest and in transit 2. Key management and secret security - Enforcing compliance and governance 1. VPC Service Controls and security perimeters 2. Security controls, auditing, and logging - Implementing identity and access management 1. Organizational policies and resource hierarchy 2. IAM roles, permissions, and service accounts
Topic 5: Managing implementation	12.5%	- Using Google Cloud tools and APIs programmatically 1. Cloud SDK, Cloud Shell, and Cloud Code 2. Infrastructure as Code (Terraform, Deployment Manager) - Guiding development and deployment teams 1. Application and infrastructure deployment strategies 2. CI/CD pipelines and automation - Testing and validating solutions 1. Functional, performance, and security testing 2. Disaster recovery and failover testing
Topic 6: Managing and provisioning solution infrastructure	15%	- Managing storage and data services 1. Database deployment, replication, and backup 2. Cloud Storage, Filestore, Persistent Disk management - Configuring network topologies and connectivity 1. Load balancing and CDN configuration 2. VPC design, peering, and hybrid connectivity - Provisioning and managing compute resources 1. VMs, GKE, App Engine, Cloud Run deployment and management 2. Auto-scaling and resource management

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Google Certified Professional - Cloud Architect (GCP) Sample Questions (Q22-Q27):

NEW QUESTION # 22
Your company has a Google Cloud project that uses BigQuery for data warehousing on a pay-per-use basis.
You want to monitor queries in real time to discover the most costly queries and which users spend the most.
What should you do?

A. 1. Create a Cloud Logging sink to export BigQuery data access logs to BigQuery.
2. Perform a BigQuery query on the generated table to extract the information you need.
B. 1. In the BigQuery dataset that contains all the tables to be queried, add a label for each user that can launch a query.
2. Open the Billing page of the project.
3. Select Reports.
4. Select BigQuery as the product and filter by the user you want to check.
C. 1. Create a Cloud Logging sink to export BigQuery data access logs to Cloud Storage. 2. Develop a Dataflow pipeline to compute the cost of queries split by users.
D. 1. Activate billing export into BigQuery.
2. Perform a BigQuery query on the billing table to extract the information you need.

Answer: D

Explanation:
Explanation
https://cloud.google.com/blog/products/data-analytics/taking-a-practical-approach-to-bigquery-cost-monitoring

NEW QUESTION # 23
Your BigQuery project has several users. For audit purposes, you need to see how many queries each user ran in the last month.

A. In the BigQuery interface, execute a query on the JOBS table to get the required information.
B. Connect Google Data Studio to BigQuery. Create a dimension for the users and a metric for the amount of queries per user.
C. Use 'bq show' to list all jobs. Per job, use 'bq Is' to list job information and get the required information.
D. Use Cloud Audit Logging to view Cloud Audit Logs, and create a filter on the query operation to get the required information.

Answer: C

NEW QUESTION # 24
Your company wants to deploy several microservices to help their system handle elastic loads.
Each microservice uses a different version of software libraries. You want to enable their developers to keep their development environment in sync with the various production services.
Which technology should you choose?

A. Containers
B. Chef/Puppet
C. RPM/DEB
D. Virtual machines

Answer: A

Explanation:
A is not correct because although OS packages are a convenient way to distribute and deploy libraries, they don't directly help with synchronizing. Even with a common repository, the development environments will probably deviate from production.
B is correct because using containers for development, test, and production deployments abstracts away system OS environments, so that a single host OS image can be used for all environments. Changes that are made during development are captured using a copy-on-write filesystem, and teams can easily publish new versions of the microservices in a repository.
C is not correct because although infrastructure configuration as code can help unify production and test environments, it is very difficult to make all changes during development this way.
D is not correct because virtual machines run their own OS, which will eventually deviate in each environment, just as now.

NEW QUESTION # 25
You have created several preemptible Linux virtual machine instances using Google Compute Engine. You want to properly shut down your application before the virtual machines are preempted. What should you do?

A. Create a shutdown script named k99.shutdown in the /etc/rc.6.d/ directory.
B. Create a shutdown script registered as a xinetd service in Linux and configure a Stackdnver endpoint check to call the service.
C. Create a shutdown script, registered as a xinetd service in Linux, and use the gcloud compute instances add-metadata command to specify the service URL as the value for a new metadata entry with the key shutdown-script-url
D. Create a shutdown script and use it as the value for a new metadata entry with the key shutdown-script in the Cloud Platform Console when you create the new virtual machine instance.

Answer: A

NEW QUESTION # 26
For this question refer to the TerramEarth case study
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 your 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: C

Explanation:
Topic 1, 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.

NEW QUESTION # 27
......

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