Latest Professional-Cloud-Architect Actual Free Exam Updated 378 Questions
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NEW QUESTION # 115
Your architecture calls for the centralized collection of all admin activity and VM system logs within your project.
How should you collect these logs from both VMs and services?
- A. Install the Stackdriver Logging agent on a single compute instance and let it collect all audit and access logs for your environment.
- B. Stackdriver automatically collects admin activity logs for most services. The Stackdriver Logging agent must be installed on each instance to collect system logs.
- C. All admin and VM system logs are automatically collected by Stackdriver.
- D. Launch a custom syslogd compute instance and configure your GCP project and VMs to forward all logs to it.
Answer: B
Explanation:
https://cloud.google.com/logging/docs/agent/
NEW QUESTION # 116
The operations manager asks you for a list of recommended practices that she should consider when migrating a J2EE application to the cloud. Which three practices should you recommend? Choose 3 answers
- A. Migrate from MySQL to a managed NoSQL database like Google Cloud Datastore or Bigtable.
- B. Select an automation framework to reliably provision the cloud infrastructure.
- C. Integrate Cloud Dataflow into the application to capture real-time metrics.
- D. Port the application code to run on Google App Engine.
- E. Deploy a continuous integration tool with automated testing in a staging environment.
- F. Instrument the application with a monitoring tool like Stackdriver Debugger.
Answer: B,D,E
Explanation:
Explanation
References: https://cloud.google.com/appengine/docs/standard/java/tools/uploadinganapp
https://cloud.google.com/appengine/docs/standard/java/building-app/cloud-sql
NEW QUESTION # 117
You are tasked with building an online analytical processing (OLAP) marketing analytics and reporting tool. This requires a relational database that can operate on hundreds of terabytes of data. What is the Google- recommended tool for such applications?
- A. Cloud Spanner, because it is globally distributed
- B. Cloud SQL, because it is a fully managed relational database
- C. BigQuery, because it is designed for large-scale processing of tabular data
- D. Cloud Firestore, because it offers real-time synchronization across devices
Answer: C
Explanation:
Because this requires a relational database
https://cloud.google.com/files/BigQueryTechnicalWP.pdf
BigQuery is relational database and suport OLAP
Cloud Spanner OLTP
NEW QUESTION # 118
Your architecture calls for the centralized collection of all admin activity and VM system logs within your project.
How should you collect these logs from both VMs and services?
- A. All admin and VM system logs are automatically collected by Stackdriver.
- B. Install the Stackdriver Logging agent on a single compute instance and let it collect all audit and access logs for your environment.
- C. Launch a custom syslogd compute instance and configure your GCP project and VMs to forward all logs to it.
- D. Stackdriver automatically collects admin activity logs for most services. The Stackdriver Logging agent must be installed on each instance to collect system logs.
Answer: B
Explanation:
https://cloud.google.com/logging/docs/agent/
NEW QUESTION # 119
Your company has a stateless web API that performs scientific calculations. The web API runs on a single Google Kubernetes Engine (GKE) cluster. The cluster is currently deployed in us-central1. Your company has expanded to offer your API to customers in Asi a. You want to reduce the latency for the users in Asia. What should you do?
- A. Create a second GKE cluster in asia-southeast1, and use kubemci to create a global HTTP(s) load balancer
- B. Use a global HTTP(s) load balancer with Cloud CDN enabled
- C. Increase the memory and CPU allocated to the application in the cluster
- D. Create a second GKE cluster in asia-southeast1, and expose both API's using a Service of type Load Balancer. Add the public Ips to the Cloud DNS zone
Answer: A
Explanation:
https://cloud.google.com/kubernetes-engine/docs/concepts/multi-cluster-ingress#how_works
https://github.com/GoogleCloudPlatform/k8s-multicluster-ingress
https://cloud.google.com/blog/products/gcp/how-to-deploy-geographically-distributed-services-on-kubernetes-engine-with-kubemci
NEW QUESTION # 120
For this question, refer to the Dress4Win case study. Dress4Win is expected to grow to 10 times its size in 1 year with a corresponding growth in data and traffic that mirrors the existing patterns of usage. The CIO has set the target of migrating production infrastructure to the cloud within the next 6 months. How will you configure the solution to scale for this growth without making major application changes and still maximize the ROI?
- A. Migrate RabbitMQ to Cloud Pub/Sub, Hadoop to BigQuery, and NAS to Compute Engine with Persistent Disk storage. Deploy Tomcat, and deploy Nginx using Deployment Manager.
- B. Implement managed instance groups for Tomcat and Nginx. Migrate MySQL to Cloud SQL, RabbitMQ to Cloud Pub/Sub, Hadoop to Cloud Dataproc, and NAS to Compute Engine with Persistent Disk storage.
- C. Implement managed instance groups for the Tomcat and Nginx. Migrate MySQL to Cloud SQL, RabbitMQ to Cloud Pub/Sub, Hadoop to Cloud Dataproc, and NAS to Cloud Storage.
- D. Migrate the web application layer to App Engine, and MySQL to Cloud Datastore, and NAS to Cloud Storage. Deploy RabbitMQ, and deploy Hadoop servers using Deployment Manager.
Answer: B
NEW QUESTION # 121
Your BigQuery project has several users. For audit purposes, you need to see how many queries each user ran in the last month. What should you do?
- A. Use `bq show' to list all jobs. Per job, use `bq Is' to list job information and get the required information.
- B. Use Cloud Audit Logging to view Cloud Audit Logs, and create a filter on the query operation to get the required information.
- C. Connect Google Data Studio to BigQuery. Create a dimension for the users and a metric for the amount of queries per user.
- D. In the BigQuery interface, execute a query on the JOBS table to get the required information.
Answer: B
Explanation:
Cloud Audit Logs maintains audit logs for admin activity, data access and system events.
BIGQUERY is automatically send to cloud audit log functionality.
In the filter you can filter relevant BigQuery Audit messages, you can express filters as part of the export
https://cloud.google.com/logging/docs/audit
https://cloud.google.com/bigquery/docs/reference/auditlogs#ids
https://cloud.google.com/bigquery/docs/reference/auditlogs#auditdata_examples
NEW QUESTION # 122
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
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 wants to move their User Profiles database to Google Cloud Platform. Which Google Database should they use?
- A. Google Cloud Datastore
- B. Cloud Spanner
- C. Google Cloud SQL
- D. Google BigQuery
Answer: A
Explanation:
Common workloads for Google Cloud Datastore:
User profiles
* Product catalogs
* Game state
* References: https://cloud.google.com/storage-options/
https://cloud.google.com/datastore/docs/concepts/overview
NEW QUESTION # 123
You are implementing a single Cloud SQL MySQL second-generation database that contains business-critical transaction dat a. You want to ensure that the minimum amount of data is lost in case of catastrophic failure. Which two features should you implement? (Choose two.)
- A. Automated backups
- B. Binary logging
- C. Read replicas
- D. Sharding
- E. Semisynchronous replication
Answer: A,B
Explanation:
Backups help you restore lost data to your Cloud SQL instance. Additionally, if an instance is having a problem, you can restore it to a previous state by using the backup to overwrite it. Enable automated backups for any instance that contains necessary data. Backups protect your data from loss or damage.
Enabling automated backups, along with binary logging, is also required for some operations, such as clone and replica creation.
NEW QUESTION # 124
You are implementing Firestore for Mountkirk Games. Mountkirk Games wants to give a new game programmatic access to a legacy game's Firestore database. Access should be as restricted as possible. What should you do?
- A. Create a service account (SA) in the lgacy game's Google Cloud project, give the SA the Organization Admin rule and then give it the Firebase Admin role in both projects
- B. Create a service account (SA) in the legacy game's Google Cloud project, add this SA in the new game's IAM page, and then give it the Firebase Admin role in both projects
- C. Create a service account (SA) in the legacy game's Google Cloud project, add a second SA in the new game's IAM page, and then give the Organization Admin role to both SAs
- D. Create a service account (SA) in the legacy game's Google Cloud project, give it the Firebase Admin role, and then migrate the new game to the legacy game's project.
Answer: B
NEW QUESTION # 125
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. Load data into Google BigQuery
- B. Stream data into Google Cloud Datastore
- C. Put flat files into Google Cloud Storage
- D. Insert data into Google Cloud SQL
Answer: A
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.
References: https://cloud.google.com/bigquery/
NEW QUESTION # 126
You need to deploy an application to Google Cloud. The application receives traffic via TCP and reads and writes data to the filesystem. The application does not support horizontal scaling. The application process requires full control over the data on the file system because concurrent access causes corruption. The business is willing to accept a downtime when an incident occurs, but the application must be available 24/7 to support their business operations. You need to design the architecture of this application on Google Cloud.
What should you do?
- A. Use a managed instance group with instances in multiple zones, use Cloud Filestore, and use an HTTP load balancer in front of the instances.
- B. Use an unmanaged instance group with an active and standby instance in different zones, use a regional persistent disk, and use an HTTP load balancer in front of the instances.
- C. Use an unmanaged instance group with an active and standby instance in different zones, use a regional persistent disk, and use a network load balancer in front of the instances.
- D. Use a managed instance group with instances in multiple zones, use Cloud Filestore, and use a network load balancer in front of the instances.
Answer: C
Explanation:
Reference: https://cloud.google.com/compute/docs/instance-groups
NEW QUESTION # 127
TerramEarth plans to connect all 20 million vehicles in the field to the cloud. This increases the volume to 20 million 600 byte records a second for 40 TB an hour.
How should you design the data ingestion?
- A. Vehicles write data directly to GCS
- B. Vehicles write data directly to Google Cloud Pub/Sub
- C. Vehicles continue to write data using the existing system (FTP)
- D. Vehicles stream data directly to Google BigQuery
Answer: D
NEW QUESTION # 128
A lead software engineer tells you that his new application design uses websockets and HTTP sessions that are not distributed across the web servers. You want to help him ensure his application will run property on Google Cloud Platform. What should you do?
- A. Help the engineer redesign the application to use a distributed user session service that does not rely on websockets and HTTP sessions.
- B. Review the encryption requirements for websocket connections with the security team.
- C. Help the engineer to convert his websocket code to use HTTP streaming.
- D. Meet with the cloud operations team and the engineer to discuss load balancer options.
Answer: D
Explanation:
Google Cloud Platform (GCP) HTTP(S) load balancing provides global load balancing for HTTP(S) requests destined for your instances.
The HTTP(S) load balancer has native support for the WebSocket protocol.
NEW QUESTION # 129
Your company acquired a healthcare startup and must retain its customers' medical information for up to 4 more years, depending on when it was created. Your corporate policy is to securely retain this data, and then delete it as soon as regulations allow.
Which approach should you take?
- A. Store the data in Google Drive and manually delete records as they expire.
- B. Anonymize the data using the Cloud Data Loss Prevention API and store it indefinitely.
- C. Store the data in Cloud Storage and run a nightly batch script that deletes all expired data.
- D. Store the data in Cloud Storage and use lifecycle management to delete files when they expire.
Answer: D
Explanation:
Explanation/Reference:
NEW QUESTION # 130
You company has a Kubernetes application that pulls messages from Pub/Sub and stores them in Firestore.
Because the application is simple, it was deployed as a single pod. The infrastructure team has analyzed Pub/Sub metrics and discovered that the application cannot process the messages in real time. Most of them wait for minutes before being processed. You need to scale the elaboration process that is I/O-intensive. What should you do?
- A. Configure a Kubernetes autoscaling based on the subscription/push_request metric.
- B. Use kubectl autoscale deployment APP_NAME -max 6 -min 2 -cpu- percent 50 to configure Kubernetes autoscaling deployment
- C. Use the -enable- autoscaling flag when you create the Kubernetes cluster
- D. Configure a Kubernetes autoscaling based on the subscription/num_undelivered message metric.
Answer: A
Explanation:
Explanation
https://cloud.google.com/kubernetes-engine/docs/concepts/custom-and-external-metrics#external_metrics
NEW QUESTION # 131
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