Updated Apr-2024 Test Engine to Practice Professional-Cloud-Architect Test Questions
Professional-Cloud-Architect Real Exam Questions Test Engine Dumps Training With 278 Questions
The benefit of obtaining the Google Professional Cloud Architect Exam Certification
- Google Professional Cloud Architect certification has more useful and relevant networks that help them in setting career goals for themselves. Google Professional Cloud Architect networks provide them with the correct career guidance than non certified generally are unable to get.
- Google Professional Cloud Architect Certification is distinguished among competitors. Google Professional Cloud Architect certification can give them an edge at that time easily when candidates appear for employment interview, employers are very fascinated to note one thing that differentiates the individual from all other candidates.
- Google Professional Cloud Architect Certifications provide opportunities to get a job easily in which they are interested in instead of wasting years and ending without getting any experience.
- Google Professional Cloud Architect Exam provide proven knowledge to use the tools to complete the task efficiently and cost effectively than the other non-certified professionals lack in doing so.
NEW QUESTION # 110
For this question, refer to the TerramEarth case study
Your development team has created a structured API to retrieve vehicle data. They want to allow third parties to develop tools for dealerships that use this vehicle event data. You want to support delegated authorization against this data. What should you do?
- A. Restrict data access based on the source IP address of the partner systems.
- B. Build SAML 2.0 SSO compatibility into your authentication system.
- C. Build or leverage an OAuth-compatible access control system.
- D. Create secondary credentials for each dealer that can be given to the trusted third party.
Answer: C
Explanation:
https://cloud.google.com/appengine/docs/flexible/go/authorizing-apps
https://cloud.google.com/docs/enterprise/best-practices-for-enterprise-organizations#delegate_application_authorization_with_oauth2 Delegate application authorization with OAuth2 Cloud Platform APIs support OAuth 2.0, and scopes provide granular authorization over the methods that are supported. Cloud Platform supports both service-account and user-account OAuth, also called three-legged OAuth.
References:
https://cloud.google.com/docs/enterprise/best-practices-for-enterprise-organizations#delegate_application_authorization_with_oauth2
https://cloud.google.com/appengine/docs/flexible/go/authorizing-apps
NEW QUESTION # 111
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, 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
- B. 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.
- C. Create a shutdown script registered as a xinetd service in Linux and configure a Stackdnver endpoint check to call the service.
- D. Create a shutdown script named k99.shutdown in the /etc/rc.6.d/ directory.
Answer: D
NEW QUESTION # 112
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 App Engine with Google Stackdriver for logging
- B. Google Compute Engine unmanaged instance groups and Network Load Balancer
- C. Google Cloud Dataproc to run Apache Hadoop jobs to process each test
- D. Google Compute Engine managed instance groups with auto-scaling
Answer: D
Explanation:
Reference:
https://cloud.google.com/compute/docs/instance-groups/
Google Compute Engine enables users to launch virtual machines (VMs) on demand. VMs can be launched from the standard images or custom images created by users.
Managed instance groups offer autoscaling capabilities that allow you to automatically add or remove instances from a managed instance group based on increases or decreases in load. Autoscaling helps your applications gracefully handle increases in traffic and reduces cost when the need for resources is lower.
NEW QUESTION # 113
Dress4Win has end-to-end tests covering 100% of their endpoints.
They want to ensure that the move to the cloud does not introduce any new bugs.
Which additional testing methods should the developers employ to prevent an outage?
- A. They should add canary tests so developers can measure how much of an impact the new release
causes to latency. - B. They should add additional unit tests and production scale load tests on their cloud staging
environment. - C. They should enable Google Stackdriver Debugger on the application code to show errors in the code.
- D. They should run the end-to-end tests in the cloud staging environment to determine if the code is
working as intended.
Answer: B
NEW QUESTION # 114
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. 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.
- B. Enable autoscaling on the Compute Engine instance group. Use an Ingress resource to load balance the HTTPS traffic.
- C. Enable autoscaling on the Compute Engine instance group. Use a Service resource of type LoadBalancer to load-balance the HTTPS traffic.
- D. Use the Horizontal Pod Autoscaler and enable cluster autoscaling. Use an Ingress resource to loadbalance the HTTPS traffic.
Answer: A
Explanation:
https://cloud.google.com/kubernetes-engine/docs/tutorials/http-balancer
https://cloud.google.com/kubernetes-engine/docs/concepts/network-overview#ext-lb
NEW QUESTION # 115
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. Schedule a cron script using gsutil is -lr gs://backups/** to find and remove items older than
90 days. - B. Schedule a cron script using gsutil ls -1 gs://backups/** to find and remove items older than
90 days and schedule it with cron. - C. Write a lifecycle management rule in XML and push it to the bucket with gsutil.
- D. Write a lifecycle management rule in JSON and push it to the bucket with gsutil.
Answer: D
Explanation:
https://cloud.google.com/storage/docs/gsutil/commands/lifecycle
NEW QUESTION # 116
For this question, refer to the JencoMart case study.
The migration of JencoMart's application to Google Cloud Platform (GCP) is progressing too slowly. The infrastructure is shown in the diagram. You want to maximize throughput.
What are three potential bottlenecks? (Choose 3 answers.)
- A. A copy command that is not suited to operate over long distances
- B. A tier of Google Cloud Storage that is not suited for this task
- C. Complicated internet connectivity between the on-premises infrastructure and GCP
- D. A single VPN tunnel, which limits throughput
- E. A separate storage layer outside the VMs, which is not suited for this task
- F. Fewer virtual machines (VMs) in GCP than on-premises machines
Answer: C,D,E
NEW QUESTION # 117
You want to optimize the performance of an accurate, real-time, weather-charting application.
The data comes from 50,000 sensors sending 10 readings a second, in the format of a timestamp and sensor reading. Where should you store the data?
- A. Google Cloud Storage
- B. Google Cloud SQL
- C. Google Cloud Bigtable
- D. Google BigQuery
Answer: C
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
* References: https://cloud.google.com/storage-options/
NEW QUESTION # 118
For this question, refer to the Dress4Win case study. You want to ensure that your on-premises
architecture meets business requirements before you migrate your solution.
What change in the on-premises architecture should you make?
- A. Replace RabbitMQ with Google Pub/Sub.
- B. Downgrade MySQL to v5.7, which is supported by Cloud SQL for MySQL.
- C. Containerize the micro services and host them in Google Kubernetes Engine.
- D. Resize compute resources to match predefined Compute Engine machine types.
Answer: D
Explanation:
Explanation/Reference:
Question Set 1
NEW QUESTION # 119
Case Study: 7 - Mountkirk Games
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.
For this question, refer to the Mountkirk Games case study. You need to analyze and define the technical architecture for the database workloads for your company, Mountkirk Games.
Considering the business and technical requirements, what should you do?
- A. Use Cloud Bigtable to replace MySQL, and use BigQuery for historical data queries.
- B. Use Cloud SQL for time series data, and use Cloud Bigtable for historical data queries.
- C. Use Cloud SQL to replace MySQL, and use Cloud Spanner for historical data queries.
- D. Use Cloud Bigtable for time series data, use Cloud Spanner for transactional data, and use BigQuery for historical data queries.
Answer: D
NEW QUESTION # 120
You need to develop procedures to test a disaster plan for a mission-critical application. You want to use Google-recommended practices and native capabilities within GCP.
What should you do?
- A. Use gcloud scripts to automate service provisioning. Use Activity Logs monitor and debug your tests.
- B. Use Deployment Manager to automate service provisioning. Use Stackdriver to monitor and debug your tests.
- C. Use gcloud scripts to automate service provisioning. Use Stackdriver to monitor and debug your tests.
- D. Use Deployment Manager to automate service provisioning. Use Activity Logs to monitor and debug your tests.
Answer: B
NEW QUESTION # 121
You have a Python web application with many dependencies that requires 0.1 CPU cores and 128 MB of memory to operate in production. You want to monitor and maximize machine utilization. You also to reliably deploy new versions of the application. Which set of steps should you take?
- A. Perform the following:
1) Create a managed instance group with n1-standard-1 type machines.
2) Build a Compute Engine image from the production branch that contains all of the dependencies and automatically starts the Python app.
3) Rebuild the Compute Engine image, and update the instance template to deploy new production releases. - B. Perform the following:
1) Create a managed instance group with f1-micro type machines.
2) Use a startup script to clone the repository, check out the production branch, install the dependencies, and start the Python app.
3) Restart the instances to automatically deploy new production releases. - C. Perform the following:
1) Create a Kubernetes Engine cluster with n1-standard-1 type machines.
2) Build a Docker image from the production branch with all of the dependencies, and tag it with the
3) Create a Kubernetes Deployment with the imagePullPolicy set to "IfNotPresent" in the staging namespace, and then promote it to the production namespace after testing. - D. Perform the following:
1) Create a Kubernetes Engine (GKE) cluster with n1-standard-4 type machines.
2) Build a Docker image from the master branch will all of the dependencies, and tag it with "latest".
3) Create a Kubernetes Deployment in the default namespace with the imagePullPolicy set to "Always".
Restart the pods to automatically deploy new production releases.
Answer: D
Explanation:
Reference:
https://cloud.google.com/compute/docs/instance-templates
NEW QUESTION # 122
Case Study: 5 - Dress4win
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. The application has grown from a few servers in the founder's garage to several hundred servers and appliances in a collocated 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 moving their development and test environments. They are also 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. All servers run Ubuntu LTS v16.04.
Databases:
MySQL. 1 server for user data, inventory, static data:
- MySQL 5.8
- 8 core CPUs
- 128 GB of RAM
- 2x 5 TB HDD (RAID 1)
Redis 3 server cluster for metadata, social graph, caching. Each server is:
- Redis 3.2
- 4 core CPUs
- 32GB of RAM
Compute:
40 Web Application servers providing micro-services based APIs and static content.
- Tomcat - Java
- Nginx
- 4 core CPUs
- 32 GB of RAM
20 Apache Hadoop/Spark servers:
- Data analysis
- Real-time trending calculations
- 8 core CPUS
- 128 GB of RAM
- 4x 5 TB HDD (RAID 1)
3 RabbitMQ servers for messaging, social notifications, and events:
- 8 core CPUs
- 32GB of RAM
Miscellaneous servers:
- Jenkins, monitoring, bastion hosts, security scanners
- 8 core CPUs
- 32GB of RAM
Storage appliances:
iSCSI for VM hosts
Fiber channel SAN - MySQL databases
- 1 PB total storage; 400 TB available
NAS - image storage, logs, backups
- 100 TB total storage; 35 TB available
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.
Technical Requirements
Easily create non-production environment in the cloud.
Implement an automation framework for provisioning resources in cloud.
Implement a continuous deployment process for deploying applications to the on-premises
datacenter or cloud.
Support failover of the production environment to cloud during an emergency.
Encrypt data on the wire and at rest.
Support multiple private connections between the production data center and cloud
environment.
Executive Statement
Our investors are concerned about our ability to scale and contain costs with our current infrastructure. They are also concerned that a competitor could use a public cloud platform to offset their up-front investment and free them to focus on developing better features. Our traffic patterns are highest in the mornings and weekend evenings; during other times, 80% of our capacity is sitting idle.
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 for a public cloud strategy achieves a cost reduction between 30% and 50% over our current model.
For this question, refer to the Dress4Win case study. To be legally compliant during an audit, Dress4Win must be able to give insights in all administrative actions that modify the configuration or metadata of resources on Google Cloud.
What should you do?
- A. Use Stackdriver Monitoring to create a dashboard on the project's activity.
- B. Use Stackdriver Trace to create a trace list analysis.
- C. Use the Activity page in the GCP Console and Stackdriver Logging to provide the required insight.
- D. Enable Cloud Identity-Aware Proxy in all projects, and add the group of Administrators as a member.
Answer: C
NEW QUESTION # 123
Your company has just acquired another company, and you have been asked to integrate their existing Google Cloud environment into your company's data center. Upon investigation, you discover that some of the RFC
1918 IP ranges being used in the new company's Virtual Private Cloud (VPC) overlap with your data center IP space. What should you do to enable connectivity and make sure that there are no routing conflicts when connectivity is established?
- A. Create a Cloud VPN connection from the new VPC to the data center, create a Cloud Router, and apply new IP addresses so there is no overlapping IP space.
- B. Create a Cloud VPN connection from the new VPC to the data center, and create a Cloud NAT instance to perform NAT on the overlapping IP space.
- C. Create a Cloud VPN connection from the new VPC to the data center, create a Cloud Router, and apply a custom route advertisement to block the overlapping IP space.
- D. Create a Cloud VPN connection from the new VPC to the data center, and apply a firewall rule that blocks the overlapping IP space.
Answer: A
Explanation:
Explanation
To connect two networks together we need (1) either VPN or interconnect and (2) peering. When there is peering, you cannot have conflicting IP addresses. You can use either Cloud VPN or Cloud Interconnect to securely connect your on-premises network to your VPC network.
(https://cloud.google.com/vpc/docs/vpc-peering#transit-network) At the time of peering, Google Cloud checks to see if there are any subnet IP ranges that overlap subnet IP ranges in the other network. If there is any overlap, peering is not established. (https://cloud.google.com/vpc/docs/vpc-peering#considerations) NAT is used to translate private to public IP and vice versa, however because we are connecting 2 networks together, they become private IPs. So it is not applicable.
NEW QUESTION # 124
Your agricultural division is experimenting with fully autonomous vehicles. You want your architecture to
promote strong security during vehicle operation.
Which two architectures should you consider? (Choose two.)
- A. Use multiple connectivity subsystems for redundancy.
- B. Enclose the vehicle's drive electronics in a Faraday cage to isolate chips.
- C. Require IPv6 for connectivity to ensure a secure address space.
- D. Use a functional programming language to isolate code execution cycles.
- E. Treat every micro service call between modules on the vehicle as untrusted.
- F. Use a trusted platform module (TPM) and verify firmware and binaries on boot.
Answer: B,F
NEW QUESTION # 125
You are working at an institution that processes medical dat
a. You are migrating several workloads onto Google Cloud. Company policies require all workloads to run on physically separated hardware, and workloads from different clients must also be separated You created a sole-tenant node group and added a node for each client. You need to deploy the workloads on these dedicated hosts. What should you do?
- A. Use node affinity labels based on the node group name when creating Compute Engine instances in order to host each workload on the correct node group
- B. Add the node name as a network tag when creating Compute Engine instances in order to host each workload on the correct node.
- C. Use node affinity labels based on the node name when creating Compute Engine instances in order to host each workload on the correct node.
- D. Add the node group name as a network tag when creating Compute Engine instances in order to host each workload on the correct node group.
Answer: A
Explanation:
https://cloud.google.com/compute/docs/nodes/provisioning-sole-tenant-vms#provision_a_sole-tenant_vm
https://cloud.google.com/compute/docs/nodes/provisioning-sole-tenant-vms#gcloud_2 When you create a VM, you request sole-tenancy by specifying node affinity or anti-affinity, referencing one or more node affinity labels. You specify custom node affinity labels when you create a node template, and Compute Engine automatically includes some default affinity labels on each node. By specifying affinity when you create a VM, you can schedule VMs together on a specific node or nodes in a node group. By specifying anti-affinity when you create a VM, you can ensure that certain VMs are not scheduled together on the same node or nodes in a node group.
NEW QUESTION # 126
Your company is forecasting a sharp increase in the number and size of Apache Spark and Hadoop jobs being run on your local datacenter You want to utilize the cloud to help you scale this upcoming demand with the least amount of operations work and code change. Which product should you use?
- A. Google Compute Engine
- B. Google Cloud Dataproc
- C. Google Cloud Dataflow
- D. Google Container Engine
Answer: B
Explanation:
Google Cloud Dataproc is a fast, easy-to-use, low-cost and fully managed service that lets you run the Apache Spark and Apache Hadoop ecosystem on Google Cloud Platform. Cloud Dataproc provisions big or small clusters rapidly, supports many popular job types, and is integrated with other Google Cloud Platform services, such as Google Cloud Storage and Stackdriver Logging, thus helping you reduce TCO.
References: https://cloud.google.com/dataproc/docs/resources/faq
NEW QUESTION # 127
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 self-contained applications with external dependencies as a first move to the cloud.
- D. Identify enterprise applications with internal dependencies and recommend these as a first move to the cloud.
Answer: C
Explanation:
Explanation
https://cloud.google.com/blog/products/gcp/the-five-phases-of-migrating-to-google-cloud-platform
NEW QUESTION # 128
Your development teams release new versions of games running on Google Kubernetes Engine (GKE) daily.
You want to create service level indicators (SLIs) to evaluate the quality of the new versions from the user's perspective. What should you do?
- A. Create GKE CPU Utilization and Memory Utilization as service level indicators.
- B. Create Server Uptime and Error Rate as service level indicators.
- C. Create CPU Utilization and Request Latency as service level indicators.
- D. Create Request Latency and Error Rate as service level indicators.
Answer: C
Explanation:
Topic 7, 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.
Reference:
A real time requires Stream / Messaging so Pub/Sub, Analytics by Big Query.
NEW QUESTION # 129
For this question, refer to the Helicopter Racing League (HRL) case study. Recently HRL started a new regional racing league in Cape Town, South Africa. In an effort to give customers in Cape Town a better user experience, HRL has partnered with the Content Delivery Network provider, Fastly. HRL needs to allow traffic coming from all of the Fastly IP address ranges into their Virtual Private Cloud network (VPC network). You are a member of the HRL security team and you need to configure the update that will allow only the Fastly IP address ranges through the External HTTP(S) load balancer. Which command should you use?
- A. gcloud compute security policies rules update 1000 \
--security-policy hlr-policy \
--expression "evaluatePreconfiguredExpr('sourceiplist-fastly')" \
--action " allow" - B. gcloud compute firewall rules update
sourceiplist-fastly \
priority 1000 \
allow tcp: 443 - C. glouc compute firewall rules update hlr-policy \
--priority 1000 \
target tags-sourceiplist fastly \
--allow tcp:443 - D. gcloud compute priority-policies rules update
1000 \
security policy from fastly
--src- ip-ranges"
-- action " allow"
Answer: A
Explanation:
Reference: https://cloud.google.com/load-balancing/docs/https
D18912E1457D5D1DDCBD40AB3BF70D5D
NEW QUESTION # 130
Dress4Win has configured a new uptime check with Google Stackdriver for several of their legacy
services. The Stackdriver dashboard is not reporting the services as healthy.
What should they do?
- A. Configure their legacy web servers to allow requests that contain user-Agent HTTP header when the
value matches GoogleStackdriverMonitoring-UptimeChecks (https://cloud.google.com/monitoring) - B. Install the Stackdriver agent on all of the legacy web servers.
- C. In the Cloud Platform Console download the list of the uptime servers' IP addresses and create an
inbound firewall rule - D. Configure their load balancer to pass through the User-Agent HTTP header when the value matches
GoogleStackdriverMonitoring-UptimeChecks (https://cloud.google.com/monitoring)
Answer: A
NEW QUESTION # 131
Your solution is producing performance bugs in production that you did not see in staging and test environments. You want to adjust your test and deployment procedures to avoid this problem in the future.
What should you do?
- A. Deploy fewer changes to production
- B. Deploy smaller changes to production
- C. Deploy changes to a small subset of users before rolling out to production
- D. Increase the load on your test and staging environments
Answer: C
Explanation:
Explanation
NEW QUESTION # 132
Dress4Win has configured a new uptime check with Google Stackdriver for several of their legacy services.
The Stackdriver dashboard is not reporting the services as healthy.
What should they do?
- A. Configure their load balancer to pass through the User-Agent HTTP header when the value matches GoogleStackdriverMonitoring-UptimeChecks (https://cloud.google.com/monitoring)
- B. In the Cloud Platform Console download the list of the uptime servers' IP addresses and create an inbound firewall rule
- C. Install the Stackdriver agent on all of the legacy web servers.
- D. Configure their legacy web servers to allow requests that contain user-Agent HTTP header when the value matches GoogleStackdriverMonitoring-UptimeChecks (https://cloud.google.com/monitoring)
Answer: D
NEW QUESTION # 133
For this question, refer to the Mountkirk Games case study.
Mountkirk Games' gaming servers are not automatically scaling properly. Last month, they rolled out a new feature, which suddenly became very popular. A record number of users are trying to use the service, but many of them are getting 503 errors and very slow response times. What should they investigate first?
- A. Verify that the load-testing team is not running their tool against production.
- B. Verify that the project quota hasn't been exceeded.
- C. Verify that the database is online.
- D. Verify that the new feature code did not introduce any performance bugs.
Answer: B
Explanation:
Explanation
503 is service unavailable error. If the database was online everyone would get the 503 error.
https://cloud.google.com/docs/quota#capping_usage
NEW QUESTION # 134
......
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