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Google Certified Professional - Cloud Architect (GCP) Sample Questions (Q263-Q268):

NEW QUESTION # 263
One of the developers on your team deployed their application In Google Container Engine with the Dockerfile below. They report that their application deployments are taking too long.

You want to optimize this Dockerfile for faster deployment times without adversely affecting the app's functionality. Which two actions should you take? Choose 2 answers

A. Use a slimmed-down base image like Alpine linux.
B. Remove Python after running pip.
C. Copy the source after the package dependencies (Python and pip) are installed.
D. Remove dependencies from requirements.txt.
E. Use larger machine types for your Google Container Engine node pools.

Answer: A,C

Explanation:
The speed of deployment can be changed by limiting the size of the uploaded app, limiting the complexity of the build necessary in the Dockerfile, if present, and by ensuring a fast and reliable internet connection.
Note: Alpine Linux is built around musl libc and busybox. This makes it smaller and more resource efficient than traditional GNU/Linux distributions. A container requires no more than 8 MB and a minimal installation to disk requires around 130 MB of storage. Not only do you get a fully-fledged Linux environment but a large selection of packages from the repository.
References: https://groups.google.com/forum/#!topic/google-appengine/hZMEkmmObDU
https://www.alpinelinux.org/about/

NEW QUESTION # 264
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 Bigtable
B. Google Cloud SQL
C. Google BigQuery
D. Google Cloud Storage

Answer: A

Explanation:
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

References: https://cloud.google.com/storage-options/

NEW QUESTION # 265
Your team will start developing a new application using microservices architecture on Kubernetes Engine. As part of the development lifecycle, any code change that has been pushed to the remote develop branch on your GitHub repository should be built and tested automatically. When the build and test are successful, the relevant microservice will be deployed automatically in the development environment. You want to ensure that all code deployed in the development environment follows this process. What should you do?

A. Create a Cloud Build trigger based on the development branch that tests the code, builds the container, and stores it in Container Registry. Create a deployment pipeline that watches for new images and deploys the new image on the development cluster. Ensure only the deployment tool has access to deploy new versions.
B. Have each developer install a pre-commit hook on their workstation that tests the code and builds the container when committing on the development branch. After a successful commit, have the developer deploy the newly built container image on the development cluster.
C. Create a Cloud Build trigger based on the development branch to build a new container image and store it in Container Registry. Rely on Vulnerability Scanning to ensure the code tests succeed. As the final step of the Cloud Build process, deploy the new container image on the development cluster. Ensure only Cloud Build has access to deploy new versions.
D. Install a post-commit hook on the remote git repository that tests the code and builds the container when code is pushed to the development branch. After a successful commit, have the developer deploy the newly built container image on the development cluster.

Answer: B

NEW QUESTION # 266
For this question, refer to the Mountkirk Games case study. You are in charge of the new Game Backend
Platform architecture. The game communicates with the backend over a REST API.
You want to follow Google-recommended practices. How should you design the backend?

A. Create an instance template for the backend. For every region, deploy it on a multi-zone managed
instance group. Use an L7 load balancer.
B. Create an instance template for the backend. For every region, deploy it on a multi-zone managed
instance group. Use an L4 load balancer.
C. Create an instance template for the backend. For every region, deploy it on a single-zone managed
instance group. Use an L7 load balancer.
D. Create an instance template for the backend. For every region, deploy it on a single-zone managed
instance group. Use an L4 load balancer.

Answer: B

Explanation:
Explanation/Reference:
Testlet 1
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 was 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, Terram Earth 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 to 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 lower 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 # 267
You are developing your microservices application on Google Kubernetes Engine. During testing, you want to validate the behavior of your application in case a specific microservice should suddenly crash. What should you do?

A. Add a taint to one of the nodes of the Kubernetes cluster. For the specific microservice, configure a pod anti-affinity label that has the name of the tainted node as a value.
B. Destroy one of the nodes of the Kubernetes cluster to observe the behavior.
C. Configure Istio's traffic management features to steer the traffic away from a crashing microservice.
D. Use Istio's fault injection on the particular microservice whose faulty behavior you want to simulate.

Answer: B

NEW QUESTION # 268
......

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Professional-Cloud-Architect practice materials & Professional-Cloud-Architect guide torrent: Google Certified Professional - Cloud Architect (GCP) & Professional-Cloud-Architect study guide

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Google Certified Professional - Cloud Architect (GCP) Sample Questions (Q263-Q268):

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