Professional-Cloud-Architect Pre-Exam Practice Tests | (Updated 230 Questions) Valid Professional-Cloud-Architect Exam Q A PDF - One Year Free Update NEW QUESTION 127 For this question, refer to the TerramEarth case study.The TerramEarth development team wants to create an API to meet the company's business requirements. You want the development team to focus their development effort on business value [...]

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Professional-Cloud-Architect Pre-Exam Practice Tests (Updated 230 Questions) [Q127-Q147]

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Professional-Cloud-Architect Pre-Exam Practice Tests | (Updated 230 Questions)

Valid Professional-Cloud-Architect Exam Q&A PDF - One Year Free Update

NEW QUESTION 127
For this question, refer to the TerramEarth case study.
The TerramEarth development team wants to create an API to meet the company's business requirements. You want the development team to focus their development effort on business value versus creating a custom framework. Which method should they use?

  • A. Use Google App Engine with Google Cloud Endpoints. Focus on an API for dealers and partners.
  • B. Use Google App Engine with a JAX-RS Jersey Java-based framework. Focus on an API for the public.
  • C. Use Google App Engine with the Swagger (open API Specification) framework. Focus on an API for the public.
  • D. Use Google Container Engine with a Django Python container. Focus on an API for the public.
  • E. Use Google Container Engine with a Tomcat container with the Swagger (Open API Specification) framework. Focus on an API for dealers and partners.

Answer: A

Explanation:
Explanation
https://cloud.google.com/endpoints/docs/openapi/about-cloud-endpoints?hl=en_US&_ga=2.21787131.-1712523
https://cloud.google.com/endpoints/docs/openapi/architecture-overview
https://cloud.google.com/storage/docs/gsutil/commands/test
Develop, deploy, protect and monitor your APIs with Google Cloud Endpoints. Using an Open API Specification or one of our API frameworks, Cloud Endpoints gives you the tools you need for every phase of API development.
From scenario:
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.
Reference: https://cloud.google.com/certification/guides/cloud-architect/casestudy-terramearth
Topic 2, Mountkirk Games Case Study
Company Overview
Mountkirk Games makes online, session-based. multiplayer games for the most popular mobile platforms.
Company Background
Mountkirk Games builds all of their games with some server-side integration and has historically used cloud providers to lease physical servers. A few of their games were more popular than expected, and they had problems scaling their application servers, MySQL databases, and analytics tools.
Mountkirk's 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.
Technical Requirements
Requirements for Game Backend Platform
1. Dynamically scale up or down based on game activity.
2. Connect to a managed NoSQL database service.
3. Run customized Linx distro.
Requirements for Game Analytics Platform
1. Dynamically scale up or down based on game activity.
2. Process incoming data on the fly directly from the game servers.
3. Process data that arrives late because of slow mobile networks.
4. Allow SQL queries to access at least 10 TB of historical data.
5. Process files that are regularly uploaded by users' mobile devices.
6. Use only fully managed services
CEO Statement
Our last successful game did not scale well with our previous cloud provider, resuming 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 gams to target users.
CTO Statement
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.
CFO Statement
We are not capturing enough user demographic data usage metrics, and other KPIs. As a result, we do not engage the right users. We are not confident that our marketing is targeting the right users, and we are not selling enough premium Blast-Ups inside the games, which dramatically impacts our revenue.

 

NEW QUESTION 128
You are running a cluster on Kubernetes Engine (GKE) to serve a web application. Users are reporting that a specific part of the application is not responding anymore. You notice that all pods of your deployment keep restarting after 2 seconds. The application writes logs to standard output. You want to inspect the logs to find the cause of the issue. Which approach can you take?

  • A. Connect to the cluster using gcloud credentials and connect to a container in one of the pods to read the logs.
  • B. Review the Serial Port logs for each Compute Engine instance that is serving as a node in the cluster.
  • C. Review the Stackdriver logs for each Compute Engine instance that is serving as a node in the cluster.
  • D. Review the Stackdriver logs for the specific GKE container that is serving the unresponsive part of the application.

Answer: D

 

NEW QUESTION 129
JencoMart wants to move their User Profiles database to Google Cloud Platform.
Which Google Database should they use?

  • A. Google Cloud SQL
  • B. Google Cloud Datastore
  • C. Google BigQuery
  • D. Cloud Spanner

Answer: B

Explanation:
Explanation/Reference:
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
Testlet 1
Company Overview
Mountkirk Games makes online, session-based, multiplayer games for the most popular 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 clous resources we use

Reduce lateny to all customers

Technical Requirements
Requirements for Game Backend Platform
1. Dynamically scale up or down based on game activity
2. Connect to a managed NoSQL database service
3. Run customize Linux distro
Requirements for Game Analytics Platform
1. Dynamically scale up or down based on game activity
2. Process incoming data on the fly directly from the game servers
3. Process data that arrives late because of slow mobile networks
4. Allow SQL queries to access at least 10 TB of historical data
5. Process files that are regularly uploaded by users' mobile devices
6. Use only fully managed services
CEO 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.
CTO Statement
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.
CFO Statement
We are not capturing enough user demographic data, usage metrics, and other KPIs. As a result, we do
not engage the right users, we are not confident that our marketing is targeting the right users, and we are
not selling enough premium Blast-Ups inside the games, which dramatically impacts our revenue.

 

NEW QUESTION 130
Your company has successfully migrated to the cloud and wants to analyze their data stream to optimize operations. They do not have any existing code for this analysis, so they are exploring all their options. These options include a mix of batch and stream processing, as they are running some hourly jobs and live-processing some data as it comes in. Which technology should they use for this?

  • A. Google Compute Engine with Google BigQuery
  • B. Google Container Engine with Bigtable
  • C. Google Cloud Dataproc
  • D. Google Cloud Dataflow

Answer: D

Explanation:
Cloud Dataflow is a fully-managed service for transforming and enriching data in stream (real time) and batch (historical) modes with equal reliability and expressiveness -- no more complex workarounds or compromises needed.
References: https://cloud.google.com/dataflow/

 

NEW QUESTION 131
You want to establish a Compute Engine application in a single VPC across two regions. The application must communicate over VPN to an on-premises network. How should you deploy the VPN?

  • A. Use VPC Network Peering between the VPC and the on-premises network.
  • B. Create a global Cloud VPN Gateway with VPN tunnels from each region to the on-premises peer gateway.
  • C. Deploy Cloud VPN Gateway in each region. Ensure that each region has at least one VPN tunnel to the onpremises peer gateway.
  • D. Expose the VPC to the on-premises network using IAM and VPC Sharing.

Answer: B

 

NEW QUESTION 132
You need to deploy an application on Google Cloud that must run on a Debian Linux environment. The application requires extensive configuration in order to operate correctly. You want to ensure that you can install Debian distribution updates with minimal manual intervention whenever they become available. What should you do?

  • A. Create a Debian-based Compute Engine instance, install and configure the application, and use OS patch management to install available updates.
  • B. Create an instance with the latest available Debian image. Connect to the instance via SSH, and install and configure the application on the instance. Repeat this process whenever a new Google-managed Debian image becomes available.
  • C. Create a Compute Engine instance template using the most recent Debian image. Create an instance from this template, and install and configure the application as part of the startup script. Repeat this process whenever a new Google-managed Debian image becomes available.
  • D. Create a Docker container with Debian as the base image. Install and configure the application as part of the Docker image creation process. Host the container on Google Kubernetes Engine and restart the container whenever a new update is available.

Answer: A

 

NEW QUESTION 133
As part of implementing their disaster recovery plan, your company is trying to replicate their production MySQL database from their private data center to their GCP project using a Google Cloud VPN connection.
They are experiencing latency issues and a small amount of packet loss that is disrupting the replication. What should they do?

  • A. Send the replicated transaction to Google Cloud Pub/Sub.
  • B. Configure a Google Cloud Dedicated Interconnect.
  • C. Configure their replication to use UDP.
  • D. Add additional VPN connections and load balance them.
  • E. Restore their database daily using Google Cloud SQL.

Answer: B

 

NEW QUESTION 134
You are using Cloud Shell and need to install a custom utility for use in a few weeks. Where can you store the file so it is in the default execution path and persists across sessions?

  • A. ~/bin
  • B. Cloud Storage
  • C. /usr/local/bin
  • D. /google/scripts

Answer: A

 

NEW QUESTION 135
Your company has decided to build a backup replica of their on-premises user authentication PostgreSQL database on Google Cloud Platform. The database is 4 TB, and large updates are frequent. Replication requires private address space communication.
Which networking approach should you use?

  • A. A NAT and TLS translation gateway installed on-premises
  • B. Google Cloud Dedicated Interconnect
  • C. Google Cloud VPN connected to the data center network
  • D. A Google Compute Engine instance with a VPN server installed connected to the data center network

Answer: C

 

NEW QUESTION 136
You are building a continuous deployment pipeline for a project stored in a Git source repository and want to ensure that code changes can be verified deploying to production. What should you do?

  • A. Use Jenkins to build the staging branches and the master branch. Build and deploy changes to production for 10% of users before doing a complete rollout.
  • B. Use Jenkins to monitor tags in the repository. Deploy staging tags to a staging environment for testing.
    After testing, tag the repository for production and deploy that to the production environment.
  • C. Use Spinnaker to deploy builds to production and run tests on production deployments.
  • D. Use Spinnaker to deploy builds to production using the red/black deployment strategy so that changes can easily be rolled back.

Answer: B

Explanation:
Automation Jenkins can monitor Git repo

 

NEW QUESTION 137
For this question, refer to the TerramEarth case study.
TerramEarth's 20 million vehicles are scattered around the world. Based on the vehicle's location its telemetry data is stored in a Google Cloud Storage (GCS) regional bucket (US.
Europe, or Asia). The CTO has asked you to run a report on the raw telemetry data to determine why vehicles are breaking down after 100 K miles. You want to run this job on all the data. What is the most cost-effective way to run this job?

  • A. Move all the data into 1 zone, then launch a Cloud Dataproc cluster to run the job.
  • B. Launch a cluster in each region to preprocess and compress the raw data, then move the data into a regional bucket and use a Cloud Dataproc cluster .....
  • C. Launch a cluster in each region to preprocess and compress the raw data, then move the data into a multi region bucket and use a Dataproc cluster to finish the job.
  • D. Move all the data into 1 region, then launch a Google Cloud Dataproc cluster to run the job.

Answer: B

 

NEW QUESTION 138
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. Help the engineer to convert his websocket code to use HTTP streaming.
  • C. Meet with the cloud operations team and the engineer to discuss load balancer options.
  • D. Review the encryption requirements for websocket connections with the security team.

Answer: C

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.
Incorrect Answers:
A: HTTP server push, also known as HTTP streaming, is a client-server communication pattern that sends information from an HTTP server to a client asynchronously, without a client request. A server push architecture is especially effective for highly interactive web or mobile applications, where one or more clients need to receive continuous information from the server.
References:
https://cloud.google.com/compute/docs/load-balancing/http/

 

NEW QUESTION 139
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 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 single-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 multi-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: C

 

NEW QUESTION 140
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:
https://cloud.google.com/compute/docs/instance-groups/

 

NEW QUESTION 141
The application reliability team at your company has added a debug feature to their backend service to send all server events to Google Cloud Storage for eventual analysis.
The event records are at least 50 KB and at most 15 MB and are expected to peak at 3,000 events per second. You want to minimize data loss.
Which process should you implement?

  • A. * Append metadata to file body.
    * Compress individual files.
    * Name files with serverName-Timestamp.
    * Create a new bucket if bucket is older than 1 hour and save individual files to the new bucket. Otherwise, save files to existing bucket
  • B. * Compress individual files.
    * Name files with serverName-EventSequence.
    * Save files to one bucket
    * Set custom metadata headers for each object after saving.
  • C. * Batch every 10,000 events with a single manifest file for metadata.
    * Compress event files and manifest file into a single archive file.
    * Name files using serverName-EventSequence.
    * Create a new bucket if bucket is older than 1 day and save the single archive file to the new bucket. Otherwise, save the single archive file to existing bucket.
  • D. * Append metadata to file body.
    * Compress individual files.
    * Name files with a random prefix pattern.
    * Save files to one bucket

Answer: A

 

NEW QUESTION 142
Case Study: 2 - 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.
For this question, refer to the TerramEarth case study. The TerramEarth development team wants to create an API to meet the company's business requirements. You want the development team to focus their development effort on business value versus creating a custom framework.
Which method should they use?

  • A. Use Google App Engine with Google Cloud Endpoints. Focus on an API for dealers and partners.
  • B. Use Google App Engine with a JAX-RS Jersey Java-based framework. Focus on an API for the public.
  • C. Use Google App Engine with the Swagger (open API Specification) framework. Focus on an API for the public.
  • D. Use Google Container Engine with a Django Python container. Focus on an API for the public.
  • E. Use Google Container Engine with a Tomcat container with the Swagger (Open API Specification) framework. Focus on an API for dealers and partners.

Answer: A

Explanation:
Develop, deploy, protect and monitor your APIs with Google Cloud Endpoints. Using an Open API Specification or one of our API frameworks, Cloud Endpoints gives you the tools you need for every phase of API development.
From scenario:
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.
Reference: https://cloud.google.com/certification/guides/cloud-architect/casestudy-terramearth

 

NEW QUESTION 143
Your customer is receiving reports that their recently updated Google App Engine application is taking approximately 30 seconds to load for some of their users. This behavior was not reported before the update.
What strategy should you take?

  • A. Roll back to an earlier known good release initially, then use Stackdriver Trace and Logging to diagnose the problem in a development/test/staging environment
  • B. Work with your ISP to diagnose the problem
  • C. Open a support ticket to ask for network capture and flow data to diagnose the problem, then roll back your application
  • D. Roll back to an earlier known good release, then push the release again at a quieter period to investigate.
    Then use Stackdriver Trace and Logging to diagnose the problem

Answer: A

Explanation:
Stackdriver Logging allows you to store, search, analyze, monitor, and alert on log data and events from Google Cloud Platform and Amazon Web Services (AWS). Our API also allows ingestion of any custom log data from any source. Stackdriver Logging is a fully managed service that performs at scale and can ingest application and system log data from thousands of VMs. Even better, you can analyze all that log data in real time.
Reference: https://cloud.google.com/logging/

 

NEW QUESTION 144
The application reliability team at your company has added a debug feature to their backend service to send all server events to Google Cloud Storage for eventual analysis. The event records are at least 50 KB and at most 15 MB and are expected to peak at 3,000 events per second. You want to minimize data loss.
Which process should you implement?

  • A. Compress individual files.
    Name files with serverName-EventSequence.
    Save files to one bucket
    Set custom metadata headers for each object after saving.
  • B. Batch every 10,000 events with a single manifest file for metadata.
    Compress event files and manifest file into a single archive file.
    Name files using serverName-EventSequence.
    Create a new bucket if bucket is older than 1 day and save the single archive file to the new bucket. Otherwise, save the single archive file to existing bucket.
  • C. Append metadata to file body.
    Compress individual files.
    Name files with serverName-Timestamp.
    Create a new bucket if bucket is older than 1 hour and save individual files to the new bucket.
    Otherwise, save files to existing bucket
  • D. Append metadata to file body.
    Compress individual files.
    Name files with a random prefix pattern.
    Save files to one bucket

Answer: B

 

NEW QUESTION 145
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 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.
  • B. Perform the following:
    1. Create a Kubernetes Engine 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.
  • C. 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.
  • D. 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 version number.
    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.

Answer: C

 

NEW QUESTION 146
A news feed web service has the following code running on Google App Engine. During peak load, users report that they can see news articles they already viewed.
What is the most likely cause of this problem?

  • A. The URL of the API needs to be modified to prevent caching
  • B. The session variable is local to just a single instance
  • C. The session variable is being overwritten in Cloud Datastore
  • D. The HTTP Expires header needs to be set to -1 stop caching

Answer: C

Explanation:
Explanation/Reference:
Reference: https://stackoverflow.com/questions/3164280/google-app-engine-cache-list-in-session- variable?rq=1

 

NEW QUESTION 147
......

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