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Exam Target Audience
The specialists with this sought-after Google Professional Cloud Architect certificate have an in-depth understanding of Cloud architecture & Google Cloud Platform that enables them to create, develop, and operate highly available, secure, robust, scalable, and highly dynamic solutions in compliance with the business objectives of the organizations. With some relevant experience in the industry as well as familiarity with the products within the Google Cloud sphere, it is easier to comprehend the required test domains.
NEW QUESTION 41
During a high traffic portion of the day, one of your relational databases crashes, but the replica is never promoted to a master. You want to avoid this in the future. What should you do?
- A. Create snapshots of your database more regularly.
- B. Choose larger instances for your database.
- C. Implement routinely scheduled failovers of your databases.
- D. Use a different database.
Answer: C
Explanation:
https://cloud.google.com/solutions/dr-scenarios-planning-guide
NEW QUESTION 42
Case Study: 6 - TerramEarth
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.
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 and Windows-based systems that reside in a single U.S. west coast based data center. These systems gzip CSV files from the field and upload via FTP, 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.
* 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.
Technical Requirements
Expand beyond a single datacenter to decrease latency to the American Midwest and east
* coast.
Create a backup strategy.
* Increase security of data transfer from equipment to the datacenter.
* Improve data in the data warehouse.
* Use customer and equipment data to anticipate customer needs.
* Application 1: Data ingest
A custom Python application reads uploaded datafiles from a single server, writes to the data warehouse.
Compute:
Windows Server 2008 R2
* - 16 CPUs
- 128 GB of RAM
- 10 TB local HDD storage
Application 2: Reporting
An off the shelf application that business analysts use to run a daily report to see what equipment needs repair. Only 2 analysts of a team of 10 (5 west coast, 5 east coast) can connect to the reporting application at a time.
Compute:
Off the shelf application. License tied to number of physical CPUs
* - Windows Server 2008 R2
- 16 CPUs
- 32 GB of RAM
- 500 GB HDD
Data warehouse:
A single PostgreSQL server
* - RedHat Linux
- 64 CPUs
- 128 GB of RAM
- 4x 6TB HDD in RAID 0
Executive 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. My goals are to build our skills while addressing immediate market needs through incremental innovations.
For this question, refer to the TerramEarth case study. You are asked to design a new architecture for the ingestion of the data of the 200,000 vehicles that are connected to a cellular network. You want to follow Google-recommended practices.
Considering the technical requirements, which components should you use for the ingestion of the data?
- A. Compute Engine with project-wide SSH keys
- B. Compute Engine with specific SSH keys
- C. Google Kubernetes Engine with an SSL Ingress
- D. Cloud IoT Core with public/private key pairs
Answer: C
NEW QUESTION 43
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
RAID 1)
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.
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 tier of Google Cloud Storage that is not suited for this task
- B. Complicated internet connectivity between the on-premises infrastructure and GCP
- C. A copy command that is not suited to operate over long distances
- D. A separate storage layer outside the VMs, which is not suited for this task
- E. Fewer virtual machines (VMs) in GCP than on-premises machines
- F. A single VPN tunnel, which limits throughput
Answer: C,D,F
NEW QUESTION 44
You need to ensure reliability for your application and operations by supporting reliable task a scheduling for compute on GCP. Leveraging Google best practices, what should you do?
- A. Using the Cron service provided by GKE, publish messages to a Cloud Pub/Sub topic. Subscribe to that topic using a message-processing utility service running on Compute Engine instances.
- B. Using the Cron service provided by App Engine, publish messages to a Cloud Pub/Sub topic.
Subscribe to that topic using a message-processing utility service running on Compute Engine instances. - C. Using the Cron service provided by Google Kubernetes Engine (GKE), publish messages directly to a message-processing utility service running on Compute Engine instances.
- D. Using the Cron service provided by App Engine, publishing messages directly to a message- processing utility service running on Compute Engine instances.
Answer: B
NEW QUESTION 45
Your web application must comply with the requirements of the European Union's General Data Protection Regulation (GDPR). You are responsible for the technical architecture of your web application. What should you do?
- A. Define a design for the security of data in your web application that meets GDPR requirements.
- B. Ensure that Cloud Security Scanner is part of your test planning strategy in order to pick up any compliance gaps.
- C. Enable the relevant GDPR compliance setting within the GCPConsole for each of the services in use within your application.
- D. Ensure that your web application only uses native features and services of Google Cloud Platform, because Google already has various certifications and provides "pass-on" compliance when you use native features.
Answer: A
NEW QUESTION 46
You write a Python script to connect to Google BigQuery from a Google Compute Engine virtual machine.
The script is printing errors that it cannot connect to BigQuery. What should you do to fix the script?
- A. Install the bq component for gccloud with the command gcloud components install bq.
- B. Install the latest BigQuery API client library for Python
- C. Create a new service account with BigQuery access and execute your script with that user
- D. Run your script on a new virtual machine with the BigQuery access scope enabled
Answer: D
Explanation:
Explanation
The error is most like caused by the access scope issue. When create new instance, you have the default Compute engine default service account but most serves access including BigQuery is not enable. Create an instance Most access are not enabled by default You have default service account but don't have the permission (scope) you can stop the instance, edit, change scope and restart it to enable the scope access. Of course, if you Run your script on a new virtual machine with the BigQuery access scope enabled, it also works
https://cloud.google.com/compute/docs/access/service-accounts
NEW QUESTION 47
Your customer is moving an existing corporate application to Google Cloud Platform from an on-premises data center. The business owners require minimal user disruption. There are strict security team requirements for storing passwords. What authentication strategy should they use?
- A. Provision users in Google using the Google Cloud Directory Sync tool.
- B. Use G Suite Password Sync to replicate passwords into Google.
- C. Ask users to set their Google password to match their corporate password.
- D. Federate authentication via SAML 2.0 to the existing Identity Provider.
Answer: B
Explanation:
https://support.google.com/a/answer/2611859?hl=en
NEW QUESTION 48
Your customer is moving an existing corporate application to Google Cloud Platform from an on-premises data center. The business owners require minimal user disruption. There are strict security team requirements for storing passwords. What authentication strategy should they use?
- A. Provision users in Google using the Google Cloud Directory Sync tool.
- B. Use G Suite Password Sync to replicate passwords into Google.
- C. Ask users to set their Google password to match their corporate password.
- D. Federate authentication via SAML 2.0 to the existing Identity Provider.
Answer: D
Explanation:
https://cloud.google.com/solutions/authenticating-corporate-users-in-a-hybrid-environment
NEW QUESTION 49
Your organization requires that metrics from all applications be retained for 5 years for future analysis in possible legal proceedings.
Which approach should you use?
- A. Configure Stackdriver Monitoring for all Projects, and export to BigQuery
- B. Configure Stackdriver Monitoring for all Projects, and export to Google Cloud Storage
- C. Configure Stackdriver Monitoring for all Projects with the default retention policies
- D. Grant the security team access to the logs in each Project
Answer: A
Explanation:
Explanation/Reference:
Explanation:
Stackdriver Logging provides you with the ability to filter, search, and view logs from your cloud and open source application services. Allows you to define metrics based on log contents that are incorporated into dashboards and alerts. Enables you to export logs to BigQuery, Google Cloud Storage, and Pub/Sub.
Reference: https://cloud.google.com/stackdriver/
NEW QUESTION 50
The development team has provided you with a Kubernetes Deployment file. You have no infrastructure yet and need to deploy the application. What should you do?
- A. Use gcloud to create a Kubernetes cluster. Use Deployment Manager to create the deployment.
- B. Use kubectl to create a Kubernetes cluster. Use kubectl to create the deployment.
- C. Use gcloud to create a Kubernetes cluster. Use kubectl to create the deployment.
- D. Use kubectl to create a Kubernetes cluster. Use Deployment Manager to create the deployment.
Answer: C
Explanation:
Gcloud to create
Kubectl to do Kubernete
NEW QUESTION 51
Your company wants to track whether someone is present in a meeting room reserved for a scheduled meeting. There are 1000 meeting rooms across 5 offices on 3 continents. Each room is equipped with a motion sensor that reports its status every second. You want to support the data upload and collection needs of this sensor network. The receiving infrastructure needs to account for the possibility that the devices may have inconsistent connectivity. Which solution should you design?
- A. Have devices poll for connectivity to Cloud Pub/Sub and publish the latest messages on a regular interval to a shared topic for all devices.
- B. Have each device create a persistent connection to a Compute Engine instance and write messages to a custom application.
- C. Have devices poll for connectivity to Cloud SQL and insert the latest messages on a regular interval to a device specific table.
- D. Have devices create a persistent connection to an App Engine application fronted by Cloud Endpoints, which ingest messages and write them to Cloud Datastore.
Answer: A
Explanation:
A is not correct because having a persistent connection does not handle the case where the device is disconnected.
B is not correct because Cloud SQL is a relational database and not the best fit for sensor data.
Additionally, the frequency of the writes has the potential to exceed the supported number of concurrent connections.
C is correct because Cloud Pub/Sub can handle the frequency of this data, and consumers of the data can pull from the shared topic for further processing.
D is not correct because having a persistent connection does not handle the case where the device is disconnected.
https://cloud.google.com/sql/
https://cloud.google.com/pubsub/
NEW QUESTION 52
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 BigQuery
- D. Google Cloud Bigtable
Answer: D
Explanation:
Explanation
It is time-series data, So Big Table.
https://cloud.google.com/bigtable/docs/schema-design-time-series
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 53
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 BigQuery
- D. Google Cloud Bigtable
Answer: D
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 54
Your applications will be writing their logs to BigQuery for analysis. Each application should have its own table.
Any logs older than 45 days should be removed. You want to optimize storage and follow Google recommended practices. What should you do?
- A. Rely on BigQuery's default behavior to prune application logs older than 45 days
- B. Make the tables time-partitioned, and configure the partition expiration at 45 days
- C. Create a script that uses the BigQuery command line tool (bq) to remove records older than 45 days
- D. Configure the expiration time for your tables at 45 days
Answer: B
Explanation:
https://cloud.google.com/bigquery/docs/managing-partitioned-tables
NEW QUESTION 55
For this question, refer to the TerramEarth case study. You need to implement a reliable, scalable GCP solution for the data warehouse for your company, TerramEarth. Considering the TerramEarth business and technical requirements, what should you do?
- A. Replace the existing data warehouse with BigQuery. Use table partitioning.
- B. Replace the existing data warehouse with a Compute Engine instance with 96 CPUs.
- C. Replace the existing data warehouse with BigQuery. Use federated data sources.
- D. Replace the existing data warehouse with a Compute Engine instance with 96 CPUs. Add an additional Compute Engine pre-emptible instance with 32 CPUs.
Answer: A
Explanation:
Topic 7, Mountkrik Games Case 2
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.
NEW QUESTION 56
For this question, refer to the Dress4Win case study.
As part of Dress4Win's plans to migrate to the cloud, they want to be able to set up a managed logging and monitoring system so they can handle spikes in their traffic load. They want to ensure that:
* The infrastructure can be notified when it needs to scale up and down to handle the ebb and flow of usage throughout the day
* Their administrators are notified automatically when their application reports errors.
* They can filter their aggregated logs down in order to debug one piece of the application across many hosts Which Google StackDriver features should they use?
- A. Monitoring, Trace, Debug, Logging
- B. Monitoring, Logging, Alerts, Error Reporting
- C. Logging, Alerts, Insights, Debug
- D. Monitoring, Logging, Debug, Error Report
Answer: D
NEW QUESTION 57
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. Enable autoscaling on the Compute Engine instance group. Use an Ingress resource to load balance the HTTPS traffic.
- B. 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.
- 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: B
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 58
For this question, refer to the JencoMart case study.
JencoMart has built a version of their application on Google Cloud Platform that serves traffic to Asia. You want to measure success against their business and technical goals. Which metrics should you track?
- A. Total visits, error rates, and latency from Asia
- B. The number of character sets present in the database
- C. Latency difference between US and Asia
- D. Total visits and average latency for users in Asia
- E. Error rates for requests from Asia
Answer: D
NEW QUESTION 59
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 Deployment Manager to automate service provisioning. Use Activity Logs to monitor and debug your tests.
- B. Use gcloud scripts to automate service provisioning. Use Activity Logs monitor and debug your tests.
- C. Use automated scripts to automate service provisioning. Use Activity Logs monitor and debug your tests.
- D. Use Deployment Manager to automate provisioning. Use Stackdriver to monitor and debug your tests.
Answer: D
Explanation:
Explanation
https://cloud.google.com/solutions/dr-scenarios-planning-guide
NEW QUESTION 60
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 larger machine types for your Google Container Engine node pools.
- B. Remove Python after running pip.
- C. Copy the source after the package dependencies (Python and pip) are installed.
- D. Use a slimmed-down base image like Alpine linux.
- E. Remove dependencies from requirements.txt.
Answer: C,D
Explanation:
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 61
For this question, refer to the TerramEarth case study.
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 continue to write data using the existing system (FTP).
- B. Vehicles write data directly to GCS.
- C. Vehicles write data directly to Google Cloud Pub/Sub.
- D. Vehicles stream data directly to Google BigQuery.
Answer: C
Explanation:
Reference:
https://cloud.google.com/solutions/data-lifecycle-cloud-platform
https://cloud.google.com/solutions/designing-connected-vehicle-platform
NEW QUESTION 62
For this question, refer to the Mountkirk Games case study. Which managed storage option meets Mountkirk's technical requirement for storing game activity in a time series database service?
- A. Cloud Spanner
- B. Cloud Bigtable
- C. Cloud Datastore
- D. BigQuery
Answer: B
Explanation:
Explanation/Reference:
TerramEarth, A
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 63
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 Spinnaker to deploy builds to production using the red/black deployment strategy so that changes can easily be rolled back.
- B. 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.
- C. Use Spinnaker to deploy builds to production and run tests on production deployments.
- D. 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.
Answer: D
Explanation:
Reference: https://github.com/GoogleCloudPlatform/continuous-deployment-on-kubernetes/blob/master/ README.md
NEW QUESTION 64
You have developed a non-critical update to your application that is running in a managed instance group, and have created a new instance template with the update that you want to release. To prevent any possible impact to the application, you don't want to update any running instances. You want any new instances that are created by the managed instance group to contain the new update. What should you do?
- A. Start a new rolling restart operation.
- B. Start a new rolling replace operation.
- C. Start a new rolling update. Select the Opportunistic update mode.
- D. Start a new rolling update. Select the Proactive update mode.
Answer: C
NEW QUESTION 65
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