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NEW QUESTION # 104
Mountkirk Games wants to set up a continuous delivery pipeline. Their architecture includes many small services that they want to be able to update and roll back quickly. Mountkirk Games has the following requirements:
* Services are deployed redundantly across multiple regions in the US and Europe
* Only frontend services are exposed on the public internet
* They can provide a single frontend IP for their fleet of services
* Deployment artifacts are immutable
Which set of products should they use?
- A. Google Cloud Storage, Google App Engine, Google Network Load Balancer
- B. Google Cloud Functions, Google Cloud Pub/Sub, Google Cloud Deployment Manager
- C. Google Kubernetes Registry, Google Container Engine, Google HTTP(S) Load Balancer
- D. Google Cloud Storage, Google Cloud Dataflow, Google Compute Engine
Answer: C
NEW QUESTION # 105
For this question, refer to the Mountkirk Games case study.
Mountkirk Games wants to set up a continuous delivery pipeline. Their architecture includes many small services that they want to be able to update and roll back quickly.
Mountkirk Games has the following requirements:
* Services are deployed redundantly across multiple regions in the US and Europe.
* Only frontend services are exposed on the public internet.
* They can provide a single frontend IP for their fleet of services.
* Deployment artifacts are immutable.
Which set of products should they use?
- A. Google Cloud Storage, Google App Engine, Google Network Load Balancer
- B. Google Cloud Functions, Google Cloud Pub/Sub, Google Cloud Deployment Manager
- C. Google Container Registry, Google Container Engine, Google HTTP(s) Load Balancer
- D. Google Cloud Storage, Google Cloud Dataflow, Google Compute Engine
Answer: C
Explanation:
Topic 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.
NEW QUESTION # 106
You are deploying an application on App Engine that needs to integrate with an on-premises database. For security purposes, your on-premises database must not be accessible through the public Internet. What should you do?
- A. Deploy your application on App Engine standard environment and use Cloud VPN to limit access to the onpremises database.
- B. Deploy your application on App Engine standard environment and use App Engine firewall rules to limit access to the open on-premises database.
- C. Deploy your application on App Engine flexible environment and use App Engine firewall rules to limit access to the on-premises database.
- D. Deploy your application on App Engine flexible environment and use Cloud VPN to limit access to the onpremises database.
Answer: B
NEW QUESTION # 107
For this question, refer to the JencoMart case study
A few days after JencoMart migrates the user credentials database to Google Cloud Platform and shuts down the old server, the new database server stops responding to SSH connections. It is still serving database requests to the application servers correctly. What three steps should you take to diagnose the problem?
Choose 3 answers
- A. Connect the machine to another network with very simple firewall rules and investigate.
- B. Delete the instance, attach the disk to a new VM, and investigate.
- C. Take a snapshot of the disk and connect to a new machine to investigate.
- D. Print the Serial Console output for the instance for troubleshooting, activate the interactive console, and investigate.
- E. Check inbound firewall rules for the network the machine is connected to.
- F. Delete the virtual machine (VM) and disks and create a new one.
Answer: C,D,E
Explanation:
Explanation
https://cloud.google.com/compute/docs/troubleshooting/troubleshooting-ssh D: Handling "Unable to connect on port 22" error message Possible causes include:
There is no firewall rule allowing SSH access on the port. SSH access on port 22 is enabled on all Compute Engine instances by default. If you have disabled access, SSH from the Browser will not work. If you run sshd on a port other than 22, you need to enable the access to that port with a custom firewall rule.
The firewall rule allowing SSH access is enabled, but is not configured to allow connections from GCP Console services. Source IP addresses for browser-based SSH sessions are dynamically allocated by GCP Console and can vary from session to session.
References:
https://cloud.google.com/compute/docs/ssh-in-browser
https://cloud.google.com/compute/docs/ssh-in-browser
NEW QUESTION # 108
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: A
Explanation:
Explanation: https://cloud.google.com/solutions/disaster-recovery-cookbook
NEW QUESTION # 109
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. Identify enterprise applications with internal dependencies and recommend these as a first move to the cloud.
- C. Identify self-contained applications with external dependencies as a first move to the cloud.
- D. Recommend moving their message queuing servers to the cloud and continue handling requests to on- premise applications.
Answer: A
NEW QUESTION # 110
For this question, refer to the EHR Healthcare case study. EHR has single Dedicated Interconnect connection between their primary data center and Googles network. This connection satisfies EHR's network and security policies:
* On-premises servers without public IP addresses need to connect to cloud resources without public IP addresses
* Traffic flows from production network mgmt. servers to Compute Engine virtual machines should never traverse the public internet.
You need to upgrade the EHR connection to comply with their requirements. The new connection design must support business critical needs and meet the same network and security policy requirements. What should you do?
- A. Upgrade the bandwidth on the Dedicated Interconnect connection to 100 G
- B. Add a new Dedicated Interconnect connection
- C. Add a new Carrier Peering connection
- D. Add three new Cloud VPN connections
Answer: B
Explanation:
Explanation
The case does not call out the throughput being an issue. However, to achieve 99.99%, you need to have 4 connections as per Google recommendations. However, in the options only A has the option to add an additional Interconnect connection.
https://cloud.google.com/network-connectivity/docs/interconnect/concepts/dedicated-overview#availability
NEW QUESTION # 111
For this question, refer to the Mountkirk Games case study.
Mountkirk Games wants you to design their new testing strategy. How should the test coverage differ from their existing backends on the other platforms?
- A. Unit tests are no longer required, only end-to-end tests.
- B. Tests should be applied after the release is in the production environment.
- C. Tests should include directly testing the Google Cloud Platform (GCP) infrastructure.
- D. Tests should scale well beyond the prior approaches.
Answer: D
Explanation:
Explanation
From Scenario:
A few of their games were more popular than expected, and they had problems scaling their application servers, MySQL databases, and analytics tools.
Requirements for Game Analytics Platform include: Dynamically scale up or down based on game activity
Topic 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
20 TB
Complex table structure
Well maintained, clean data
Strong backup strategy
* PostgreSQL database stores user credentials
Single-homed in US West
No redundancy
Backed up every 12 hours
100% uptime service level agreement (SLA)
Authenticates all users
Compute
* 30 machines in US West Coast, each machine has:
Twin, dual core CPUs
32GB of RAM
Twin 250 GB HDD (RAID 1)
* 20 machines in US East Coast, each machine has:
Single dual-core CPU
24 GB of RAM
Twin 250 GB HDD (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.
NEW QUESTION # 112
Your company sends all Google Cloud logs to Cloud Logging. Your security team wants to monitor the logs. You want to ensure that the security team can react quickly if an anomaly such as an unwanted firewall change or server breach is detected. You want to follow Google-recommended practices. What should you do?
- A. Export logs to a Cloud Storage bucket, and trigger Cloud Run with the relevant log events.
- B. Export logs to BigQuery, and trigger a query in BigQuery to process the log data for the relevant events.
- C. Schedule a cron job with Cloud Scheduler. The scheduled job queries the logs every minute for the relevant events.
- D. Export logs to a Pub/Sub topic, and trigger Cloud Function with the relevant log events.
Answer: D
Explanation:
https://cloud.google.com/blog/products/management-tools/automate-your-response-to-a-cloud-logging-event
NEW QUESTION # 113
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. Considering the technical requirements, how should you reduce the unplanned vehicle downtime in GCP?
- A. Use BigQuery as the data warehouse. Connect all vehicles to the network and stream data into BigQuery using Cloud Pub/Sub and Cloud Dataflow. Use Google Data Studio for analysis and reporting.
- B. Use BigQuery as the data warehouse. Connect all vehicles to the network and upload gzip files to a Multi-Regional Cloud Storage bucket using gcloud. Use Google Data Studio for analysis and reporting.
- C. Use Cloud Dataproc Hive as the data warehouse. Upload gzip files to a MultiRegional Cloud Storage bucket. Upload this data into BigQuery using gcloud. Use Google data Studio for analysis and reporting.
- D. Use Cloud Dataproc Hive as the data warehouse. Directly stream data into prtitioned Hive tables.
Use Pig scripts to analyze data.
Answer: A
NEW QUESTION # 114
An application development team believes their current logging tool will not meet their needs for their new cloud-based product. They want a bettor tool to capture errors and help them analyze their historical log dat a. You want to help them find a solution that meets their needs, what should you do?
- A. Send them a list of online resources about logging best practices.
- B. Help them upgrade their current tool to take advantage of any new features.
- C. Direct them to download and install the Google StackDriver logging agent.
- D. Help them define their requirements and assess viable logging tools.
Answer: D
Explanation:
Reference:
Help them define their requirements and assess viable logging tools. They know the requirements and the existing tools' problems. While it's true StackDriver Logging and Error Reporting possibly meet all their requirements, there might be other tools also meet their need. They need you to provide expertise to make assessment for new tools, specifically, logging tools that can "capture errors and help them analyze their historical log data".
References: https://cloud.google.com/logging/docs/agent/installation
NEW QUESTION # 115
For this question, refer to the TerramEarth case study. TerramEarth has decided to store data files in Cloud Storage. You need to configure Cloud Storage lifecycle rule to store 1 year of data and minimize file storage cost.
Which two actions should you take?
- A. Create a Cloud Storage lifecycle rule with Age: "30", Storage Class: "Standard", and Action: "Set to Coldline", and create a second GCS life-cycle rule with Age: "365", Storage Class: "Coldline", and Action: "Delete".
- B. Create a Cloud Storage lifecycle rule with Age: "30", Storage Class: "Coldline", and Action: "Set to Nearline", and create a second GCS life-cycle rule with Age: "91", Storage Class: "Coldline", and Action:
"Set to Nearline". - C. Create a Cloud Storage lifecycle rule with Age: "30", Storage Class: "Standard", and Action: "Set to Coldline", and create a second GCS life-cycle rule with Age: "365", Storage Class: "Nearline", and Action: "Delete".
- D. Create a Cloud Storage lifecycle rule with Age: "90", Storage Class: "Standard", and Action: "Set to Nearline", and create a second GCS life-cycle rule with Age: "91", Storage Class: "Nearline", and Action:
"Set to Coldline".
Answer: A
NEW QUESTION # 116
You need to deploy an application to Google Cloud. The application receives traffic via TCP and reads and writes data to the filesystem. The application does not support horizontal scaling. The application process requires full control over the data on the file system because concurrent access causes corruption. The business is willing to accept a downtime when an incident occurs, but the application must be available 24/7 to support their business operations. You need to design the architecture of this application on Google Cloud.
What should you do?
- A. Use an unmanaged instance group with an active and standby instance in different zones, use a regional persistent disk, and use an HTTP load balancer in front of the instances.
- B. Use a managed instance group with instances in multiple zones, use Cloud Filestore, and use a network load balancer in front of the instances.
- C. Use a managed instance group with instances in multiple zones, use Cloud Filestore, and use an HTTP load balancer in front of the instances.
- D. Use an unmanaged instance group with an active and standby instance in different zones, use a regional persistent disk, and use a network load balancer in front of the instances.
Answer: D
Explanation:
Reference: https://cloud.google.com/compute/docs/instance-groups
NEW QUESTION # 117
An application development team has come to you for advice.They are planning to write and deploy an HTTP(S) API using Go 1.12. The API will have a very unpredictable workload and must remain reliable during peaks in traffic. They want to minimize operational overhead for this application. What approach should you recommend?
- A. Develop the application for App Engine standard environment
- B. Develop an application with containers, and deploy to Google Kubernetes Engine (GKE)
- C. Use a Managed Instance Group when deploying to Compute Engine
- D. Develop the application for App Engine Flexible environment using a custom runtime
Answer: A
Explanation:
Explanation
https://cloud.google.com/appengine/docs/the-appengine-environments
NEW QUESTION # 118
Your customer is moving their corporate applications to Google Cloud Platform. The security team wants detailed visibility of all projects in the organization. You provision the Google Cloud Resource Manager and set up yourself as the org admin. What Google Cloud Identity and Access Management (Cloud IAM) roles should you give to the security team'?
- A. Org viewer, project viewer
- B. Project owner, network admin
- C. Org admin, project browser
- D. Org viewer, project owner
Answer: A
Explanation:
Explanation
https://cloud.google.com/iam/docs/using-iam-securely
NEW QUESTION # 119
For this question, refer to the TerramEarth case study. TerramEarth has decided to store data files in Cloud Storage. You need to configure Cloud Storage lifecycle rule to store 1 year of data and minimize file storage cost.
Which two actions should you take?
- A. Create a Cloud Storage lifecycle rule with Age: "30", Storage Class: "Coldline", and Action: "Set to Nearline", and create a second GCS life-cycle rule with Age: "91", Storage Class: "Coldline", and Action: "Set to Nearline".
- B. Create a Cloud Storage lifecycle rule with Age: "30", Storage Class: "Standard", and Action: "Set to Coldline", and create a second GCS life-cycle rule with Age: "365", Storage Class: "Coldline", and Action:
"Delete". - C. Create a Cloud Storage lifecycle rule with Age: "90", Storage Class: "Standard", and Action: "Set to Nearline", and create a second GCS life-cycle rule with Age: "91", Storage Class: "Nearline", and Action:
"Set to Coldline". - D. Create a Cloud Storage lifecycle rule with Age: "30", Storage Class: "Standard", and Action: "Set to Coldline", and create a second GCS life-cycle rule with Age: "365", Storage Class: "Nearline", and Action:
"Delete".
Answer: B
NEW QUESTION # 120
Your company has a Google Cloud project that uses BlgQuery for data warehousing There are some tables that contain personally identifiable information (PI!) Only the compliance team may access the PH. The other information in the tables must be available to the data science team. You want to minimize cost and the time it takes to assign appropriate access to the tables What should you do?
- A. 1 Create a dataset for the data science team
2 Create views of tables that you want to share excluding Pll
3 Assign an appropriate project-level IAM role to the members of the data science team
4 Assign access controls to the dataset that contains the view
5 Authorize the view to access the source dataset - B. 1 From the dataset where you have the source data, create views of tables that you want to share, excluding Pll
2 Assign an appropriate project-level IAM role to the members of the data science team
3 Assign access controls to the dataset that contains the view - C. 1. Create a dataset for the data science team.
2. Create materialized views of tables that you want to share, excluding Pll
3. Assign an appropriate project-level IAM role to the members of the data science team
4 Assign access controls to the dataset that contains the view
5 Authorize the view to access the source dataset - D. 1 From the dataset where you have the source data, create materialized views of tables that you want to share excluding Pll
2 Assign an appropriate project-level IAM role to the members of the data science team 3. Assign access controls to the dataset that contains the view.
Answer: A
Explanation:
This option can help minimize cost and time by using views and authorized datasets. Views are virtual tables defined by a SQL query that can exclude PII columns from the source tables. Views do not incur storage costs and do not duplicate data. Authorized datasets are datasets that have access to another dataset's data without granting direct access to individual users or groups. By creating a dataset for the data science team and creating views of tables that exclude PII, you can share only the relevant information with the team. By assigning an appropriate project-level IAM role to the members of the data science team, you can grant them access to the BigQuery service and resources. By assigning access controls to the dataset that contains the view, you can grant them access to query the views. By authorizing the view to access the source dataset, you can enable the view to read data from the source tables without exposing PII. The other options are not optimal for this scenario, because they either use materialized views instead of views, which incur storage costs and duplicate data (B, D), or do not create a separate dataset for the data science team, which makes it harder to manage access controls (A). References:
https://cloud.google.com/bigquery/docs/views
https://cloud.google.com/bigquery/docs/authorized-datasets
NEW QUESTION # 121
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