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質問 # 140
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 write data directly to GCS.
- B. Vehicles stream data directly to Google BigQuery.
- C. Vehicles write data directly to Google Cloud Pub/Sub.
- D. Vehicles continue to write data using the existing system (FTP).
正解：C
解説：
Explanation
https://cloud.google.com/solutions/data-lifecycle-cloud-platform
https://cloud.google.com/solutions/designing-connected-vehicle-platform
質問 # 141
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 and run tests on production deployments.
- B. Use Spinnaker to deploy builds to production using the red/black deployment strategy so that changes can easily be rolled back.
- C. 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.
- D. 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.
正解：C
解説：
Reference: https://github.com/GoogleCloudPlatform/continuous-deployment-on-kubernetes/blob/master/ README.md
質問 # 142
For this question, refer to the Mountkirk Games case study.
Mountkirk Games wants to set up a real-time analytics platform for their new game. The new platform must meet their technical requirements. Which combination of Google technologies will meet all of their requirements?
- A. Cloud Dataflow, Cloud Storage, Cloud Pub/Sub, and BigQuery
- B. Cloud Pub/Sub, Compute Engine, Cloud Storage, and Cloud Dataproc
- C. Cloud Dataproc, Cloud Pub/Sub, Cloud SQL, and Cloud Dataflow
- D. Container Engine, Cloud Pub/Sub, and Cloud SQL
- E. Cloud SQL, Cloud Storage, Cloud Pub/Sub, and Cloud Dataflow
正解：A
解説：
A real time requires Stream / Messaging so Pub/Sub, Analytics by Big Query.
Ingest millions of streaming events per second from anywhere in the world with Cloud Pub/Sub, powered by Google's unique, high-speed private network. Process the streams with Cloud Dataflow to ensure reliable, exactly-once, low-latency data transformation. Stream the transformed data into BigQuery, the cloud-native data warehousing service, for immediate analysis via SQL or popular visualization tools.
From scenario: They plan to deploy the game's backend on Google Compute Engine so they can capture streaming metrics, run intensive analytics.
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 SQL queries to access at least 10 TB of historical data
* Process files that are regularly uploaded by users' mobile devices
* Use only fully managed services
References:
https://cloud.google.com/solutions/big-data/stream-analytics/
質問 # 143
You deploy your custom Java application to Google App Engine. It fails to deploy and gives you the following stack trace.
What should you do?
- A. Upload missing JAR files and redeploy your application.
- B. Digitally sign all of your JAR files and redeploy your application
- C. Recompile the CLoakedServlet class using and MD5 hash instead of SHA1
正解：B
質問 # 144
As part of their new application experience, Dress4Wm allows customers to upload images of themselves.
The customer has exclusive control over who may view these images.
Customers should be able to upload images with minimal latency and also be shown their images quickly on the main application page when they log in.
Which configuration should Dress4Win use?
- A. Store image files in a Google Cloud Storage bucket. Use Google Cloud Datastore to maintain metadata that maps each customer's ID and their image files.
- B. Use a distributed file system to store customers' images. As storage needs increase, add more persistent disks and/or nodes. Use a Google Cloud SQL database to maintain metadata that maps each customer's ID to their image files.
- C. Store image files in a Google Cloud Storage bucket. Add custom metadata to the uploaded images in Cloud Storage that contains the customer's unique ID.
- D. Use a distributed file system to store customers' images. As storage needs increase, add more persistent disks and/or nodes. Assign each customer a unique ID, which sets each file's owner attribute, ensuring privacy of images.
正解：A
質問 # 145
A small number of API requests to your microservices-based application take a very long time. You know that each request to the API can traverse many services. You want to know which service takes the longest in those cases. What should you do?
- A. Send custom metrics for each of your requests to Stackdriver Monitoring.
- B. Set timeouts on your application so that you can fail requests faster.
- C. Use Stackdriver Monitoring to look for insights that show when your API latencies are high.
- D. Instrument your application with Stackdnver Trace in order to break down the request latencies at each microservice.
正解：C
質問 # 146
You want to allow your operations learn to store togs from all the production protects in your Organization, without during logs from other projects All of the production projects are contained in a folder. You want to ensure that all logs for existing and new production projects are captured automatically. What should you do?
- A. Create an aggregated export on the Production folder. Set the log sink to be a Cloud Storage bucket in an operations project
- B. Create an aggregated export on the Organization resource. Set the tog sink to be a Cloud Storage bucket in an operations project.
- C. Create tog exports in the production projects. Set the tog sinks to be BigQuery datasets in the production projects and grant IAM access to the operations team to run queries on the datasets
- D. Create log exports in the production projects. Set the log sinks to be a Cloud Storage bucket in an operations project.
正解：A
解説：
An aggregated export is a type of sink that combines and routes log entries from the Google Cloud resources contained by an organization or folder1. By creating an aggregated export on the Production folder, you can capture all the logs from the existing and new production projects in that folder automatically1.
A log sink is a destination for log entries that match a filter1. By setting the log sink to be a Cloud Storage bucket in an operations project, you can store the log entries in Cloud Storage and allow your operations team to access them1.
質問 # 147
TerramEarth has equipped all connected trucks with servers and sensors to collect telemetry data. Next year they want to use the data to train machine learning models. They want to store this data in the cloud while reducing costs.
What should they do?
- A. Have the vehicle's computer compress the data in hourly snapshots, and store it in a GCS Coldline bucket
- B. Have the vehicle's computer compress the data in hourly snapshots, and store it in a Google Cloud Storage (GCS) Nearline bucket
- C. Push the telemetry data in real-time to a streaming dataflow job that compresses the data, and store it in Google BigQuery
- D. Push the telemetry data in real-time to a streaming dataflow job that compresses the data, and store it in Cloud Bigtable
正解：A
解説：
Storage is the best choice for data that you plan to access at most once a year, due to its slightly lower availability, 90-day minimum storage duration, costs for data access, and higher per-operation costs. For example:
Cold Data Storage - Infrequently accessed data, such as data stored for legal or regulatory reasons, can be stored at low cost as Coldline Storage, and be available when you need it.
Disaster recovery - In the event of a disaster recovery event, recovery time is key. Cloud Storage provides low latency access to data stored as Coldline Storage.
References: https://cloud.google.com/storage/docs/storage-classes
質問 # 148
Your company is developing a web-based application. You need to make sure that production deployments are linked to source code commits and are fully auditable. What should you do?
- A. Make sure the developer is tagging the commits with :latest
- B. Make the container tag match the source code commit hash.
- C. Make sure a developer is adding a comment to the commit that links to the deployment.
- D. Make sure a developer is tagging the code commit with the date and time of commit
正解：B
解説：
From: https://cloud.google.com/architecture/best-practices-for-building-containers Under: Tagging using the Git commit hash (bottom of page almost)
"In this case, a common way of handling version numbers is to use the Git commit SHA-1 hash (or a short version of it) as the version number. By design, the Git commit hash is immutable and references a specific version of your software.
You can use this commit hash as a version number for your software, but also as a tag for the Docker image built from this specific version of your software. Doing so makes Docker images traceable: because in this case the image tag is immutable, you instantly know which specific version of your software is running inside a given container."
質問 # 149
You set up an autoscaling instance group to serve web traffic for an upcoming launch. After configuring the instance group as a backend service to an HTTP(S) load balancer, you notice that virtual machine (VM) instances are being terminated and re-launched every minute. The instances do not have a public IP address. You have verified the appropriate web response is coming from each instance using the curl command. You want to ensure the backend is configured correctly.
What should you do?
- A. Ensure that a firewall rules exists to allow source traffic on HTTP/HTTPS to reach the load balancer.
- B. Create a tag on each instance with the name of the load balancer. Configure a firewall rule with the name of the load balancer as the source and the instance tag as the destination.
- C. Assign a public IP to each instance and configure a firewall rule to allow the load balancer to reach the instance public IP.
- D. Ensure that a firewall rule exists to allow load balancer health checks to reach the instances in the instance group.
正解：D
解説：
Explanation/Reference:
Explanation:
The best practice when configuration a health check is to check health and serve traffic on the same port.
However, it is possible to perform health checks on one port, but serve traffic on another. If you do use two different ports, ensure that firewall rules and services running on instances are configured appropriately. If you run health checks and serve traffic on the same port, but decide to switch ports at some point, be sure to update both the backend service and the health check.
Backend services that do not have a valid global forwarding rule referencing it will not be health checked and will have no health status.
References: https://cloud.google.com/compute/docs/load-balancing/http/backend-service
質問 # 150
You want to enable your running Google Container Engine cluster to scale as demand for your application changes.
What should you do?
- A. Create a new Container Engine cluster with the following command:
gcloud alpha container clusters create mycluster --enable-autocaling --min-nodes=1 --max-nodes=10 - B. Add additional nodes to your Container Engine cluster using the following command:
gcloud container clusters resize CLUSTER_NAME --size 10 - C. Add a tag to the instances in the cluster with the following command:
gcloud compute instances add-tags INSTANCE --tags enable --autoscaling max-nodes-10 - D. Update the existing Container Engine cluster with the following command:
gcloud alpha container clusters update mycluster --enable-autoscaling --min-nodes=1 --max-nodes=10
正解：C
解説：
and redeploy your application.
Explanation:
Cluster autoscaling
--enable-autoscaling
Enables autoscaling for a node pool.
Enables autoscaling in the node pool specified by --node-pool or the default node pool if --node-pool is not provided.
Where:
--max-nodes=MAX_NODES
Maximum number of nodes in the node pool.
Maximum number of nodes to which the node pool specified by --node-pool (or default node pool if unspecified) can scale.
Incorrect Answers:
C, D: Warning: Do not use Alpha Clusters or alpha features for production workloads.
Note: You can experiment with Kubernetes alpha features by creating an alpha cluster. Alpha clusters are short-lived clusters that run stable Kubernetes releases with all Kubernetes APIs and features enabled. Alpha clusters are designed for advanced users and early adopters to experiment with workloads that take advantage of new features before those features are production-ready. You can use Alpha clusters just like normal Kubernetes Engine clusters.
References: https://cloud.google.com/sdk/gcloud/reference/container/clusters/create Reference:
https://cloud.google.com/kubernetes-engine/docs/concepts/cluster-autoscaler
質問 # 151
You are designing an application for use only during business hours. For the minimum viable product release, you'd like to use a managed product that automatically "scales to zero" so you don't incur costs when there is no activity.
Which primary compute resource should you choose?
- A. Compute Engine
- B. AppEngine flexible environment
- C. Cloud Functions
- D. Kubernetes Engine
正解：C
解説：
Explanation
https://cloud.google.com/serverless-options
質問 # 152
You have deployed an application to Kubernetes Engine, and are using the Cloud SQL proxy container to make the Cloud SQL database available to the services running on Kubernetes. You are notified that the application is reporting database connection issues. Your company policies require a post-mortem. What should you do?
- A. In the GCP Console, navigate to Cloud SQL. Restore the latest backup. Use kubect1 to restart all pods.
- B. In the GCP Console, navigate to Stackdriver Logging. Consult logs for Kubernetes Engine and Cloud SQL.
- C. Use gcloud sql instances restart.
- D. Validate that the Service Account used by the Cloud SQL proxy container still has the Cloud Build Editor role.
正解：B
質問 # 153
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. Expose the VPC to the on-premises network using IAM and VPC Sharing.
- C. Deploy Cloud VPN Gateway in each region. Ensure that each region has at least one VPN tunnel to the
on-premises peer gateway. - D. Create a global Cloud VPN Gateway with VPN tunnels from each region to the on-premises peer
gateway.
正解：C
質問 # 154
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. To be compliant with European GDPR regulation, TerramEarth is required to delete data generated from its European customers after a period of 36 months when it contains personal data. In the new architecture, this data will be stored in both Cloud Storage and BigQuery. What should you do?
- A. Create a BigQuery time-partitioned table for the European data, and set the partition expiration period to 36 months. For Cloud Storage, use gsutil to enable lifecycle management using a DELETE action with an Age condition of 36 months.
- B. Create a BigQuery table for the European data, and set the table retention period to 36 months.
For Cloud Storage, use gsutil to enable lifecycle management using a DELETE action with an Age condition of 36 months. - C. Create a BigQuery time-partitioned table for the European data, and set the partition period to 36 months. For Cloud Storage, use gsutil to create a SetStorageClass to NONE action with an Age condition of 36 months.
- D. Create a BigQuery table for the European data, and set the table retention period to 36 months.
For Cloud Storage, use gsutil to create a SetStorageClass to NONE action when with an Age condition of 36 months.
正解：D
質問 # 155
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 a JAX-RS Jersey Java-based framework. Focus on an API for the public.
- B. Use Google App Engine with Google Cloud Endpoints. Focus on an API for dealers and partners.
- C. Use Google Container Engine with a Django Python container. Focus on an API for the public.
- D. Use Google App Engine with the Swagger (open API Specification) framework. 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.
正解：B
解説：
https://cloud.google.com/endpoints/docs/openapi/about-cloud-endpoints?hl=en_US&_ga=2.21787131.-1712523161.1522785064
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
質問 # 156
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