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NEW QUESTION # 130
You are tasked with building an online analytical processing (OLAP) marketing analytics and reporting tool. This requires a relational database that can operate on hundreds of terabytes of data. What is the Google- recommended tool for such applications?
- A. Cloud Spanner, because it is globally distributed
- B. Cloud Firestore, because it offers real-time synchronization across devices
- C. BigQuery, because it is designed for large-scale processing of tabular data
- D. Cloud SQL, because it is a fully managed relational database
Answer: C
Explanation:
Because this requires a relational database
https://cloud.google.com/files/BigQueryTechnicalWP.pdf
BigQuery is relational database and suport OLAP
Cloud Spanner OLTP
NEW QUESTION # 131
Your company runs several databases on a single MySQL instance. They need to take backups of a specific database at regular intervals. The backup activity needs to complete as quickly as possible and cannot be allowed to impact disk performance. How should you configure the storage?
- A. Mount a Local SSD volume as the backup location. After the backup is complete, use gsutil to move the backup to Google Cloud Storage.
- B. Configure a cron job to use the gcloud tool to take regular backups using persistent disk snapshots.
- C. Use gcsfuse to mount a Google Cloud Storage bucket as a volume directly on the instance and write backups to the mounted location using mysqldump
- D. Mount additional persistent disk volumes onto each virtual machine (VM) instance in a RAID10 array and use LVM to create snapshots to send to Cloud Storage.
Answer: C
Explanation:
Explanation
https://cloud.google.com/storage/docs/gcs-fuse
References: https://github.com/mvarrieur/MySQL-backup-to-Google-Cloud-Storage
https://cloud.google.com/storage/docs/gcs-fuse
NEW QUESTION # 132
For this question, refer to the TerramEarth case study
Your development team has created a structured API to retrieve vehicle data. They want to allow third parties to develop tools for dealerships that use this vehicle event data. You want to support delegated authorization against this data. What should you do?
- A. Create secondary credentials for each dealer that can be given to the trusted third party.
- B. Restrict data access based on the source IP address of the partner systems.
- C. Build SAML 2.0 SSO compatibility into your authentication system.
- D. Build or leverage an OAuth-compatible access control system.
Answer: D
Explanation:
https://cloud.google.com/appengine/docs/flexible/go/authorizing-apps
https://cloud.google.com/docs/enterprise/best-practices-for-enterprise-organizations#delegate_application_authorization_with_oauth2 Delegate application authorization with OAuth2 Cloud Platform APIs support OAuth 2.0, and scopes provide granular authorization over the methods that are supported. Cloud Platform supports both service-account and user-account OAuth, also called three-legged OAuth.
References:
https://cloud.google.com/docs/enterprise/best-practices-for-enterprise-organizations#delegate_application_authorization_with_oauth2
https://cloud.google.com/appengine/docs/flexible/go/authorizing-apps
NEW QUESTION # 133
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 data. You want to help them find a solution that meets their needs, what should you do?
- A. Direct them to download and install the Google StackDriver logging agent.
- B. Help them upgrade their current tool to take advantage of any new features.
- C. Help them define their requirements and assess viable logging tools.
- D. Send them a list of online resources about logging best practices.
Answer: A
Explanation:
The Stackdriver Logging agent streams logs from your VM instances and from selected third party software packages to Stackdriver Logging. Using the agent is optional but we recommend it. The agent runs under both Linux and Microsoft Windows.
Note: 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.
References: https://cloud.google.com/logging/docs/agent/installation
https://medium.com/google-cloud/hidden-super-powers-of-stackdriver-logging-ca110dae7e74
NEW QUESTION # 134
Dress4Win has end-to-end tests covering 100% of their endpoints.
They want to ensure that the move to the cloud does not introduce any new bugs.
Which additional testing methods should the developers employ to prevent an outage?
- A. They should add additional unit tests and production scale load tests on their cloud staging
environment. - B. They should run the end-to-end tests in the cloud staging environment to determine if the code is
working as intended. - C. They should add canary tests so developers can measure how much of an impact the new release
causes to latency. - D. They should enable Google Stackdriver Debugger on the application code to show errors in the code.
Answer: A
NEW QUESTION # 135
You are tasked with building an online analytical processing (OLAP) marketing analytics and reporting tool.
This requires a relational database that can operate on hundreds of terabytes of data. What is the Google recommended tool for such applications?
- A. Cloud Spanner, because it is globally distributed
- B. Cloud Firestore, because it offers real-time synchronization across devices
- C. BigQuery, because it is designed for large-scale processing of tabular data
- D. Cloud SQL, because it is a fully managed relational database
Answer: A
Explanation:
Reference: https://cloud.google.com/files/BigQueryTechnicalWP.pdf
NEW QUESTION # 136
Your company has an application running as a Deployment in a Google Kubernetes Engine (GKE) cluster When releasing new versions of the application via a rolling deployment, the team has been causing outages The root cause of the outages is misconfigurations with parameters that are only used in production You want to put preventive measures for this in the platform to prevent outages What should you do?
- A. Configure liveness and readiness probes in the Pod specification
- B. Configure health checks on the managed instance group
- C. Create a Scheduled Task to check whether the application is available
- D. Configure an uptime alert in Cloud Monitoring
Answer: B
Explanation:
This option can help prevent outages caused by misconfigurations with parameters that are only used in production. Liveness and readiness probes are mechanisms to check the health and availability of the Pods and containers in a GKE cluster. Liveness probes determine if a container is still running, and if not, restart it.
Readiness probes determine if a container is ready to serve requests, and if not, remove it from the load balancer. By configuring liveness and readiness probes in the Pod specification, you can ensure that your application can handle traffic and recover from failures gracefully during a rolling update. The other options are not optimal for this scenario, because they either do not prevent outages, but only alert or monitor them (B, C), or do not apply to GKE clusters, but to Compute Engine instances (D). References:
https://cloud.google.com/kubernetes-engine/docs/how-to/updating-apps
https://cloud.google.com/blog/products/containers-kubernetes/kubernetes-best-practices-setting-up-health
NEW QUESTION # 137
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. Create a new service account with BigQuery access and execute your script with that user
- B. Run your script on a new virtual machine with the BigQuery access scope enabled
- C. Install the bq component for gccloud with the command gcloud components install bq.
- D. Install the latest BigQuery API client library for Python
Answer: D
Explanation:
https://cloud.google.com/bigquery/docs/python-client-migration
NEW QUESTION # 138
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 Kubernetes Registry, Google Container Engine, Google HTTP(S) Load Balancer
- D. Google Cloud Storage, Google Cloud Dataflow, Google Compute Engine
Answer: C
Explanation:
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 # 139
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 upload gzip files to a Multi-Regional Cloud Storage bucket using gcloud. Use Google Data Studio for analysis and reporting.
- B. 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.
- 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: B
NEW QUESTION # 140
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 Datastore
- B. BigQuery
- C. Cloud Bigtable
- D. Cloud Spanner
Answer: C
NEW QUESTION # 141
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 with the default retention policies
- C. Configure Stackdriver Monitoring for all Projects, and export to Google Cloud Storage
- 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.
References: https://cloud.google.com/stackdriver/
NEW QUESTION # 142
Your company just finished a rapid lift and shift to Google Compute Engine for your compute needs. You have another 9 months to design and deploy a more cloud-native solution. Specifically, you want a system that is no-ops and auto-scaling. Which two compute products should you choose? Choose 2 answers
- A. Compute Engine with managed instance groups
- B. Compute Engine with containers
- C. Compute Engine with custom instance types
- D. Google Kubernetes Engine with containers
- E. Google App Engine Standard Environment
Answer: D,E
Explanation:
B: With Container Engine, Google will automatically deploy your cluster for you, update, patch, secure the nodes.
Kubernetes Engine's cluster autoscaler automatically resizes clusters based on the demands of the workloads you want to run.
C: Solutions like Datastore, BigQuery, AppEngine, etc are truly NoOps.
App Engine by default scales the number of instances running up and down to match the load, thus providing consistent performance for your app at all times while minimizing idle instances and thus reducing cost.
Note: At a high level, NoOps means that there is no infrastructure to build out and manage during usage of the platform. Typically, the compromise you make with NoOps is that you lose control of the underlying infrastructure.
NEW QUESTION # 143
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. Help them upgrade their current tool to take advantage of any new features.
- B. Help them define their requirements and assess viable logging tools.
- C. Direct them to download and install the Google StackDriver logging agent.
- D. Send them a list of online resources about logging best practices.
Answer: B
Explanation:
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 # 144
You have deployed an application to Google Kubernetes Engine (GKE), 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. Validate that the Service Account used by the Cloud SQL proxy container still has the Cloud Build Editor role.
- B. Use gcloud sql instances restart.
- C. In the GCP Console, navigate to Stackdriver Logging. Consult logs for (GKE) and Cloud SQL.
- D. In the GCP Console, navigate to Cloud SQL. Restore the latest backup. Use kubectlto restart all pods.
Answer: C
NEW QUESTION # 145
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