Deployment Environments DY0-001 Practice Questions (Page 1)

Questions 1–5

1. 1foundation · easy

   What is the primary purpose of edge computing in a deployment environment?

   • ATo replace all on-premises servers with virtual machines in the cloud.
   • BTo centralize all data processing in a single cloud region for easier management.
   • CTo provide a backup data center in a different geographic region.
   • DTo process data closer to its source, reducing latency and bandwidth usage.
   Reveal Solution Discussion Select an answer first
2. 2application · medium

   A manufacturing company operates a network of automated assembly lines in a remote factory with intermittent internet connectivity. Each line's sensors generate terabytes of data per day that must be analyzed in real-time to detect defects and halt the line if a problem is found. The company also needs to run a weekly batch analysis of all the week's data at their central headquarters. Which deployment approach is most appropriate for the real-time defect detection?

   • AStream all sensor data directly to a public cloud analytics service for real-time processing.
   • BInstall a large on-premises server at the factory to handle both real-time and weekly batch analysis.
   • CDeploy a containerized analytics application on an edge gateway located in the factory to process data locally.
   • DUse a hybrid cloud model where all data is sent to the private cloud at headquarters for processing.
   Reveal Solution Discussion Select an answer first
4. 3foundation · easy

   Which cloud deployment model is characterized by infrastructure that is provisioned for exclusive use by a single organization, but may be managed by a third party and located on or off premises?

   • AHybrid cloud
   • BPublic cloud
   • CCommunity cloud
   • DPrivate cloud
   Reveal Solution Discussion Select an answer first
5. 4application · medium

   A financial services firm must process sensitive customer data that is subject to strict regulatory requirements mandating that the data never leave the organization's physical premises. However, the firm occasionally needs to burst compute capacity for quarterly risk simulations that far exceed their in-house cluster's capability. Which deployment strategy best satisfies both the data residency constraint and the need for temporary compute elasticity?

   • AMove all workloads to a public cloud provider's region within the same country, relying on the provider's compliance certifications.
   • BKeep the sensitive data processing on-premises and use a hybrid model where only the simulation code and non-sensitive parameters are sent to a public cloud for the burst capacity.
   • CDeploy a private cloud on-premises and expand its capacity by purchasing additional physical servers to handle the peak simulation load.
   • DUse an edge computing deployment where the simulation is processed on IoT devices located within the firm's offices.
   Reveal Solution Discussion Select an answer first
6. 5expert · hard

   A smart-city project deploys thousands of sensors to monitor traffic and air quality. The sensors generate data continuously. The city wants to use this data to provide real-time traffic light adjustments and also to run long-term trend analysis for urban planning. The city has a central cloud environment. Which deployment architecture best meets both the real-time and long-term analysis needs?

   • AUse edge gateways to process data for real-time traffic adjustments and send only aggregated or relevant data to the central cloud for long-term analysis.
   • BDeploy a dedicated on-premises data center in the city to handle all processing and analysis.
   • CSend all raw sensor data directly to the central cloud for both real-time processing and long-term analysis.
   • DUse a hybrid cloud where the real-time processing is done in a private cloud and the long-term analysis is done in a public cloud.
   Reveal Solution Discussion Select an answer first