Cloud computing

BDPC · 30 questions

• A planning department wants elastic analytics capacity without buying every server for the basement rack. How should they define cloud computing for Big Data in that context?
• Regional analysts need to reach Big Data clusters without traveling to a single locked computer room. Which cloud access characteristic matters most?
• IT wants Hadoop- or Spark-style stacks without tying every node to a named physical rack forever. What cloud underpinning enables that flexibility?
• Election-night traffic analytics need a large burst of capacity, then quiet days afterward. Which cloud benefit should the city leverage?
• Open-data crunch seasons are short, but the city previously bought large always-on clusters. Which cloud cost-flexibility idea applies?
• A grant-funded pilot needs a short-lived Spark-capable environment within hours, not months of hardware procurement. Which cloud benefit is illustrated?
• A regional consortium runs shared analytics on capacity owned by a cloud provider, under contracts and controls the cities accept. Which ownership model is that?
• Police evidence analytics must remain on infrastructure dedicated to the agency because of policy. Which ownership model fits that constraint?
• Sensitive resident datasets must stay on-premises, but the city wants to burst heavy model training into public cloud capacity. Which model describes that design?
• The city installs and manages its own Hadoop stack on virtual machines rented from a cloud provider. Which service-range model is that?
• A city analytics team wants Spark and Kafka-like capacity without patching brokers or cluster nodes every week. Which cloud service range best matches that goal?
• After a county lake prepares daily civic metrics, leadership wants a hosted dashboard product citizens never see under the hood. Which cloud service range fits analytics consumption?
• A metro moves its Big Data lake to a public cloud. The provider hardens the foundation, yet auditors still ask who classifies resident records and manages staff identities. What shared-responsibility idea applies?
• Policy requires resident analytics datasets to remain inside the national region. How should that rule shape cloud selection for the municipal lake?
• Traffic cameras dump large video objects into one cloud region, then analysts repeatedly pull the same files into another region for nightly jobs. Which cost and architecture concern should the team address first?
• A town redesigns its Hadoop-era lake for the cloud and needs a durable landing zone for raw civic files. Which pattern commonly replaces or fronts classic HDFS in that setting?
• A parks department runs heavy MapReduce-style jobs only a few nights each month. Which cloud pattern best matches spinning capacity up for the job and releasing it afterward?
• Leadership wants two public clouds “for safety” for the same Kafka and Spark stack, but the city has deep skills in only one provider. What caution should the Big Data lead raise?
• A county lake holds critical analytical datasets that must survive a regional outage. Which cloud practice best supports disaster recovery for those stores?
• During a cloud lake review, auditors find a storage bucket of citizen personally identifiable information left publicly readable. What security baseline judgment is correct?
• Permit-portal click events spike during storm season and streaming consumers fall behind. How does cloud elasticity primarily support the Velocity V in this scenario?
• A transit agency must retain years of vehicle telemetry for trend studies. Which cloud capability most directly supports the Volume V?
• A city builds every lake job against proprietary managed APIs that have no portable equivalent. What lock-in awareness should architects apply?
• An air-gapped utilities operations network needs OT analytics that cannot reach the public internet. What cloud-chapter conclusion is appropriate?
• Data scientists want to try new Spark job ideas without risking the production civic lake. Which cloud practice best fits that need?
• Staff across departments need access to cloud analytics workspaces without a separate password vault for every tool. What foundation should the city prioritize?
• Parks and transit both run Spark jobs on the same cloud account, and finance wants each department to see its share. Which practice supports that visibility?
• A public-health adjacent dataset will land in the city’s cloud lake. Beyond ordinary open-data rules, what design factor should influence the cloud Big Data layout?
• A city must move its on-prem Kafka and Spark stack to the cloud. What contrast captures the main migration-style choice?
• After moving HDFS, Spark, and Kafka-style components into a public cloud, a trainee asks whether BDPC concepts still apply. What is the best response?