Download Designing and Implementing an Azure AI Solution.AI-100.PrepAway.2021-05-20.156q.vcex

Data Lake will be a bit more expensive although they are in close range of each other. Blob storage has more options for pricing depending upon things like how frequently you need to access your data (cold vs  hot storage).  Reference: http://bloq.praqmaticworks.com/azure-data-lake-vs-azure-blob-storaqe-in-data-warehousinq

Table Storage is a NoSQL key-value store for rapid development using massive semi-structured datasets You can develop applications on Cosmos DB using popular NoSQL APls.  Both services have a different scenario and pricing model.  While Azure Storage Tables is aimed at high capacity on a single region (optional secondary read only region but no failover), indexing by PK/RK and storage-optimized pricing; Azure Cosmos DB Tables aims for high throughput (single-digit millisecond latency), global distribution (multiple failover), SLA-backed predictive performance with automatic indexing of each attribute/property and a pricing model focused on throughput.  References: https://db-enqines.com/en/svstem/Microsoft+Azure+Cosmos+DB%3BMicrosoft+Azure+Table+Storaqe

References: https://docs.microsoft.com/en-us/azure/architecture/data-quide/technologv—choices/data—storaqe

References: https://qithub.com/MicrosoftDocs/azure-docs/blob/master/articles/machine-learning/studio/alqorithm-choice.md

B: To keep up with application demands in Azure Kubernetes Service (AKS), you may need to adjust the number of nodes that run your workloads. The cluster autoscaler component can watch for pods in your cluster that can't be scheduled because of resource constraints. When issues are detected, the number of nodes is increased to meet the application demand. Nodes are also regularly checked for a lack of running pods, with the number of nodes then decreased as needed. This ability to automatically scale up or down the number of nodes in your AKS cluster lets you run an efficient, cost-effective cluster.  A: You can also use the horizontal pod autoscaler to automatically adjust the number of pods that run your application.  Reference: httlos://docs.microsoft.com/en-us/azure/aks/cluster-autoscaler

FPGAs, such as those available on Azure, provide performance close to ASICs. They are also flexible and reconfigurable over time, to implement new logic.  Incorrect Answers: D: ASICs are custom circuits, such as Google's TensorFlow Processor Units (TPU), provide the highest efficiency. They can't be reconfigured as your needs change.  References: httos://docs.microsoft.com/en-us/azure/m achine-Iearnind/service/concept-accelerate-with-qas

An AKS cluster has one or more nodes.  References: https://docs.microsoft.com/en-us/azure/aks/concepts-clusters-workloads

Azure HDInsight makes it easy, fast, and cost-effective to process massive amounts of data.  You can use HDInsight to process streaming data that's received in real time from a variety of devices.  References: https://docs.microsoft.com/en-us/azure/hdinsiqht/hadoop/apache-hadoop-introduction

Throughput provisioned for a container is divided evenly among physical partitions.  Incorrect: Not A: Increasing request units would also improve throughput, but at a cost. Reference: httbs://docs.microsoft.com/en-us/azure/architecture/best-practices/data—partitioni_ng