A would instead validate the other design where an analytics team wants hierarchical namespace operations for big-data processing on object storage. That evidence is consistent with enable Azure Data Lake Storage Gen2 hierarchical namespace on a suitable storage account, because a hierarchical namespace supports directory-oriented analytics workloads and atomic rename semantics. It does not demonstrate that the target case achieves an archived object must be rehydrated before normal online access.

C would instead validate the other design where a latency-sensitive object application needs high transaction rates for supported small-blob operations. That evidence is consistent with evaluate premium block blob storage after benchmarking the workload, because premium block blobs offer SSD-backed storage performance for qualifying request patterns. It does not demonstrate that the target case achieves an archived object must be rehydrated before normal online access.

D would instead validate the other design where a media business needs scalable object storage for photos and videos accessed over HTTPS. That evidence is consistent with use Azure Blob Storage for the media objects, because object storage is optimized for large unstructured content and REST access. It does not demonstrate that the target case achieves an archived object must be rehydrated before normal online access.

“Keep those blob objects in the Hot access tier” relies on this Azure capability: hot favors frequent access over the lowest storage charge. This workload involves An analytics team wants hierarchical namespace operations for big-data processing on object storage. The decisive Azure design mechanism is: a hierarchical namespace supports directory-oriented analytics workloads and atomic rename semantics. Thus “Enable Azure Data Lake Storage Gen2 hierarchical namespace on a suitable storage account” is the applicable architecture choice.

“Choose Azure Cosmos DB for NoSQL with a suitable partition key” relies on this Azure capability: cosmos DB for NoSQL is a managed distributed document store with configurable consistency. This workload involves An analytics team wants hierarchical namespace operations for big-data processing on object storage. The decisive Azure design mechanism is: a hierarchical namespace supports directory-oriented analytics workloads and atomic rename semantics. Thus “Enable Azure Data Lake Storage Gen2 hierarchical namespace on a suitable storage account” is the applicable architecture choice.

“Evaluate premium block blob storage after benchmarking the workload” relies on this Azure capability: premium block blobs offer SSD-backed storage performance for qualifying request patterns. This workload involves An analytics team wants hierarchical namespace operations for big-data processing on object storage. The decisive Azure design mechanism is: a hierarchical namespace supports directory-oriented analytics workloads and atomic rename semantics. Thus “Enable Azure Data Lake Storage Gen2 hierarchical namespace on a suitable storage account” is the applicable architecture choice.

A would instead validate the other design where a news website serves recently uploaded pictures repeatedly throughout each day. That evidence is consistent with keep those blob objects in the Hot access tier, because hot favors frequent access over the lowest storage charge. It does not demonstrate that the target case achieves directory moves and analytics reads work through the expected ADLS Gen2 interface.

B would instead validate the other design where a globally used mobile application stores variable JSON documents and needs low-latency partitioned operations. That evidence is consistent with choose Azure Cosmos DB for NoSQL with a suitable partition key, because cosmos DB for NoSQL is a managed distributed document store with configurable consistency. It does not demonstrate that the target case achieves directory moves and analytics reads work through the expected ADLS Gen2 interface.

C would instead validate the other design where a latency-sensitive object application needs high transaction rates for supported small-blob operations. That evidence is consistent with evaluate premium block blob storage after benchmarking the workload, because premium block blobs offer SSD-backed storage performance for qualifying request patterns. It does not demonstrate that the target case achieves directory moves and analytics reads work through the expected ADLS Gen2 interface.

“Evaluate Azure NetApp Files NFS volumes for supported network and region” relies on this Azure capability: azure NetApp Files provides managed performance-oriented NFS shares. This workload involves An enterprise architecture assessment records: A latency-sensitive object application needs high transaction rates for supported small-blob operations. The decisive Azure design mechanism is: premium block blobs offer SSD-backed storage performance for qualifying request patterns. Thus “Evaluate premium block blob storage after benchmarking the workload” is the applicable architecture choice.

“Keep those blob objects in the Hot access tier” relies on this Azure capability: hot favors frequent access over the lowest storage charge. This workload involves An enterprise architecture assessment records: A latency-sensitive object application needs high transaction rates for supported small-blob operations. The decisive Azure design mechanism is: premium block blobs offer SSD-backed storage performance for qualifying request patterns. Thus “Evaluate premium block blob storage after benchmarking the workload” is the applicable architecture choice.

“Move eligible blobs to an infrequent-access online tier such as Cool” relies on this Azure capability: cool can reduce storage costs when reads are uncommon and minimum-retention constraints are met. This workload involves An enterprise architecture assessment records: A latency-sensitive object application needs high transaction rates for supported small-blob operations. The decisive Azure design mechanism is: premium block blobs offer SSD-backed storage performance for qualifying request patterns. Thus “Evaluate premium block blob storage after benchmarking the workload” is the applicable architecture choice.

A would instead validate the other design where a high-performance Linux workload needs enterprise NFS file shares with predictable throughput. That evidence is consistent with evaluate Azure NetApp Files NFS volumes for supported network and region, because azure NetApp Files provides managed performance-oriented NFS shares. It does not demonstrate that the target case achieves measured request latency meets the required IO service target.

C would instead validate the other design where a legal team retains case documents that are seldom read but may be needed online within seconds. That evidence is consistent with move eligible blobs to an infrequent-access online tier such as Cool, because cool can reduce storage costs when reads are uncommon and minimum-retention constraints are met. It does not demonstrate that the target case achieves measured request latency meets the required IO service target.

D would instead validate the other design where a news website serves recently uploaded pictures repeatedly throughout each day. That evidence is consistent with keep those blob objects in the Hot access tier, because hot favors frequent access over the lowest storage charge. It does not demonstrate that the target case achieves measured request latency meets the required IO service target.

“Select read-access geo-zone-redundant storage if available for the service and region” relies on this Azure capability: rA-GZRS combines zone redundancy with asynchronous read-access regional replication. This workload involves A cloud migration design must satisfy the following: A company must protect storage against one availability-zone failure without replicating outside the primary region. The decisive Azure design mechanism is: zRS synchronously replicates across availability zones within one region. Thus “Choose zone-redundant storage in a region that supports ZRS” is the applicable architecture choice.

“Choose geo-redundant storage for an eligible account” relies on this Azure capability: gRS replicates data to a secondary region asynchronously. This workload involves A cloud migration design must satisfy the following: A company must protect storage against one availability-zone failure without replicating outside the primary region. The decisive Azure design mechanism is: zRS synchronously replicates across availability zones within one region. Thus “Choose zone-redundant storage in a region that supports ZRS” is the applicable architecture choice.

“Attach an appropriate Azure managed disk to the virtual machine” relies on this Azure capability: managed disks present persistent block storage to VMs. This workload involves A cloud migration design must satisfy the following: A company must protect storage against one availability-zone failure without replicating outside the primary region. The decisive Azure design mechanism is: zRS synchronously replicates across availability zones within one region. Thus “Choose zone-redundant storage in a region that supports ZRS” is the applicable architecture choice.

A would instead validate the other design where a reporting solution needs both multi-zone primary durability and reads from a secondary region when supported. That evidence is consistent with select read-access geo-zone-redundant storage if available for the service and region, because rA-GZRS combines zone redundancy with asynchronous read-access regional replication. It does not demonstrate that the target case achieves simulated loss of one zone leaves stored data available through the storage endpoint.

B would instead validate the other design where a media company needs a secondary regional copy of blob data but does not require secondary reads before failover. That evidence is consistent with choose geo-redundant storage for an eligible account, because gRS replicates data to a secondary region asynchronously. It does not demonstrate that the target case achieves simulated loss of one zone leaves stored data available through the storage endpoint.

C would instead validate the other design where a virtual machine application requires a block device attached as a data volume. That evidence is consistent with attach an appropriate Azure managed disk to the virtual machine, because managed disks present persistent block storage to VMs. It does not demonstrate that the target case achieves simulated loss of one zone leaves stored data available through the storage endpoint.

“Select read-access geo-zone-redundant storage if available for the service and region” relies on this Azure capability: rA-GZRS combines zone redundancy with asynchronous read-access regional replication. This workload involves A media company needs a secondary regional copy of blob data but does not require secondary reads before failover. The decisive Azure design mechanism is: gRS replicates data to a secondary region asynchronously. Thus “Choose geo-redundant storage for an eligible account” is the applicable architecture choice.

“Evaluate Azure Cosmos DB for MongoDB against required feature compatibility” relies on this Azure capability: the compatible API can preserve supported MongoDB client interactions. This workload involves A media company needs a secondary regional copy of blob data but does not require secondary reads before failover. The decisive Azure design mechanism is: gRS replicates data to a secondary region asynchronously. Thus “Choose geo-redundant storage for an eligible account” is the applicable architecture choice.

“Configure immutable Azure Blob Storage retention policies on the appropriate scope” relies on this Azure capability: wORM immutability enforces governed retention of supported blob content. This workload involves A media company needs a secondary regional copy of blob data but does not require secondary reads before failover. The decisive Azure design mechanism is: gRS replicates data to a secondary region asynchronously. Thus “Choose geo-redundant storage for an eligible account” is the applicable architecture choice.

A would instead validate the other design where a compliance team must prevent deletion or modification of protected archived objects for a fixed retention period. That evidence is consistent with configure immutable Azure Blob Storage retention policies on the appropriate scope, because wORM immutability enforces governed retention of supported blob content. It does not demonstrate that the target case achieves account replication status shows the configured regional redundancy.

C would instead validate the other design where a vendor's document application already uses MongoDB drivers and depends on a supported MongoDB API. That evidence is consistent with evaluate Azure Cosmos DB for MongoDB against required feature compatibility, because the compatible API can preserve supported MongoDB client interactions. It does not demonstrate that the target case achieves account replication status shows the configured regional redundancy.

D would instead validate the other design where a reporting solution needs both multi-zone primary durability and reads from a secondary region when supported. That evidence is consistent with select read-access geo-zone-redundant storage if available for the service and region, because rA-GZRS combines zone redundancy with asynchronous read-access regional replication. It does not demonstrate that the target case achieves account replication status shows the configured regional redundancy.

“Keep those blob objects in the Hot access tier” relies on this Azure capability: hot favors frequent access over the lowest storage charge. This workload involves An Azure solution needs to solve the following challenge: A reporting solution needs both multi-zone primary durability and reads from a secondary region when supported. The decisive Azure design mechanism is: rA-GZRS combines zone redundancy with asynchronous read-access regional replication. Thus “Select read-access geo-zone-redundant storage if available for the service and region” is the applicable architecture choice.

“Choose zone-redundant storage in a region that supports ZRS” relies on this Azure capability: zRS synchronously replicates across availability zones within one region. This workload involves An Azure solution needs to solve the following challenge: A reporting solution needs both multi-zone primary durability and reads from a secondary region when supported. The decisive Azure design mechanism is: rA-GZRS combines zone redundancy with asynchronous read-access regional replication. Thus “Select read-access geo-zone-redundant storage if available for the service and region” is the applicable architecture choice.

“Configure immutable Azure Blob Storage retention policies on the appropriate scope” relies on this Azure capability: wORM immutability enforces governed retention of supported blob content. This workload involves An Azure solution needs to solve the following challenge: A reporting solution needs both multi-zone primary durability and reads from a secondary region when supported. The decisive Azure design mechanism is: rA-GZRS combines zone redundancy with asynchronous read-access regional replication. Thus “Select read-access geo-zone-redundant storage if available for the service and region” is the applicable architecture choice.

A would instead validate the other design where a news website serves recently uploaded pictures repeatedly throughout each day. That evidence is consistent with keep those blob objects in the Hot access tier, because hot favors frequent access over the lowest storage charge. It does not demonstrate that the target case achieves read operations against the supported secondary endpoint succeed.

B would instead validate the other design where a company must protect storage against one availability-zone failure without replicating outside the primary region. That evidence is consistent with choose zone-redundant storage in a region that supports ZRS, because zRS synchronously replicates across availability zones within one region. It does not demonstrate that the target case achieves read operations against the supported secondary endpoint succeed.

C would instead validate the other design where a compliance team must prevent deletion or modification of protected archived objects for a fixed retention period. That evidence is consistent with configure immutable Azure Blob Storage retention policies on the appropriate scope, because wORM immutability enforces governed retention of supported blob content. It does not demonstrate that the target case achieves read operations against the supported secondary endpoint succeed.