Supporting deployments that distribute data across different geographical zones.
B.
Supporting deployments that require strong consistency across geographical zones.
C.
Supporting deployments with very large data sets and high throughput operations.
D.
Supporting deployments where datasets fit into RAM and performance needs are met.
E.
Supporting deployments that require redundancy and increased data availability.
The Answer Is:
A, C
This question includes an explanation.
Explanation:
Sharding is MongoDB ' s horizontal-scaling mechanism: it partitions a collection ' s data across multiple shards so a deployment can scale storage capacity and distribute query or write workload beyond the limits of one server. That directly supports deployments with very large datasets and high-throughput operations, making C correct. MongoDB also supports zone sharding, which associates ranges of shard-key values with selected shards. Zones can be used to keep particular data near a geographical region, satisfy locality requirements, or map data ranges to hardware tiers, so A is also correct. Option B overstates what sharding itself provides; cross-region consistency behavior depends on replication topology, read/write concerns, latency, and application design rather than simply enabling sharding. Option D describes a deployment that already fits comfortably in memory and meets performance goals, so sharding may add unnecessary operational complexity. Option E primarily describes replication: replica sets maintain redundant copies, provide elections, and improve availability. Production shards are themselves normally replica sets, but redundancy is a replication function rather than the defining purpose of sharding. Therefore the two functions represented here are geographic zone distribution and horizontal scale: A and C.
Study Guide reference/topic:Sharding Strategies and Scalable Deployments - horizontal scaling, large datasets, throughput, shard keys, and zone sharding.
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