Memory-optimized ECSs are specifically designed for the workload described. Huawei Cloud defines memory-optimized ECSs as instances that excel at processing large in-memory datasets and high-throughput networking . They are intended for memory-intensive workloads involving large datasets, frequent or heavy data access, and requirements for rapid data processing and exchange.
The scenario deliberately combines several identifying characteristics: large-memory datasets, substantial data volumes, high numbers of access requests, demanding network performance, and rapid data transfer and processing. These characteristics correspond directly to the design profile of the memory-optimized ECS family. Huawei lists representative applications such as high-performance databases, in-memory databases, distributed memory caches, data analysis and mining, Hadoop, Spark, e-commerce, and other enterprise applications.
Ultra-high I/O instances emphasize extremely high storage IOPS and low disk latency. High-performance computing instances are optimized primarily for compute-intensive scientific or engineering workloads. Although “large-memory” may appear plausible, memory-optimized is the ECS category whose official description explicitly combines large in-memory datasets with high-throughput networking and heavy data access.
Therefore, D is the precise Huawei Cloud classification required by the scenario.
Reference topics: ECS Types and Specifications; Memory-Optimized ECSs; Memory-Intensive Workloads; High-Throughput Networking.
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