Updated on 2025-08-07 GMT+08:00

Selecting ECS Specifications

Scenarios

Huawei Cloud provides various ECS specifications to meet different service needs. Different types of ECSs provide different computing and storage capabilities. For the same ECS type, you can select different ECS specifications based on the number of vCPUs and memory size.

This section describes how to select ECSs suitable for your service requirements.

Specifications

  1. To learn details about the available ECS specifications, see A Summary List of x86 ECS Specifications.
  2. To learn how ECS flavors are named, see ECS Flavor Naming Rules.
  3. To learn more about common metrics, see vCPUs and network QoS.

Specification Selection

  • By type

    View the ECS specification details to learn about the major ECS types, computing and network performance, and supported disk types. You can select ECS specifications based on different properties. ECS supports the following CPU architectures: x86 and Kunpeng. For details, see x86 and Kunpeng Architectures.

    This section is intended for users who are familiar with the CPU architecture, vCPUs, memory, and instance family and generation of ECSs and want to select specific specifications.

    x86 ECSs

    Kunpeng ECSs

    On the ECS purchase page, you can select an ECS by specifying its vCPUs, memory, or flavor name.

  • By scenario

    This section is intended for users who have specific service requirements.

    Category

    Sub-category

    Characteristics

    Recommended ECS (Example)

    Web applications

    Traditional office

    High security and reliability, suitable for traditional office scenarios like OA, ERP, and CRM with less than 200 concurrent access requests

    C7 and C6

    Enterprise websites

    A balance of compute, memory, and network resources with a baseline level of vCPU performance and high cost-effectiveness

    • C7 and C6
    • S7 and S6

    Personal application setup

    A balance of compute, memory, and network resources with a baseline level of vCPU performance and high cost-effectiveness

    • S7 and S6
    • T6

    Development and testing

    A balance of compute, memory, and network resources with a baseline level of vCPU performance and the ability to provide burst CPU power at any time for as long as required

    S7 and S6

    Front-end servers

    A balance of compute, memory, and network resources with a baseline level of vCPU performance. These ECSs can be used as front-end servers like Apache, Nginx, and IIS

    S7 and S6

    Back-end servers

    High vCPUs-to-memory ratios, high performance, and low latency These ECSs are cost-effective options for back-end servers like Tomcat and JBoss

    C7, C6, and C6s

    Website applications/E-commerce

    100,000 pageviews/1,000 active users

    Cost-effective, flexible, elastic resources available anytime

    • S7 and S6
    • T6

    200,000 pageviews/2,000 active users

    Suitable for e-commerce websites, which require high-performance cloud servers with fast elasticity and high stability to handle traffic bursts typical of special promotions, flash sales, and live commerce

    • C7, C6, and C6s
    • S7 and S6

    500,000 pageviews/5,000 active users

    Suitable for e-commerce websites, which require high-performance cloud servers with fast elasticity and high stability to handle traffic bursts typical of special promotions, flash sales, and live commerce

    C7, C6, and C6s

    Gaming

    Gaming

    Suitable for gaming services, which require high performance, high stability, high cost-effectiveness, and low latency

    C7, C6, and C6s

    Databases

    Compute

    Stable, high-performance compute

    C7, C6, and C6s

    Storage

    Servers that use local disks with high storage bandwidth and IOPS to provide cost-effective mass data storage

    • M7 and M6
    • D7 and D6

    Network

    High PPS performance, high TPS throughput, and low network latency for rapid data exchange and processing

    • E7 and E6
    • M7 and M6
    • C7, C6, and C6s

    Data analytics

    Management nodes

    A large volume of compute resources scheduled to accelerate data processing

    C7, C6, and C6s

    Compute nodes

    Balanced compute with high performance and stability

    • M7 and M6
    • C7, C6, and C6s
    • I7, Ir7, I3, and Ir3
    • S7 and S6

    Storage nodes

    Cost-effective, high-bandwidth storage for processing large amounts of reads and writes

    • I3 and Ir3
    • D7, D6, and D3

    Image rendering

    Animation rendering

    CPU-accelerated rendering with high precision and stability

    aC7, C6, and C3

    Video rendering

    GPU-accelerated rendering with high processing speed

    G5 and G6

    AI/Machine learning

    AI training

    Compatible with NVIDIA smart NICs for deep learning training, scientific computing, computational fluid dynamics, computational finance, seismic analysis, molecular modeling, and genomics

    P2vs, P2v, and P2s

    AI inference

    Compatible with NVIDIA smart NICs for image classification and recognition, speech recognition, natural language processing, video encoding and decoding, machine learning, and lightweight training

    Pi2

    On the ECS purchase page, you can select specifications based on service scenarios.

  • By pre-installed software

    Select an ECS based on the pre-installed software you need.

    Scenario

    Application

    Requirement

    Recommended ECS (Example)

    Cache

    Redis

    Memcached

    Low CPU computing capability

    Very high memory

    M7 and M6

    Big data

    Spark

    Hive

    High CPU computing capability

    High memory bandwidth

    I/O: high storage bandwidth

    D7i, I7, and D7

    Load balancing

    Nginx

    Very high CPU computing capability

    C7, C6, and X1

    Database

    MySQL

    NoSQL

    Lightweight database

    aC8 and C7

    Real-time computing

    Flink

    You can select general-purpose ECSs or cloud disks based on the storage capacity.

    You can also select disk-intensive ECSs.

    I7 and D7

    Offline computing

    Hadoop

    HDFS

    vCPU to memory ratio: 1:4 (preferred)

    D7i and D7

    Message queue

    Kafka

    RabbitMQ

    vCPU to memory ratio: 1:1

    aC8, C7, and X1

    Text search

    ElasticSearch

    Large vCPU-to-memory ratio

    I7

  • Verification and adjustment

    After selecting an ECS and using it, you can check whether the selected ECS specifications are proper based on performance monitoring of the ECS within a period of time.

    If the CPU usage of the ECS is too low, check whether the memory usage is very high. For details, see Monitoring Using Cloud Eye.

    If the memory usage of the ECS is very high, you can adjust the vCPU-to-memory ratio to an appropriate ratio. For details, see Modifying Specifications of Individual ECSs.

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