IoT Cloud Infrastructure

Huawei offers a wide range of cloud services, including an IoT platform and big data, security, management, and application services. These services accelerate IoT-based innovation for a variety of industries.
Solution Advantages
  • Scenario-based Solutions

    Pre-integrated and highly adaptable solutions for connected car, public utilities, and predictive maintenance applications

  • Easy Device Access

    Smooth device-platform communication via IoT Agents and OSGi-based cloud inter-networking gateways (CIGs)

  • Easily Obtained Data Insights

    Value-enhancing E2E data processing capabilities, such as data injection, real-time processing, analysis, and mining

  • Extended Ecosystem

    Extensive IoT application ecosystem with pre-integrated modules and devices from leading IoT vendors

Business Challenges
  • Concurrent Access Support

    Sensor and device data collection is the first step in digitizing IoT; however, diversified protocols complicate access. For massive amounts of collected data to be reported quickly to the cloud, the platform itself must possess high-concurrency processing capabilities.

  • Data Insight Extraction

    IoT processes massive amounts of diverse data from various systems. This poses the challenge of efficient data processing and analysis to improve operational efficiency and help create new services and business models.

  • Lack of App-enabling Tools

    As IoT continues being applied to traditional industries not adequately equipped with IT capabilities, the lack of IoT enablement tools is an obstacle. Instead of focusing on service innovation, customers are forced to invest resources in infrastructure development, resulting in slow service rollouts and market opportunity losses.

  • Security and O&M Efficiency

    Despite being more complex, IoT networks face major security threats, making it imperative to implement reliable network and data security measures. Due to the rudimentary nature of current monitoring, logging, and data security measures, as well as limited third-party compatibility, it is also difficult to offer efficient O&M.

Typical Scenarios
  • Massive Number of IoT Connections

  • Full-Stack Big Data Analysis

  • Diversified App Enablement

  • E2E Security and O&M

Massive Number of IoT Connections

Two options are available to help customers support up to hundreds of millions of IoT connections.

  1. Option 1: Creating a Connection Processing Module on the IoT Platform

    Applies to one-stop pre-integration service scenarios. The customer can create a connection processing module to quickly integrate multiple devices, support the smooth expansion of hundreds of millions of connections, and implement an O&M-free platform.

  2. Option 2: Deploying and Migrating an Existing IoT Connection Processing Module on Basic Cloud Services

    Applies to scenarios in which a customer has already developed an IoT connection processing module. The customer can use a series of basic cloud services provided by HUAWEI CLOUD, such as ECS, CCE, ELB, DMS, and DDS, to deploy the existing module on the cloud.

  3. Related Services

    IoT Platform

    Elastic Cloud Server

    Cloud Container Engine

    Elastic Load Balance

    Distributed Message Service

    Document Database Service

Full-Stack Big Data Analysis

The reference architecture of IoT big data can be unified to help customers quickly gain insights into IoT data.

  1. E2E Process

    E2E IoT data processing capabilities include data injection, real-time processing, storage, analysis and calculation, and mining and presentation.

  2. Scenario-based Design

    Cloud services required for different IoT scenarios are provided, including CS for SQL queries, MLS for preventive maintenance modeling, and CloudTable for time series data.

  3. Cost-effectiveness

    The most suitable data storage, query, and analysis architectures and solutions are matched according to specific customer requirements. For example, decoupling of computing and storage for non-real-time services can be provided to reduce big data analysis costs.

  4. Related Services

    Data Ingestion Service

    Cloud Stream Service

    MapReduce Service

    Machine Learning Service

    Data Lake Insight

Diversified App Enablement

Rich infrastructure as a service (IaaS) and platform as a service (PaaS) layer services facilitate quick creation of IoT applications.

  1. Basic Scenarios

    ECS and CCE are used to implement bearer and horizontal expansion of application clusters.

  2. Intermediate Scenarios

    Highly scalable and reliable middleware services are used to reduce the burden on O&M. Middleware services commonly used in IoT scenarios include RDS, DDS, DCS, and DMS.

  3. Advanced Scenarios

    Services such as FunctionStage, ServiceStage, and DevCloud are used, allowing customers to focus on business innovation.

  4. Related Services

    Elastic Cloud Server

    Cloud Container Engine

    Distributed Message Service

    Document Database Service



E2E Security and O&M

Secure cloud management services support efficient IoT application O&M.

  1. Management and Deployment Services

    Services include core O&M services such as Cloud Eye, LTS, and CTS.

  2. Security Services

    DEW encrypts data in block storage and object storage, ensuring the security of IoT data on the cloud. Anti-DDoS and WAF ensure the security of IoT access networks and hosts.

  3. Compatible with Leading Automation Platforms

    OpenStack architecture enables compatibility with leading automation platforms (such as Cloud Foundry and Terraform) for easy deployment of applications on HUAWEI CLOUD.

  4. Related Services

    Data Encryption Workshop

    Cloud Eye

    Log Tank Service

    Cloud Trace Service

    Web Application Firewall


Solution Architectures


Huawei offers a wide range of cloud services, including an IoT platform and big data, security, management, and application services.


  • One-stop cloud service combinations
  • IoT scenario–oriented optimization
  • Flexible architecture options
  • Well-developed IoT ecosystem
  • Pre-integrated scenario-specific solutions
  • Cloud-pipe-device synergy
Recommended Services
  • IoT Platform
    IoT Platform connects millions of IoT devices, delivers commands to them, and collects device data, facilitating device management.
  • Machine Learning Service
    Machine Learning Service (MLS) enables users to quickly discover data rules, build a prediction model, and deploy a prediction analysis solution.
  • Cloud Stream Service
    Cloud Stream Service (CS) fully manages computing clusters, enabling users to focus only on Stream SQL services. CS is compatible with Apache Flink APIs, and CS jobs run in real time.

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