IDC | China CWPP Market Share Report 2024 Released
Key Trends and Vendor Landscape in Focus
Beijing, June 17, 2025
International Data Corporation (IDC) has officially released two research reports on cloud workload security market share: "IDC China AI-Enabled Public Cloud Workload Security Market Share, 2024: CNAPP to Become Standard for Cloud Security" 《IDC 中国AI赋能的公有云云工作负载安全市场份额，2024：CNAPP将成为云安全标配》(Doc# CHC53545325, June 2025) and "IDC China AI-Enabled Private Cloud Workload Security Market Share, 2024: Automation, Intelligence, and Cloud-Native Become Main Themes" 《IDC 中国AI赋能的私有云云工作负载安全市场份额，2024：自动化、智能化、云原生化成为主旋律》(Doc# CHC53545225, June 2025). The reports provide detailed analyses of the 2024 Chinese public cloud and private cloud workload security markets, covering market size, growth rates, key players, and trends in market and technology development.
IDC data shows that China's public cloud workload security market achieved a year-on-year growth of 17.1% in 2024, reaching a market size of 1.16 billion RMB. In terms of market share, major players include Alibaba Cloud, Tencent Cloud, China Mobile, Huawei Cloud, Baidu, and others. For details, please refer to the chart below:
The Chinese private cloud workload security market showed a year-on-year negative growth of -3.3% in 2024, with a market size reaching 1.48 billion RMB. In terms of the competitive landscape, major players in this market include Qingteng, QAX, Asiainfo, Huawei Cloud, and Alibaba Cloud. For details, please refer to the figure below:
IDC believes that technology service providers should focus on the following trends:
Artificial intelligence has further deepened its application in cloud workload security products, with large security models rapidly developing in the cybersecurity field. The integration of Generative AI (GenAI) helps systems perform in-depth correlation analysis of security data, effectively improving alert noise reduction capabilities, automatically generating remediation suggestions, and combining with playbooks for automated execution of responses. This reduces manual intervention, enhances operational efficiency, and achieves the transformation of cybersecurity from "passive post-event response" to "proactive pre-event defence."
Unified management capabilities for multi-cloud and hybrid cloud workload security. Enterprises aim to achieve unified management of all workloads across multi-cloud and hybrid cloud environments through a single management control platform, thereby reducing security operation complexity while enhancing the consistency of asset management and security policies.
The proportion of container security requirements is gradually increasing, with serverless gaining attention. Modern application development requires the capability to continuously ensure application security, vulnerability assessment, and configuration checks during development, deployment, and runtime. With the widespread adoption of containers and serverless technologies, enterprises are placing greater emphasis on container security, while agentless and sidecar deployment models are experiencing rapid development.
CNAPP helps enterprises build comprehensive cloud-native security protection. Integrating the combined capabilities of CWPP, CSPM, and CIEM, CNAPP consolidates multiple cloud-native application protection functions. It provides full lifecycle security protection for cloud-native applications from development to production through unified and tightly integrated security and compliance features, enabling security shift-left.
Analyst Views
Zhao Weijing, Senior Research Manager of IDC China's Cybersecurity Market, stated that due to the unique development of the cloud computing and cybersecurity markets, the main players in China's cloud workload security market for public and private cloud scenarios have formed distinct camps. Public cloud providers and specialised security vendors each demonstrate their respective technical and service advantages. Market demand for Cloud-Native Application Protection Platforms (CNAPP), container security, and agentless models has significantly increased. In the future, as AI/GenAI applications in products deepen further, system detection, analysis, and response capabilities will be substantially enhanced, thereby improving operational efficiency.
