How Mobile Cloud Earned Top‑Tier AIOps Certification and What It Means for Intelligent Operations

Intelligent Operations (AIOps) applies AI techniques such as machine learning to IT operations, enhancing monitoring, fault prediction, root‑cause analysis, and maintenance strategy optimization, thereby improving system stability, efficiency, and cost.

On December 15, 2023, the GOLF+ IT New Governance Leadership Forum in Beijing announced that China Academy of Information and Communications Technology (CAICT) released the latest evaluation results for DevOps and AIOps standards.

China Mobile Suzhou Software Technology Co., Ltd. (Mobile Cloud) submitted its "Mobile Cloud Smart Operations Platform (CC‑OPS) Intelligent Operations Capability Construction Project" and passed the CAICT "Cloud Computing Intelligent Operations (AIOps) Capability Maturity Model – Part 1: General Capability Requirements" Level‑3 assessment for anomaly detection and alarm convergence, marking a domestic leading level.

Mobile Cloud has thus completed two CAICT AIOps standard assessments: one for general capability requirements and one for system and tool technical requirements.

Q: Please introduce your company and the project you evaluated. A: Mobile Cloud, a wholly‑owned subsidiary of China Mobile with over 4,000 staff, focuses on cloud services, R&D, and integrated operation support. The evaluated project targets the "Smart Operations (AIOps) Capability Maturity Model – General Capability" scenario, leveraging operational data and AI algorithms to digitize and boost operational efficiency.

Q: How do you feel after passing the CAICT AIOps assessment? A: AIOps is the future of operations; the maturity standard provides a clear implementation path, accelerates digital transformation, and validates our intelligent operations system as the first cloud service provider to achieve Level‑3, demonstrating technical leadership.

Q: What considerations guided your participation in the assessment? A: We aimed to validate our AIOps capabilities, drive continuous improvement, and exchange ideas with industry experts, especially exploring large‑model applications for cost reduction and efficiency gains.

Q: What changes has the assessment brought to your team? A: It confirmed our architecture aligns with industry trends, generated best‑practice experience for future platform evolution, and enhanced team skills and confidence in intelligent operations.

Q: What are the key features of the evaluated IT system? A: The Smart Operations Platform follows a three‑layer architecture: acquisition/control, service, and application layers. It supports large‑scale resource management, high‑concurrency interfaces, and complex operational scenarios, delivering AIOps functions such as single/multi‑metric anomaly detection, text and topology‑based alarm convergence, log anomaly detection, and dynamic baselines.

Q: Was the assessment process smooth? Any difficulties? A: The on‑site evaluation was smooth thanks to early planning and cross‑department support. Multi‑scenario alarm convergence required close collaboration among alarm, fault, topology, and algorithm teams, ultimately simplifying alarm rules and speeding root‑cause identification.

Q: What are your next steps for AIOps? A: We will expand intelligent capabilities to cost, efficiency, and security scenarios, and actively explore large‑model applications to provide high‑quality, high‑efficiency operational support.

Q: What is your view on the future of AIOps? A: Future AIOps will hinge on integrating operational large models with knowledge graphs to improve alarm aggregation, fault root‑cause recommendation, log analysis, and ChatOps, ultimately achieving advanced intelligent operation driving.

The article also presents industry statistics: as of December 15, 2023, four enterprises have passed seven AIOps general‑capability assessments, and nineteen enterprises have passed thirty‑eight system‑and‑tool assessments across banking, securities, and communications sectors.