How Migu’s Cloud Gaming Platform Achieved Leading AIOps Observability Standards

In the context of rapidly growing IT complexity, AIOps has become essential for enterprises to manage physical devices, iterate quickly, and ensure business continuity, as highlighted in national policies such as the "14th Five-Year Plan" and related emergency system plans.

On October 18, 2024, at the 24th GOPS Global Operations Conference in Shanghai, the China Academy of Information and Communications Technology announced the dual certification results of the ITU AIOps international standard and the domestic AIOps standard.

Migu Interactive Entertainment Co., Ltd. participated with the "Migu Fast Game Intelligent Operations Observability Project", which passed both the ITU AIOps international assessment and the domestic "Observability Capability Level 3" assessment, demonstrating a leading domestic capability.

In an interview, Su Yi, Deputy General Manager of Migu Interactive Entertainment, explained that Migu Fast Game leverages 5G, cloud computing, blockchain, and artificial intelligence to provide a cloud gaming platform, and has built an observability system covering client‑server data collection, user‑experience monitoring, end‑to‑end performance analysis, full‑stack code profiling, system optimization, anomaly detection, and alarm‑noise reduction.

The observability system correlates logs, metrics, traces, and events, performs deep metric perspective and topology analysis, and provides real‑time technical support for production environments, laying a solid foundation for interactive, intelligent, and convenient digital product experiences.

Su Yi emphasized that observability is crucial for business continuity in highly distributed and dynamically changing systems. He described challenges such as monitoring blind spots, complex inter‑service dependencies, and manual operation processes, and explained how Migu addressed them by standardizing data collection, deploying distributed tracing, expanding monitoring coverage, and fostering an observability culture through regular training and knowledge sharing.

Future plans include finer‑grained monitoring, AI‑driven predictive analysis, expanded user‑experience observability, and broader organizational adoption of observability practices to create a shared observability culture across departments.

The article also presents statistics of enterprises that have completed the AIOps maturity assessments and outlines the three parts of the AIOps capability maturity model: general capabilities, system & tool requirements, and observability requirements.