How Intelligent Operations Are Redefining IT Management – Key Takeaways from the 2021 GOPS Conference

Recently, the 2021 16th GOPS Global Operations Conference, guided by the Cloud Computing Open Source Industry Alliance and co‑hosted by the Efficient Operations Community and Open Operations Alliance, was held in Shenzhen, where Qingchuang Technology shared insights on intelligent operations, practicality, and usability.

In the AIOps Best Practices session, Qingchuang CEO Yang Chen and Professor Wang Peng from Fudan University presented progressive approaches to building intelligent operations and explored ways to improve its practicality and ease of use, offering constructive solutions to common challenges.

As a crucial element of digital transformation, IT operations efficiency directly impacts business continuity; the surge in digital business creates severe operational challenges, making problem detection, root‑cause analysis, data governance, and operational analytics increasingly difficult.

Yang Chen emphasized that moving from traditional to intelligent operations is essentially a digitization process: first describing existing processes digitally, then creating data‑driven operational scenarios.

He highlighted that a middle‑platform capability is key to operational digitization. Qingchuang’s self‑developed Digital Operations Platform provides data governance, stream‑batch integration, and AI services, leveraging massive data processing and strong algorithm support to enable flexible, diverse intelligent operation scenarios and continuously improve data quality.

Regarding the order of building platforms versus scenarios, enterprises with clear data visibility may prioritize platform construction, while those focused on immediate business value may start with scenario development.

Qingchuang proposes a "three principles, six steps" best‑practice framework: first enhance real‑time data processing through intelligent monitoring, metric monitoring, and log anomaly detection; then improve post‑event analysis via intelligent fault diagnosis, knowledge management (knowledge graph), and self‑healing.

Four major capabilities that boost the practicality and usability of intelligent operations:

Algorithm capability: provide algorithms such as anomaly detection, log clustering, and root‑cause localization for different operational scenarios.

Heterogeneous data management: unified handling of large‑scale time‑series, log/alert text, graph, and structured data.

Data semantic fusion: achieve entity matching, association, and feature linking across multiple data sources.

Data exploration: unified queries and semantic queries across heterogeneous data.

These capabilities enable unified data management and semantic‑level fusion, allowing cross‑source queries and more effective algorithm design, testing, and application, while emphasizing the importance of data exploration.

With fully utilized operational data, enterprises can better uncover insights, simplify troubleshooting for operators, and ultimately enhance operational efficiency and maturity.

Qingchuang, as a strategic partner for digital and intelligent transformation, has applied AIOps solutions across banking, securities, insurance, transportation, and energy sectors, and will continue to build practical, intelligent tools based on its "three principles, six steps" methodology to serve more enterprise customers.