Customer background

Wangxiaobao is an innovative company deeply engaged in intelligent AI sales scenarios. It is one of the few technology companies in China's high-per-transaction industry with "AIOT + big data + delivery results," and a leader in the AIS (AIS) sector for new real estate sales.

Previously, Wangxiaobao used open-source monitoring software designed for specific monitoring needs. With the development of innovative AI scenarios, monitoring needs are gradually covering complex environments, cross-cloud resources, and core business processes.

If isolated monitoring systems continue to be used, teams will be affected in problem perception, localization, and cost control in large-scale, complex environments.

Surveillance systems are fragmented and struggle to support complex scenarios

Original open-source monitoring software solved local data monitoring issues but lacked a unified entry point for multi-cloud, complex environments, and cross-business chain inspections.

Fault detection and localization rely on human experience

Fault information is scattered across different systems, cross-departmental information is not shared, and command and risk response in major scenarios lack unified data support.

Maintenance costs and alarm noise affect operational investment

Multiple tools running in parallel brings maintenance costs, frequent alarms and false alarms, and operations teams need to invest significant time dealing with low-value noise.

Solutions

Breaking down data silos and building a unified monitoring system

Deploy DataKit collectors to achieve full-stack data collection, establish unified tag standards, and connect data associations.

All monitoring data is retrieved, correlegated, and visualized on a single platform, allowing teams to analyze issues around a unified context.

Simplifying complexity to achieve unified management and control of multi-cloud environments

Deploying DataKit in multi-cloud environments automatically discovers existing computing resources, provides cross-cloud resource topologies, and displays health status and dependencies in real time.

Teams can drill down with one click, unify management and monitoring configurations, and reduce cross-platform switching.

Intelligent troubleshooting shortens fault location time

By seamlessly integrating multiple microservices, it automatically maps the call topology and links Trace, logs, and metrics to achieve complete link restoration.

Guance helps teams automatically identify fault boundaries, improving alarm accuracy and fault localization efficiency.

Customer outcomes

Improved Fault Location Efficiency:

By unifying dashboards and the operations team, a god's-eye view of system health status was achieved, reducing fault detection time from 30 minutes to 5 minutes and improving problem localization efficiency by at least 50%.

Improved alert accuracy, freeing up operations and maintenance manpower:

With intelligent noise reduction and alarm aggregation, the proportion of invalid alarms has significantly decreased, while the proportion of effective alerts has increased, greatly shortening the monthly alert handling time for operations teams.

Reduced monitoring costs and more rational resource allocation:

By significantly reducing self-built monitoring server resources and operational labor costs, teams can focus their efforts on higher-value stability development.

Controllable multi-cloud architecture supports business expansion:

Cross-cloud resource topology and unified monitoring systems make the status of cloud resources clear at a glance, providing a more solid technical foundation for future business expansion.

Bring prosperity to Xiaobao Guance