Product features
Benefits
1. Fast: Detect issues in seconds and locate them in minutes to accelerate repairs
Real-time full-link monitoring: Collects, scrubs, and analyzes logs and monitoring data in real time using a big data architecture. It detects and reports crashes within seconds.
Dynamic threshold alerting: Uses intelligent baseline detection to meet emergency response needs during critical events, such as new version releases and major sales promotions.
2. Accurate: Pinpoint complex issues with multi-dimensional root cause analysis
In-depth association analysis: Analyzes data across more than 20 dimensions, such as device model, region, and version. It correlates crash, performance, and log data to pinpoint stability issues caused by performance bottlenecks.
Custom monitoring extension: Enables custom exception and data reporting for precise diagnostics across various business scenarios.
3. Stable: Ensure enterprise-grade reliability with high-concurrency validation
Proven at massive scale: The system is tested in environments with hundreds of millions of users and validated by peak traffic during the Double 11 global shopping festival. It supports reporting and analysis of millions of data points per second, which ensures stability for high-concurrency scenarios in finance, IoT, and other industries.
End-to-end closed-loop solution: Integrates crash monitoring, App Performance Analytics, and Remote Log Access. This covers the entire lifecycle from issue discovery to resolution and reduces the inefficiency of switching between tools.
Features
1. Non-intrusive, out-of-the-box SDK integration
EMAS App Monitor features a non-intrusive SDK design that lowers the barrier to entry and improves integration efficiency for developers. You can integrate it quickly with simple configuration and without major changes to your existing code.
2. Full platform coverage and seamless multi-device compatibility
EMAS App Monitor fully supports mainstream mobile operating systems and is deeply optimized for the unique features of each platform. It provides crash capture and performance monitoring for Android, iOS, and HarmonyOS, ensuring consistent and accurate monitoring in complex, multi-device environments.
3. Comprehensive diagnostics and context restoration
Precise context restoration: Captures the complete call stack, memory information, logs, custom data, and user action paths when a crash occurs. It also retrieves client logs to fully reproduce the context of the issue.
Intelligent clustering analysis: Identifies common issue patterns, such as OOM and ANR errors. A unified feature extraction algorithm improves clustering accuracy and simplifies the categorization of complex stacks.
Multi-dimensional root cause analysis: Analyzes data across more than 20 dimensions, such as device model, operating system version, region, network environment, and user properties. This analysis is combined with startup time metrics to quickly locate performance bottlenecks.
Fine-grained sample tracking: Analyzes client feature information and the exception stack for each individual exception. It performs targeted analysis of client logs by user and device to help reproduce rare and intermittent issues.
4. Custom error reporting for complex business scenarios
In addition to general exception capture and analysis, EMAS App Monitor supports custom error reporting. This feature is ideal for monitoring critical paths in complex business scenarios because it helps developers cover potential business issues, such as proactively capturing exceptions in business logic. This lets you discover potential threats early and prevent issues before they occur.
5. Big data distributed architecture for massive-scale processing and dynamic scalability
The system is built on the EMAS big data distributed architecture and includes a real-time data analytics engine that supports hundreds of billions of data records and responds to complex queries in seconds. This engine ensures real-time reporting of core metrics, such as crash rate, ANR, and startup time, while also supporting historical data analysis for up to 90 days.