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eService Intelligent Cloud O&M Platform，Combining big data analytics and Artificial Intelligence (AI), Huawei eService provides data infrastructure — such as Huawei servers and storage devices — with automatic fault reporting, and problem management and tracking.
• Over 80% of disk failure risks are identified 14 days in advance with AI and big data analytics on the cloud.
• A fault model library containing more than 200,000 devices provides troubleshooting for 93% of faults and accelerates fault location.
• Intelligent capacity prediction: capacity consumption is forecasted 12 months in advance.
• 24/7 proactive monitoring and online O&M with fault detection in minutes; risks and failures are reported automatically.
• Monitoring of devices over mobile phone, for system risk prevention and real-time troubleshooting, anytime, anywhere.
• Automatic creation of trouble tickets on the cloud for transparent tracking of problem management.
• eService does not collect customer service data; all operations can be traced, and all logs can be audited.
• Featuring bidirectional authentication (eService client and Huawei cloud), unidirectional access, and encryption during transmission.
• 256-bit Advanced Encryption Standard (AES) algorithm ensures 99.9999% availability and General Data Protection Regulation (GDPR) compliance.
|Centralized O&M||Storage model||Mainstream Huawei storage models|
|Server model||Mainstream Huawei server models|
|Device management scale||Single-client: storage ≤ 256 sets; servers ≤ 5000
Multi-client: storage ≤ 256 x N (clients) [max. 5000 storage devices]
Emergency contacts: 5 (at least one must be a security administrator)
|Network bandwidth||≥ 10 Mbit/s|
|Health Assessment||Device health assessment||Real-time evaluation and scoring of system, hardware, configuration, capacity, and performance health|
|Alarm monitoring||24/7 remote alarm monitoring and automatic trouble tickets creation|
|Intelligent Analytics||Performance analytics||E2E performance analytics and topology|
|Performance fault diagnosis||Troubleshooting suggestions for performance faults with real-time latency detection|
|Performance fluctuation analytics||Automatic analytics of historical performance and identification of service change rules|
|Performance bottleneck analytics||Trend history: 1 month
Trend prediction: 2 months
Automatic troubleshooting suggestions for performance bottlenecks
|Intelligent Prediction||Capacity prediction||Capacity consumption predictions: 12 months
Advance warnings for overloaded resources
|Disk failure prediction||Disk risk prediction
Detection of faulty disks 14 days in advance