Application Scenarios
Scenario 1: Application O&M
Enterprises often encounter the following pain points when collecting logs for routine O&M, audit, or security compliance:
- They need to collect complex and massive logs from many departments.
- Too many cloud resources and untrained monitoring personnel make O&M difficult.
- High security compliance requirements and long-term storage result in high labor and maintenance costs.
LTS provides the following functions for this scenario:
- All-scenario quick log ingestion: covers services, applications, middleware, and infrastructure.
- Fast query and fault location: queries logs in seconds, and locates and analyzes issues in minutes based on the alarm rules and notifications you set.
- Long-term log storage in OBS: meets cyber security requirements.
Scenario 2: Security Compliance
For large enterprises, each service department has an independent cloud account for isolating resources, O&M personnel of each department rely on log monitoring and alarms to locate and analyze faults, and the security department needs to centrally monitor logs of all departments. Therefore, unified log management of multiple accounts is challenging.
- Independent O&M by service: Each service module has an independent account for resource isolation and needs a log service to configure monitoring alarms to quickly locate faults and root causes.
- Unified log monitoring: To meet regulatory requirements, the security department needs to aggregate logs of all accounts to one account and store the logs for more than 180 days.
LTS provides the following functions for this scenario:
- Independent management of accounts: Each account has isolated resources and permissions, and independently collects its own application and cloud service logs. You can configure alarm rules to demarcate 90% of problems in 10 minutes.
- Central aggregation of cross-account log data: The multi-account log center copies logs of multiple accounts to a unified monitoring account to store for at least 180 days for centralized compliance audits, meeting cyber security regulations.
Scenario 3: Operations Analysis
Enterprises collect various logs (such as mobile device and server logs) during their daily operations. After being normalized, filtered, anonymized, and enriched, these logs can be analyzed with big data platforms and BI tools to obtain operations data such as the PV, UV, user stay duration, and transaction amount. The data helps enterprises understand their operations status, analyze user behavior characteristics, make adjustments in real time, improve user experience and operations efficiency, and implement digital transformation.
Enterprises often encounter the following pain points during service analysis:
- Difficult data collection: It is not easy to collect logs of various mobile devices, such as web browsers, iOS, Android, Baidu applets, WeChat applets, DingTalk applets, and quick apps.
- Unreliable data transmission: Mobile device logs are numerous and frequently transmitted. The transmission is slow and logs are prone to be lost, affecting service analysis.
- Inconvenient data processing: Raw data cannot be directly processed by big data platforms.
LTS can collect various mobile device logs for you to analyze service operations on big data platforms.
- Full collection of device logs: You can quickly integrate LTS mobile SDKs to your devices to enable functions such as cache sending, retry upon exceptions, and batch sending.
- Fast and reliable reporting: The collected device logs are reported in seconds through the transmission link without data loss for more complete analysis.
- Quick interconnection with DLI and DWS: DLI-Flink integrates connectors and consumes logs from LTS in real time. LTS easily transfers logs to OBS for DLI to read, and transfers structured logs to DWS.
Feedback
Was this page helpful?
Provide feedbackThank you very much for your feedback. We will continue working to improve the documentation.See the reply and handling status in My Cloud VOC.
For any further questions, feel free to contact us through the chatbot.
Chatbot