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Last Updated: Feb 25, 2018

Typical scenarios of Log Service include data collection, real-time computing, data warehousing and offline analysis, product operation and analysis, and Operation & Maintenance (O&M) and management. This document introduces some typical scenarios. For more scenarios, see Best practices.

Data collection and consumption

The LogHub function of Log Service enables access to massive real-time log data (including Metric, Event, BinLog, TextLog, and Click data) at the lower costs.

Advantages of the solution:

  • Easy to use: Over 30 real-time data collection methods are provided for you to quickly build your platform. The powerful configuration and management capabilities can ease O&M workload. Nodes are available across China and the rest of the world.
  • Auto scaling: It helps easily cope with traffic peaks and business growth.


ETL/Stream Processing

LogHub can interconnect with various real-time computing and services, provides complete progress monitoring and alarm notification functions, and supports SDK/API-based custom consumption.

  • Easy to operate: It provides various SDKs and programming frameworks and can interconnect with various stream computing engines seamlessly.
  • Comprehensive functions: Rich monitoring data and alarm postponing mechanism are provided.
  • Auto scaling: PB-grade elasticity and zero latency.


Data warehouse

LogShipper ships LogHub data to storage services and supports various storage formats such as compression, user-defined partitions, row storage, and column storage.

  • Massive data: No upper limit is configured for the amount of data.
  • Rich storage formats: Various storage formats are supported, such as row storage, column storage, and TextFile.
  • Flexible configuration: Configurations such as user-defined partitions are supported.


Real-time query and analysis of logs

LogAnalytics supports indexing LogHub data in real time and provides rich query methods such as keywords, fuzzy match, context, range, and SQL aggregation.

  • Strong real-timeliness: Data can be queried after being written.
  • Massive amount and low cost: Supports PB/day indexing capabilities, and the cost is 15% of the self-built solution.
  • Strong analysis capabilities: Supports multiple query methods. Supports SQL aggregation and analysis. Visualization and alarm notification functions are provided.


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