Log Service (SLS) is a one-stop logging service developed by Alibaba Cloud that is widely used by Alibaba Group in big data scenarios. You can use Log Service to collect, query, and consume log data without the need to invest in in-house data collection and processing systems. This enables you to focus on your business, improving business efficiency and helping your business to expand.

Log Service learning path

Log Service learning path provides a quick and easy route to understand Log Service. For more information, visit Log Service learning path and read the relevant user guides. Log Service learning path also provides videos that match the user guides to help you better understand Log Service.

LogHub

Features:
  • LogHub collects real-time log data from Elastic Compute Service (ECS), containers, mobile terminals, open-source software, and JavaScript. The log data can be metrics, events, binary logs, text logs, and clicks.
  • LogHub provides a real-time consumption interface to connect with Realtime Compute (formerly StreamCompute).

Scenarios: data cleansing (ETL), stream computing, monitoring, alert, machine learning, and iterative computing.

Data cleansing

LogSearch/Analytics

The LogSearch/Analytics feature allows you to index, query, and analyze log data in real time.

  • Keyword, fuzzy, context, and range queries are supported.
  • A variety of statistical methods are provided. For example, you can use SQL aggregate functions to obtain log data statistics.
  • You can use dashboards and charts to visualize log data.
  • Log Service supports seamless interconnection with Grafana based on the JDBC and SQL-92 protocols.

Scenarios: DevOps, online O&M, real-time log data analysis, security diagnosis and analysis, business operation systems, and customer service systems.

DevOps and online O&M

LogShipper

LogShipper ensures stable and reliable log shipping. With LogShipper, you can ship logs from LogHub to storage services. LogShipper allows you to store log data in compressed files, user-defined partitions, rows, and columns.

Scenarios: data warehousing, data analysis, data auditing, product recommendation, and user profiling.

LogShipper