This topic describes typical scenarios in which you can use Simple Log Service for your business. The scenarios include data collection and consumption, data extract, transform, and load (ETL) and stream processing, integration with data warehouses, and real-time query and analysis.
Data collection and consumption
You can use the LogHub module of Simple Log Service to collect large amounts of log data in real time. The log data can be metrics, events, binary logs, text logs, and clickstream data.
Ease of use: Simple Log Service supports more than 50 data sources to help you build platforms. Simple Log Service also provides powerful configuration and management capabilities to reduce your O&M workloads.
Elastic scalability: Simple Log Service can handle traffic spikes and business growth.
ETL and stream processing
LogHub can connect to multiple stream processing engines and services. LogHub can also monitor the processing progress and generate alerts. You can also use SDKs or call API operations to consume data based on your business requirements.
Ease of use: Simple Log Service provides comprehensive SDKs and programming frameworks for seamless integration with multiple stream processing engines.
Monitoring and alerting: Simple Log Service provides comprehensive metrics and an alerting mechanism upon latency.
Elastic scalability: Simple Log Service supports auto scaling to process petabytes of data without latency.
Integration with data warehouses
The LogShipper module of Simple Log Service can ship LogHub data to storage services. During the shipping, you can compress the data, define custom partition formats, and specify row or column store.
Large data capacity: An unlimited amount of data can be shipped to storage services.
Multiple formats: Various storage formats such as row store, column store, and text files are supported.
Flexible configurations: Different configurations are supported, which allows you to define custom partition formats.
Real-time query and analysis
The LogAnalytics module can index the data in LogHub in real time and provides multiple query methods such as keyword-based search, fuzzy search, contextual query, data query within a specific time range, and SQL-based aggregation.
Timeliness: You can perform real-time query operations after data is written to LogHub.
High efficiency and low costs: You can index petabytes of data each day. Costs are 85% lower compared with self-managed systems.
Powerful analysis: Simple Log Service supports multiple query methods and SQL-based aggregate functions. Simple Log Service also provides visualized reports and allows you to configure alerts.