Log Project

Log project is the resource management unit for Cloud Log Service. You can use log projects to manage data in different applications, products, or projects. For each log project, you can create multiple log units, through which you can access Cloud Log Service resources.

Log Unit

Log unit is the basic unit for collecting, storing, querying, and analyzing log data in Cloud Log Service. Each log unit belongs to a log project, and multiple log units can be created in each log project.

Server Management

A host group is a set of cloud servers for which you want to collect logs. It is a virtual group. Cloud Log Service manages all cloud servers that require log collection through the collector as host groups. It is recommended that you divide host groups based on different business scenarios to facilitate your management of Cloud Log Service.

Log Ingestion

Cloud Log Service supports real-time log collection, with a collector to help you collect logs in various data source scenarios. After a log is collected, you can query and analyze the log data in real time on the Cloud Log Service console.

• The collector supports non-intrusive ingestion to implement real-time log collection, batch capture and reporting of log files, and multi-channel data processing, achieving efficient collection.

• Logs can be collected from cloud servers, container applications, microservice applications, and other components.

• The collection rules support dynamic configuration and provide structuring log parsing with single-line/multi-line full texts, regular expressions, delimiters, and JSON.

Log Query and Analysis

Log query refers to the functions that enable you to filter, query, and perform statistical analysis on log data collected into Cloud Log Service.

• For collected log data, second-level log queries are supported, and it takes less than one minute from a log is collected to when it can be queried.

• Provides rich query syntax to facilitate users to perform log query operations such as keyword queries, fuzzy queries, and range queries.

• Supports fuzzy queries, full-text queries, field queries, and time range queries.

• Supports contextual queries.

• Supports various query and analysis scenarios.

Data Processing

Supports processing of log data, including data normalization, desensitization and filtering.

• Data normalization: Log data often comes from different system components, applications, or devices, so its formats and structures may vary, causing difficulties in analyzing, querying, and visualizing log data. Data normalization can extract fields from logs of different formats and convert these logs to a consistent format for subsequent processing and analysis.

• Data desensitization: Desensitize sensitive information (such as passwords, mobile phone numbers, and addresses) in log data.

Alarm

You can customize alarm rules on the Cloud Log Service console and configure different rules for different log projects and log units. The applied alarm rules periodically execute monitoring tasks and execute retrieval and analysis on the specified log units. When the retrieval results meet the trigger conditions, an alarm notification will be sent so that users can know about the issues in time.

• Data filtering: Filter logs of key businesses or services for subsequent key analysis and other scenarios.