Overview of Metadata and Data Discovery - Object Storage Service

The metadata and data discovery module for Object Storage Service (OSS) enables intelligent management and efficient retrieval of large volumes of files. This module uses features such as file metadata management, multi-dimensional data indexing, storage inventory export, and file query to solve common problems in traditional file management, such as low retrieval efficiency, complex metadata configuration, and difficulty in compiling file statistics.

Scenarios

Static website performance optimization

When you host static websites on OSS, you often face issues such as slow loading caused by improper cache policies and access errors caused by incorrect file type detection. The Manage file metadata feature lets you precisely control Cache-Control policies, set the correct Content-Type for files, and configure Content-Disposition to control how files are displayed. Proper metadata configuration improves website loading speed and reduces unnecessary traffic consumption and Alibaba Cloud CDN (CDN) back-to-origin costs.

Intelligent management of multimedia content

OSS is often used to store large numbers of image, video, and audio files. The AISearch feature lets you perform intelligent searches based on content semantics. You can find relevant files by searching with natural language descriptions, such as 'spring cherry blossoms', 'sunset at the beach', or 'meeting recording'. This semantic search capability improves the efficiency of content discovery.

Corporate data compliance audit

Industries such as finance, healthcare, and government must conduct regular data audits to meet regulatory requirements. Traditional methods require manually traversing files and recording their properties, which is inefficient and prone to error. The scalar retrieval feature lets you quickly filter target files based on metadata conditions such as creation time, storage class, access permissions, and custom tags. You can then automatically generate audit reports to improve audit efficiency.

Storage cost analysis and optimization

As your business grows, large numbers of files accumulate in OSS. However, a lack of a clear understanding of storage distribution and cost composition makes it difficult to create effective cost optimization strategies. The bucket inventory feature lets you regularly generate detailed file statistics reports. You can analyze storage usage across different storage classes and business modules, identify redundant files that have not been accessed for a long time, and find opportunities for cost optimization. By implementing proper lifecycle configurations and adjusting storage classes, you can achieve significant cost savings.

Large-scale data analysis and query

OSS stores large amounts of structured data files, such as logs and reports in CSV and JSON formats. You can use the Query files feature to directly query and analyze data in the cloud. This eliminates the need to download data for local processing, which can be resource-intensive. The Query files feature supports standard SQL statements on OSS and returns only the data that matches your criteria. This greatly reduces data transfer volume and local computing load. It is ideal for scenarios such as log analysis, data validation, and report generation, and supports mainstream SQL operations, such as WHERE conditional filters and aggregate functions.

Core concepts

File metadata types

File information stored in OSS consists of two types: standard HTTP properties and user-defined metadata. Standard HTTP properties, such as Content-Type and Cache-Control, control file access behavior. User-defined metadata starts with x-oss-meta- and is used to identify the business properties and purposes of files.

Data indexing mechanism

OSS data indexing automatically builds an index table for file metadata, which supports querying massive volumes of files in seconds. Depending on the retrieval method, indexing operates in two modes: scalar retrieval and AISearch.

Bucket inventory

The bucket inventory feature automatically generates detailed reports for all files in a bucket at regular intervals. These reports include information such as file names, sizes, storage classes, and encryption statuses. Compared to traversing files one by one using the ListObjects operation, the inventory feature is more efficient and cost-effective in scenarios with a massive number of files.

FAQ

How do I choose the right data retrieval method?

The choice of retrieval method depends on your business requirements. You can use scalar retrieval if you primarily perform term queries based on file properties for tasks such as file statistics, data audits, or cost analysis. It supports larger file volumes and is more cost-effective. You can use AISearch to perform fuzzy matching based on file content for tasks such as semantic content search, multimedia similarity retrieval, or intelligent content discovery. It provides a more intelligent search experience. You can enable both methods simultaneously and choose between them as needed for different scenarios.

What are the advantages of data indexing over traditional file management methods?

Traditional methods require using the ListObjects operation to traverse files and manually build a retrieval system. For scenarios with a massive number of files, this approach leads to performance bottlenecks, complex development, and high maintenance costs. The OSS metadata and data discovery module provides out-of-the-box indexing capabilities, eliminating the need for extra development and maintenance. It also supports advanced features such as semantic search and batch analysis, meeting the demands of modern enterprises for intelligent file management.

How can I ensure stability and security in a production environment?

All features are validated in large-scale production environments and support high-concurrency access and massive data processing. To ensure stability and security in your production environment:

1) Set access permissions properly to prevent sensitive data leaks.

2) Monitor index creation progress and query performance to promptly detect anomalies.

3) Regularly back up important metadata configurations and inventory data.

4) Use Resource Access Management (RAM) access control and Virtual Private Cloud (VPC) network isolation to ensure access security.

For more information about best practices for production environments, see the user guide for each feature.