tencent cloud

Cloud File Storage

Releases Notes and Announcements
Release Notes
Announcements
Product Introduction
Overview
Strengths
Storage Classes and Performance
Use Cases
Recommended Regions
Use Limits
Service Regions and Service Providers
Purchase Guide
Billing Overview
Pricing Overview
General Series Billing
Turbo Series Billing
High-Throughput CFS Billing
Billing Mode
IA ‍Storage Billing
Storage Resource Units
Resource Purchase
Viewing Bills
Arrears Reminder
Getting Started
Creating File Systems and Mount Targets
Using CFS File Systems on Linux Clients
Using CFS File Systems on Windows Clients
Using CFS Turbo on Linux Clients
Using the CFS Client Assistant to Mount File Systems
Operation Guide
Access Management
Managing File Systems
Permission Management
Using Tags
Snapshot Management
Guide for Cross-AZ and Cross-Network Access
Automatically Mounting File Systems
Data Migration Service
User Permission Management
User Quotas
Data Encryption
Data Lifecycle Management
Upgrading Standard File Systems
Practical Tutorial
Selecting Kernels for NFS Clients
Managing Turbo CFS Directories
Terminating Compute Instances
Using CFS on TKE
Using CFS on SCF
Using CFS Turbo on TKE
Using CFS Turbo on TKE Serverless Cluster
Selecting a Network for Turbo CFS
Copying Data
CFS Storage Performance Testing
API Documentation
History
Introduction
API Category
Snapshot APIs
File system APIs
Lifecycle APIs
Other APIs
Data Flow APIs
Making API Requests
Permission Group APIs
Service APIs
Scaling APIs
Data Migration APIs
Data Types
Error Codes
Troubleshooting
Client Use Bottleneck due to Large Number of Small Files or Parallel Requests
FAQs
CFS Service Level Agreement
Contact Us
Glossary

Features

PDF
포커스 모드
폰트 크기
마지막 업데이트 시간: 2024-01-22 22:15:48

Overview

Data lifecycle management is an advanced data management feature provided by Tencent Cloud File System (CFS) to balance high performance and low cost in large-scale file storage. With this feature, you can set custom data lifecycle management policies, and the file system can automatically move cold data to lower-cost IA storage based on these policies. When the data is accessed, it is automatically restored to file storage, with the entire process being transparent to the business. This lower‍s storage costs.

Use cases

Support for storage of massive amounts of data

In scenarios involving massive data storage, traditional cloud file storage is often unable to meet users' cost control requirements due to its high unit price. In the past, the common solution was to manually store data on object storage using tools. However, with data lifecycle management, data transitioning can be completed transparently through simple configuration, greatly simplifying the operation and reducing the total cost of data storage.

Hot/Cold data

In scenarios such as autonomous driving, AI training, and offline analysis, the access frequency of data is different. For example, newly written data is often accessed very frequently, while the access frequency of older data gradually decreases over time. The data lifecycle management feature is well-suited for such access patterns. It can significantly reduce the cost of storing cold data, while meeting high-performance read and write requirements.

Strengths

Support for flexible lifecycle policies

Policies based on directories: Different businesses often have different demands for lifecycle policies. Setting policies based on directories can better meet the demands for diverse policies.
Policies based on file size: Large files often take a long time to restore after transitioning. If your business is sensitive to latency in reading large files, you can set lifecycle policies based on file size to meet your requirements for timeliness.
Policies based on access period: You can flexibly adjust the scope of data for transitioning according to the characteristics of your business, reducing the impact of frequent transitioning and restoration on your business and making better use of lifecycle policies.

Transparent to the business side

After a lifecycle policy is configured, the system automatically transitions and restores data, without any change required to the data access mode of the business side.

Reduced costs

The data lifecycle management feature achieves tiered storage of hot/cold data, which can reduce the unit cost by up to 70% in some scenarios.

Feature details

Lifecycle management policies

When creating a lifecycle management policy, you can configure rules to transition files that have not been accessed within 14, 30, 60, or 90 days to IA storage. Lifecycle management will determine whether to transition a file based on its access time (atime).
The following operations will update the access time of a file:
Reading a file
Writing a file
The following operations will not update the access time of a file:
Querying file metadata (such as by performing the ls or state operation)
Renaming a file
Modifying file metadata such as user, group, or mode

Data transitioning/restoration

Data transitioning is a process in which data is moved from a Turbo file system to IA storage. When the trigger conditions of a policy are met, the system automatically adjusts the concurrency based on the current system load, and copies data to IA storage. Then, it releases the data in the Turbo file storage after 1 hour, with metadata information retained.
Data restoration is a process in which data is moved from IA storage to the Turbo file system. When data in IA storage is accessed for the first time, the system restores the data from IA storage to the Turbo file system. This process will take some time, depending on the file size and system load. When accessed later, this data will be obtained from the Turbo file system.

도움말 및 지원

문제 해결에 도움이 되었나요?

피드백