A method and system for managing a warm-cold storage data lifecycle

Abstract

The application discloses a kind of warm cold storage data life cycle management method and system, it is related to storage data management technical field, the method includes: obtaining business data, business data is written into hot storage system, or directly written into warm storage system;If business data is stored in hot storage system, warm storage system periodically scans hot storage system, and then obtains business data from hot storage system;Through the AI model built-in in warm storage system, multidimensional data analysis is carried out on business data based on data content type and access frequency, and data classification label is generated for business data, data classification label includes hot data, warm data and cold data;Warm storage system is based on data classification label and preset life cycle strategy, carries out the automatic migration of business data between hot storage system, warm storage system and ice storage system, and helps to solve the problem that prior art cannot realize data intelligent classification and automatic life cycle management.

Description

Technical Field

[0001] This invention relates to the field of data storage lifecycle management technology, and in particular to a method and system for managing the lifecycle of warm and cold storage data. Background Technology

[0002] In the process of enterprise digital transformation, the volume of unstructured data is rapidly increasing. Different types of data have significantly different needs in terms of access frequency, storage timeliness, and cost control, naturally forming a three-tiered data architecture of hot, warm, and cold. Currently, mainstream storage and data tiering solutions in the industry have multiple pain points and cannot adapt to the current data management, cost control, and industry compliance requirements. First, the storage architecture is simplistic, with a large amount of low-frequency, warm, and cold data occupying expensive storage resources, resulting in high costs and low utilization. Second, data tiering relies on manual static configuration, making it impossible to dynamically determine the value of data and easily leading to erroneous or missed migrations. Third, cold data archiving has weak compatibility, with poor compatibility between offline media and business system protocols, making retrieval and recovery complex. Fourth, compliance capabilities are lacking, failing to meet the requirements of industries such as finance, healthcare, and government in terms of data retention, tamper prevention, and auditability.

[0003] Existing mainstream technical solutions all have significant shortcomings: EMCAutoStart's data tiering management solution relies on storage clusters to achieve basic data tiering and resource scheduling, and uses static policies to complete data migration. It only supports static migration policies with fixed time and fixed access thresholds, lacks the ability to dynamically identify data value, and cannot adjust tiering rules based on real-time data access behavior, resulting in prominent issues of erroneous and missed migrations; it is only compatible with its own brand of storage hardware, has poor compatibility with heterogeneous storage and offline tape / Blu-ray archiving media, and cannot establish a unified access point for cold data; it lacks an independent unified metadata management module, the cold data retrieval and recovery process is cumbersome, and it does not have built-in data anti-tampering and operation auditing capabilities, making it difficult to meet the requirements of industries with strong compliance.

[0004] Huawei's DME (Data Management Engine) tiered storage solution provides unified operation and maintenance and data tiering capabilities for enterprise storage resources, and is a mainstream storage management platform in China. However, its data tiering logic still relies primarily on manual configuration strategies, only counting basic access frequencies. It cannot comprehensively determine the hot / cold status of data based on data content and business tags, resulting in limited accuracy in tiering. For offline cold archiving media such as tape and Blu-ray, it only provides basic integration capabilities and does not achieve transparent online access. Business systems still need to manually intervene to retrieve cold data. Its full lifecycle management capabilities are weak, lacking closed-loop management from data generation, tiering, migration, archiving to destruction, and its audit logs and data tamper-proofing functions are inadequate.

[0005] Traditional tape library archiving systems, as a classic offline storage solution for cold data, are widely used for the long-term preservation of massive amounts of cold data. However, as a purely offline storage medium, they are incompatible with online business system protocols, making transparent read / write operations impossible. They lack automatic tiering and intelligent migration capabilities, relying entirely on manual copying, sorting, and shelving, resulting in high labor costs and extremely low efficiency. Metadata is stored independently and fragmented, making cross-media and cross-node retrieval difficult and data recovery cycles long. Furthermore, they lack compliance auditing and tamper-proof mechanisms, only enabling basic data retention.

[0006] Therefore, there is an urgent need for a temperature and cold storage management method that can automatically classify, intelligently migrate, and uniformly manage the entire lifecycle, in order to solve the problems of high cost, low efficiency, poor compatibility, and insufficient compliance of existing technologies. Summary of the Invention

[0007] In view of this, the present invention proposes a management method and system for intelligent temperature and cold storage data lifecycle based on AI for accurate identification, which can realize intelligent data classification and automated lifecycle management.

[0008] To achieve the above objectives, the present invention provides the following technical solution: A method for managing the lifecycle of warm and cold storage data includes: Acquire business data, analyze the frequency of business data access, and generate data hierarchical tags; Write business data to a hot storage system or directly to a warm storage system; If the business data is stored in the hot storage system, the hot storage system periodically scans the hot storage system and then retrieves the business data from the hot storage system; The AI ​​model built into the warm storage system performs multi-dimensional data analysis on the business data based on data content type and access frequency, and generates data classification tags for the business data, including hot data, warm data and cold data. The warm storage system performs automated migration and archiving of business data between the hot storage system, warm storage system, and ice storage system based on the data classification tags and preset lifecycle strategies.

[0009] Based on the above technical solution, the present invention can be further improved as follows: Optionally, the step of performing data analysis on the business data through the warm storage system and generating data classification tags for the business data includes: The business data is hierarchically labeled based on the access frequency of the business data. Business data with an access frequency greater than or equal to a first preset threshold are marked as hot data; Business data whose access frequency is between the first preset threshold and the second preset threshold is marked as warm data; Business data with an access frequency less than or equal to the second preset threshold are marked as cold data.

[0010] Optionally, the warm storage system, based on the data grading tags and a preset lifecycle strategy, performs automated migration and archiving of the business data between the hot storage system, the warm storage system, and the ice storage system, including: Migrate the business data tagged as "temperature data" from the hot storage system to the warm storage system. Business data that is classified as cold data in the warm storage system is archived to the ice storage system.

[0011] Optionally, the method for managing the lifecycle of warm and cold storage data further includes: The metadata of the business data is stored uniformly through a warm storage system, and the corresponding metadata is recorded synchronously when cold data is archived to an ice storage system.

[0012] Optionally, the method for managing the lifecycle of warm and cold storage data further includes: When a user or system makes a cold data retrieval request via API, cold storage is immediately scheduled. Within 1-2 minutes, the corresponding cold storage medium can be automatically loaded onto the read / write drive and the file system can be mounted, so that the cold storage medium can switch from a dormant or offline state to an accessible state.

[0013] Optionally, the method for managing the lifecycle of warm and cold storage data further includes: When accessing cold data, the corresponding cold data is transmitted back from the ice storage system to the warm storage system.

[0014] Optionally, the method for managing the lifecycle of warm and cold storage data further includes: Once the cold data archived to the ice storage system reaches the preset retention period, a delayed deletion operation is performed. After the delayed deletion period expires, the data is automatically deleted, thus completing the full lifecycle management of business data.

[0015] A management system for the lifecycle of warm and cold storage data includes: The AI-powered intelligent grading module is used to analyze the frequency of business data access and generate data grading labels. The lifecycle management engine is used to perform automated migrations based on preset strategies; A hot storage system is used to hold temperature data accessed at medium frequency and to perform data classification and migration scheduling. Warm storage systems are used to store cold data that is archived infrequently, providing low-cost offline storage; The warm storage system is also used to periodically scan the hot storage system if the business data is stored in the hot storage system, and then obtain the business data, perform data analysis on the business data through the AI ​​model built into the warm storage system, and generate data classification tags for the business data, the data classification tags including hot data, warm data and cold data; Based on the data classification labels and preset lifecycle strategies, the automated migration and archiving of the business data is performed between the hot storage system, the warm storage system, and the ice storage system. Ice storage systems are used to archive cold data.

[0016] An electronic device includes a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor executes the computer program to implement the steps of the method described herein.

[0017] A non-transitory computer-readable storage medium having a computer program stored thereon, the computer program implementing the steps of the method when executed by a processor.

[0018] The present invention has the following advantages: This invention presents a data lifecycle management method for warm and cold storage. By unifying data grading and migration scheduling through a warm storage system, it enables automated data flow between hot, warm, and cold storage layers, significantly improving data lifecycle management efficiency. Tiered storage is driven by data grading tags and lifecycle strategies, reducing high-frequency storage resource consumption and drastically lowering storage and maintenance costs. Grading and migration require no manual intervention, minimizing errors and management complexity. Simultaneously, it enables orderly archiving of cold data, improving storage resource utilization while balancing access performance and long-term compliant retention requirements.

[0019] The present invention provides a method for managing the lifecycle of warm and cold storage data. It abandons the traditional model of manually configuring static rules and can dynamically identify the hot and cold levels of data by combining data content, access frequency, and business attributes from multiple dimensions. It can automatically complete the layering determination and completely solve problems such as erroneous migration, missed migration, and inaccurate grading.

[0020] This invention provides a method for managing the lifecycle of mid-temperature cold storage data. It is fully compatible with high-performance online storage, mid-temperature data storage, and offline cold archiving media such as magnetic tape / Blu-ray. It unifies the management of multiple storage protocols and metadata, enabling upper-layer services to achieve seamless and transparent retrieval and recovery of data at all levels, significantly improving data retrieval efficiency.

[0021] This invention provides a method for managing the lifecycle of warm and cold storage data. It constructs a closed-loop management system for the entire data lifecycle, from generation, hot, warm and cold stratification, intelligent migration, long-term archiving to destruction. This optimizes the allocation of storage resources, migrates low-frequency cold data to low-cost media, significantly reduces overall storage investment, and improves hardware resource utilization.

[0022] This invention provides a method for managing the lifecycle of medium-temperature and cold-storage data. It has built-in compliance capabilities and natively incorporates modules for data tamper prevention, full-process operation auditing, and long-term data retention and control. It fully matches the compliance standards of industries such as finance, healthcare, and government, eliminating data management compliance risks. Attached Figure Description

[0023] For illustrative and not limiting purposes, the present invention will now be described in conjunction with embodiments and accompanying drawings, wherein: Figure 1 This is a flowchart illustrating the method for managing the lifecycle of warm and cold storage data in an embodiment of the present invention. Figure 2 This is a schematic diagram of the main components of the warm and cold storage data lifecycle management system in an embodiment of the present invention; Figure 3 This is a schematic diagram of the physical structure of the electronic device provided by the present invention. Detailed Implementation

[0024] To enable those skilled in the art to better understand the present invention, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0025] It should be noted that the terms "first," "second," etc., in the specification and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be used interchangeably where appropriate for the embodiments of the invention described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0026] It should be noted that, where there is no conflict, the embodiments and features of the present invention can be combined with each other. The embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0027] Figure 1 This is a flowchart illustrating the data lifecycle management method for warm and cold storage according to an embodiment of the present invention, as shown below. Figure 1 As shown, the method for managing the lifecycle of warm and cold storage data provided in this embodiment of the invention includes the following steps S101 to S105.

[0028] S101: Acquire business data, analyze the frequency of business data access, and generate data hierarchical tags.

[0029] S102 writes business data to the hot storage system or directly to the warm storage system.

[0030] The production server writes business data to the production storage (hot storage system) via the standard NAS / S3 protocol; it also supports business systems writing data directly to the hot storage system without having to pass through the hot storage system.

[0031] The hot storage system includes a business server, storage switch, and SAN / NAS / S3 storage cluster, which is used to carry frequently accessed hot data and provide high-performance storage services for business systems; it also supports business systems to directly access the hot storage system and realize direct data writing.

[0032] The warm storage system includes gigabit switches, network switches, CloudBee AI unified storage servers (distributed architecture, compatible with SAN / NAS / S3 protocols), JBOD storage expansion cabinets, and FC switches, used to carry low-frequency access warm data, serving as an intermediate cache layer between hot and cold data; interconnection with the hot storage system and ice storage is achieved through Ethernet and 16GbFC networks.

[0033] The warm storage system adopts a distributed or standalone architecture, supports S3 / NFS standard protocol access, stores warm data and manages all data metadata; it has built-in data compression, deduplication, and multiple replica / erasure coding redundancy mechanisms to ensure data reliability.

[0034] S103, if the business data is stored in the hot storage system, the hot storage system periodically scans the hot storage system and then retrieves the business data from the hot storage system.

[0035] For business data that has been written to the hot storage system, the warm storage system actively pulls and synchronizes it to ensure that the data required for hierarchical analysis is complete and available.

[0036] The warm storage system has a built-in AI intelligent recognition module that automatically identifies the content and type of unstructured data such as images and documents, and generates data classification tags based on data access frequency and business attributes. Based on a preset lifecycle strategy, it proactively extracts warm / cold data from the hot storage system to achieve automated migration.

[0037] S104 uses the AI ​​model built into the warm storage system to perform multi-dimensional data analysis on business data based on data content type and access frequency, and generates data classification tags for business data.

[0038] Data classification labels include hot data, warm data, and cold data.

[0039] A three-layer architecture—multi-dimensional feature fusion, a lightweight deep learning classification model, and a value enhancement factor—is used to generate data grading labels for the business data, while also taking into account traditional thresholding models, including: I. AI Tag Model Pattern Hierarchical Tag: Data feature acquisition layer: Real-time acquisition of access behavior, content attributes, business tags, and time features; AI Intelligent Evaluation Layer: Based on an improved LightGBM+LSTM hybrid model, it outputs data popularity scores and hierarchical labels; Strategy decision-making layer: Dynamically generate migration / retention / archiving strategies by combining cost, compliance, and storage load.

[0040] 2. Classify and label the business data based on the access frequency of the business data; Business data with an access frequency greater than or equal to a first preset threshold are marked as hot data; Business data whose access frequency is between the first preset threshold and the second preset threshold is marked as warm data; Business data with an access frequency less than or equal to the second preset threshold are marked as cold data.

[0041] The first preset threshold is 1 time per week, and the second preset threshold is 1 time per month (all thresholds can be customized according to business needs).

[0042] The S105, a warm storage system, performs automated migration and archiving of business data between hot storage systems, warm storage systems, and ice storage systems based on data grading labels and preset lifecycle strategies.

[0043] Ice storage system: Includes tape drive / Blu-ray storage arrays to carry long-term archived cold data, achieving low-cost, highly reliable offline storage; it interfaces with warm storage systems via FC network to support D2D2T (disk to tape) archiving processes.

[0044] Business data categorized as "hot data" is migrated to the hot storage system. Business data categorized as "warm data" will be migrated to the warm storage system. Business data that is classified and labeled as cold data is archived into the ice storage system.

[0045] The method for managing the lifecycle of warm and cold storage data also includes: According to the lifecycle strategy, the warm storage system archives cold data to the ice storage system (tape library / Blu-ray storage); the tape library uses the LTFS file system, and the Blu-ray storage supports direct reading, ensuring the accessibility of archived data; the archived data is set with a delayed deletion strategy to meet compliance retention requirements.

[0046] The front-end business system can directly access the warm storage system data through the NAS / S3 gateway; in response to cold data retrieval requests, it automatically loads the corresponding cold storage medium to the read / write drive, so that the cold storage medium switches from a dormant or offline state to an accessible state, realizing transparent access without manual intervention.

[0047] When accessing cold data, the corresponding cold data is transmitted back from the ice storage system to the warm storage system.

[0048] The metadata of the business data is stored uniformly by a warm storage system, and the corresponding metadata is recorded synchronously when cold data is archived to an ice storage system, so as to realize the rapid retrieval and location of cold data.

[0049] This invention allows business data to be written to production storage (hot storage system) via the production server or directly to a warm storage system. The warm storage system incorporates a data lifecycle management strategy and can proactively extract data from production storage. Through an AI intelligent recognition module, the warm storage system performs content recognition and access statistics on business data such as images and documents, generates data grading tags, and stores full data metadata. According to a preset strategy, the warm storage system writes cold data to a cold storage system, which supports tape libraries using the LTFS file system or directly readable Blu-ray discs. Simultaneously, the warm storage system performs delayed deletion of archived data according to lifecycle compliance requirements. The business front-end can access data via the standard NAS / S3 protocol. When accessing cold storage data, the system automatically loads the cold storage medium, enabling transparent access.

[0050] Figure 2 This is a schematic diagram illustrating the main components of the warm / cold storage data lifecycle management system according to an embodiment of the present invention. For example... Figure 2 As shown, the data lifecycle management system 1 for warm and cold storage provided in this embodiment of the invention includes an AI intelligent grading module 10, a lifecycle management engine 20, a hot storage system 30, a warm storage system 40, and an ice storage system 50.

[0051] AI intelligent classification module 10 is used to analyze the frequency of business data access and generate data classification labels; Lifecycle management engine 20 is used to perform automated migrations according to preset strategies; Hot storage system 30 is used for writing business data; The hot storage system deploys a multi-node distributed SAN storage cluster, which is connected to the business server through two 10 Gigabit storage switches to carry high-frequency access data for core business operations. Warm storage system 40 is used for writing business data; The warm storage system deploys a multi-node cloud backup AI unified storage server (distributed architecture), expands with multiple JBOD storage cabinets, and the total capacity can reach several thousand PB; it interfaces with the hot storage system layer through two 25Gb network switches and with the ice storage layer through two 16GbFC switches; gigabit switches are deployed for device management. The warm storage system is further configured to, if the business data is stored in the hot storage system, retrieve the business data from the hot storage system, perform data analysis on the business data through the warm storage system, and generate data classification tags for the business data, wherein the data classification tags include hot data, warm data, and cold data; Based on the data classification labels and preset lifecycle strategies, the automated migration and archiving of the business data is performed between the hot storage system, the warm storage system, and the ice storage system. Ice storage system 50, used for archiving cold data.

[0052] Ice storage systems can deploy multiple tape libraries and tape reels, and their capacity can be linearly expanded indefinitely as required. The system adopts a three-network isolation architecture, with physical isolation between the service network (25Gb+Ethernet), storage network (16Gb+FC), and management network (1GbEthernet) to ensure data security.

[0053] Table 1 compares the innovations of this invention with existing technologies. As shown in Table 1, the system of this invention automatically classifies data based on both AI models and data access frequency, replacing the traditional classification method that relies solely on fixed rule configurations. The system enables automated data transfer between hot, warm, and cold storage media without manual intervention. During cold data retrieval, the system automatically wakes up the storage media for transparent access, eliminating the need for manual tape loading. Once archived data meets compliance retention requirements, the system automatically performs a deletion operation, replacing existing manual deletion methods. This invention's system is divided into three tiers: a business system (including a hot storage system), a warm storage system, and an ice storage system. Business servers can write business data to the SAN / NAS / S3 storage cluster of the hot storage system via storage switches, or directly to the warm storage system. The warm storage system has a distributed architecture, including a cloud-based AI unified storage server, JBOD expansion cabinets, network switches, and FC switches. It interfaces with the hot storage system via Ethernet to synchronize data and with the ice storage system via a 16Gb+FC network to achieve cold data archiving. The ice storage system consists of a tape library or Blu-ray storage array, used for low-cost, long-term archiving of cold data. The warm storage system incorporates an AI intelligent recognition module and a lifecycle management engine, responsible for data classification and tagging, automated migration, and unified metadata management, realizing automated data flow throughout the entire lifecycle between the three storage tiers, balancing access performance, storage cost, and compliance retention requirements. The architecture of this invention's warm and cold storage data lifecycle management system is shown in the figure. The system is divided into three tiers: a business system (including a hot storage system), a warm storage system, and an ice storage system. Business servers can write business data to the SAN / NAS / S3 storage cluster of the hot storage system via storage switches, or directly to the warm storage system. The warm storage system features a distributed architecture, comprising a cloud-based AI unified storage server, JBOD expansion cabinets, network switches, and FC switches. It interfaces with the hot storage system via Ethernet to synchronize data and with the ice storage system via a 16Gb+FC network for cold data archiving. The ice storage system, consisting of a tape library or Blu-ray storage array, is used for low-cost, long-term archiving of cold data. The warm storage system incorporates an AI intelligent recognition module and a lifecycle management engine, responsible for data tiering and tagging, automated migration, and unified metadata management. This enables automated data flow across the three storage tiers throughout its entire lifecycle, balancing access performance, storage costs, and compliance retention requirements.

[0054] Figure 3 This is a schematic diagram of the physical structure of an electronic device provided in an embodiment of the present invention, such as... Figure 3 As shown, the electronic device 60 includes: a processor 601, a memory 602, and a bus 603; The processor 601 and the memory 602 communicate with each other via the bus 603. The processor 601 is used to call program instructions in the memory 602 to execute the methods provided in the above-described method embodiments, and to execute the methods provided in the embodiments of the present invention.

[0055] This embodiment provides a non-transitory computer-readable storage medium that stores computer instructions, which cause a computer to execute the method provided in this embodiment of the invention.

[0056] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments. The aforementioned storage medium includes various storage media capable of storing program code, such as ROM, RAM, magnetic disk, or optical disk.

[0057] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can occur depending on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for managing the lifecycle of warm and cold storage data, characterized in that, include: Acquire business data, analyze the frequency of business data access, and generate data hierarchical tags; Write business data to a hot storage system or directly to a warm storage system; If the business data is stored in the hot storage system, the hot storage system periodically scans the hot storage system and then retrieves the business data from the hot storage system; The AI ​​model built into the warm storage system performs multi-dimensional data analysis on the business data based on data content type and access frequency, and generates data classification tags for the business data, including hot data, warm data and cold data. The warm storage system performs automated migration and archiving of business data between the hot storage system, warm storage system, and ice storage system based on the data classification tags and preset lifecycle strategies.

2. The method for managing the lifecycle of warm and cold storage data according to claim 1, characterized in that, The step of performing data analysis on the business data through the warm storage system and generating data classification tags for the business data includes: The business data is hierarchically labeled based on the access frequency of the business data. Business data with an access frequency greater than or equal to a first preset threshold are marked as hot data; Business data whose access frequency is between the first preset threshold and the second preset threshold is marked as warm data; Business data with an access frequency less than or equal to the second preset threshold are marked as cold data.

3. The method for managing the lifecycle of warm and cold storage data according to claim 1, characterized in that, The warm storage system, based on the data grading tags and preset lifecycle strategies, performs automated migration and archiving of the business data between the hot storage system, warm storage system, and ice storage system, including: Migrate the business data tagged as "temperature data" from the hot storage system to the warm storage system. Business data that is classified as cold data in the warm storage system is archived to the ice storage system.

4. The method for managing the lifecycle of warm and cold storage data according to claim 1, characterized in that, The method for managing the lifecycle of warm and cold storage data also includes: The metadata of the business data is stored uniformly through a warm storage system, and the corresponding metadata is recorded synchronously when cold data is archived to an ice storage system.

5. The method for managing the lifecycle of warm and cold storage data according to claim 1, characterized in that, The method for managing the lifecycle of warm and cold storage data also includes: When a user or system makes a cold data retrieval request via API, cold storage is immediately scheduled. Within 1-2 minutes, the corresponding cold storage medium can be automatically loaded onto the read / write drive and the file system can be mounted, so that the cold storage medium can switch from a dormant or offline state to an accessible state.

6. The method for managing the lifecycle of warm and cold storage data according to claim 5, characterized in that, The method for managing the lifecycle of warm and cold storage data also includes: When accessing cold data, the corresponding cold data is transmitted back from the ice storage system to the warm storage system.

7. The method for managing the lifecycle of warm and cold storage data according to claim 1, characterized in that, The method for managing the lifecycle of warm and cold storage data also includes: Once the cold data archived to the ice storage system reaches the preset retention period, a delayed deletion operation is performed. After the delayed deletion period expires, the data is automatically deleted, thus completing the full lifecycle management of business data.

8. A management system for the lifecycle of warm and cold storage data, characterized in that, include: The AI-powered intelligent grading module is used to analyze the frequency of business data access and generate data grading labels. The lifecycle management engine is used to perform automated migrations based on preset strategies; A hot storage system is used to hold temperature data accessed at medium frequency and to perform data classification and migration scheduling. Warm storage systems are used to store cold data that is archived infrequently, providing low-cost offline storage; The warm storage system is also used to periodically scan the hot storage system if the business data is stored in the hot storage system, and then obtain the business data, perform data analysis on the business data through the AI ​​model built into the warm storage system, and generate data classification tags for the business data, the data classification tags including hot data, warm data and cold data; Based on the data classification labels and preset lifecycle strategies, the automated migration and archiving of the business data is performed between the hot storage system, the warm storage system, and the ice storage system. Ice storage systems are used to archive cold data.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method as described in any one of claims 1 to 7.

10. A non-transitory computer-readable medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1 to 7.

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