business background
With the rapid development of information technology, the combination of modern technology and strong financial demand has burst out huge innovation power. The financial industry continues to use information technology to carry out business innovation, and new business and service models continue to emerge. At the same time, more and more of business revenue comes from digital marketing and services.
As the core support platform for financial services, data centers are also continuing to undergo transformation and are undergoing modern digital transformation towards flexibility, agility, and rapid iteration. How to use innovative infrastructure to help financial users improve regulatory compliance, improve business continuity and agility, and speed up business and IT operation processing has become one of the key research directions for practitioners.
Challenges facing financial industry infrastructure
The architecture is not flexible
New businesses are emerging one after another, the IT architecture is slow to respond, and architecture adjustment is difficult. Multi-brand storage is difficult to operate and maintain, and unified management and scheduling cannot be achieved. Brands are kidnapped, equipment selection is limited, the environment is heterogeneous, and data management is complex, making it impossible to efficiently support the new business's demands on storage. Demand; complex system architecture, siled expansion, inelastic supply of capacity and performance, time-consuming and labor-intensive operation, and long storage hardware upgrade cycle.
Data is growing rapidly
The production data generated internally by financial enterprises and the data source data introduced from the outside have brought about massive data growth. In the past ten years, the internal data of enterprises has rapidly broken through from the gigabyte scale to the petabyte scale. It is foreseeable that, In the near future, exabytes will become the norm for internal data scale in large enterprises.
Data latency requirements
Facing various application scenarios such as high-density data operations, high concurrent access by Internet users, real-time data analysis, and machine learning, data storage systems must meet higher concurrent data access while ensuring low response time. The financial industry analyzes and mines a large amount of recorded and stored business data to support corporate business decision-making, accurate customer acquisition, risk prevention and other value-added data services, and puts forward higher requirements for storage performance.
Storage resources are difficult to allocate automatically, and application self-service capabilities are weak.
Although storage resources are divided into types, the actual allocation and adjustment process still requires professionals to use complex rules for manual maintenance. At present, in view of the storage performance requirements of various application systems, quantitative service standards and specification requirements have not yet been established for users to choose and use. When users go online for deployment, they do not fully understand the storage performance (IOPS\latency\throughput) requirements of the application system during daily and peak hours, making it difficult to implement user self-service functions.
Advantages of Financial Industry Solutions
Development and testing of private cloud/virtualization scenarios
In virtualization scenarios, IO is highly random and latency requirements are generally low. The unified storage block resource pool based on SDS technology can achieve dynamic expansion and effectively improve the management and usage efficiency of storage resources.
Database scenario
Database scenarios require random read and write performance and high reliability. SDS block storage combined with SSD meets the performance requirements of high IOPS and low latency through new generation distributed cache and other technologies, and supports multiple data redundancy protection mechanisms and enterprise-level features. Improve the reliability of business systems.
Disaster recovery & archiving scenarios
Breaking through the bottlenecks of traditional solutions in terms of capacity and massive small file support, users can achieve smooth upgrades and capacity expansion without being aware of it; in terms of performance, the multi-point access bandwidth of distributed storage is much better than that of single-head NAS, allowing future users to archive large amounts of data. The backup window during backup can be maintained at the originally estimated level; due to the always-online nature of object storage data, users can retrieve data on demand. Compared with backup methods such as traditional tape libraries, online big data mining has greater advantages. obvious.
Enterprise network disk scenario
Build an enterprise network disk through SDS object storage + customized development, and build a basic platform for collaborative working by all employees. Supports mobile terminal access, real-time data synchronization, and online editing/browsing to meet mobile office needs; supports mailbox integration, file sharing, team space and other features to meet collaborative office needs and improves office efficiency; object storage expansion capabilities and disaster recovery capabilities To meet the needs of enterprise office platform construction, the multi-center deployment architecture reduces network bandwidth resource consumption and saves cost investment.
Bill image scenes
Flat architecture reduces failure points, reduces bottlenecks, and saves storage servers; Internet access makes recording and recording venues more flexible; wide-area connectivity provides data access across data centers; linked file sharing breaks through the limitations of mapping relationships such as mounting , expansion is more convenient; the client is lightly dependent (Web access).
