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    OceanStor Pacific Scale-Out Storage

    Embrace the new workloads of the yottabyte era.

New Workloads

  • New Workloads
  • New Changes
  • New Innovations
  • Resources

New Workloads Are Booming in the Yottabyte Era

Over the past three decades, data storage solutions for high-value data have become increasingly important and have evolved alongside the development of data workloads. As industries become more digitalized, data workloads become more diverse. Along with traditional database workloads, emerging workloads like High-Performance Data Analytics (HPDA), big data, and artificial intelligence (AI) are growing rapidly. These new workloads have a positive impact on the development of the digital economy.

AI technology has evolved from a specialized field focused on perceiving and understanding the world, to a more widespread field focused on generating and transforming it. The development of AI intelligence is determined by the quality and quantity of data available.
AI technology has evolved from a specialized field focused on perceiving and understanding the world, to a more widespread field focused on generating and transforming it. The development of AI intelligence is determined by the quality and quantity of data available.
Big Data
Big data analytics is a key means for enterprises to make informed decisions. Enterprises can use the analysis results of large-scale data sets to make better business decisions in real time in order to gain a competitive advantage in the market.
High Performance Computing
The combination of HPC, AI, and big data speeds up the development of HPDA, which is characterized by its data intensity. HPDA technology is widely used in life sciences research, oil and gas exploration, healthcare, and automobile R&D to improve production efficiency.
Containerized applications, such as autonomous driving and data exchange, are expanding from stateless to stateful. This is driven by the increase in mass unstructured data.

Five Changes Caused by New Workloads

Massive amounts of unstructured data are used in production and decision-making.
Knowledge mining from massive amounts of unstructured data can accelerate human genomics research, improve weather forecasting accuracy, assist diagnosis and treatment, help accurately locate oil and gas in energy exploration, and accelerate the R&D of autonomous vehicles.

With the advancement and widespread use of data analytics technologies, mass unstructured data is taking center stage in supporting enterprise production and decision-making. This in turn requires data storage to deliver more elastic scalability, higher efficiency, and better reliability.
Data is more dispersed.
On-premises data is distributed on different types of storage devices from different vendors, resulting in numerous data silos that hinder data utilization. Cross-region data is distributed in different data centers and edges, resulting in data isolation, which hinders instant access and unified protection. In addition, more and more data is distributed in both on-premises data centers and cloud infrastructure, making data mobility and collaborative production difficult.

Complicated management is the primary challenge caused by exponential data growth. Storage systems must be able to mask differences between heterogeneous devices, cross-region devices, and different IT infrastructures to simplify data management and improve data access efficiency.
Ransomware attacks have become the primary threat to enterprise data.
Recent years have witnessed more frequent ransomware attacks on business systems. According to a survey, a ransomware attack occurred every 11 seconds in 2021, and the number of ransomware variants increased by 98% from 2021 to 2022.

In terms of ransomware protection, the network layer can only intercept known viruses in most cases. As the final carrier of data, storage systems are responsible for detecting attacks, retaining important data copies, and promptly restoring services to build the last line of defense for data security.
Multi-cloud deployment is the new normal.
With the maturity of cloud native technologies and markets, more and more enterprises adopt multi-cloud IT construction to fully leverage the technical advantages of different cloud platforms. However, this practice has caused cloud data silos, preventing data from being shared between multi-cloud applications. Moreover, the services of different cloud platforms vary, hindering ecosystem integration.

Connecting one storage system to multiple clouds enables centralized data sharing, on-demand invoking, and multi-cloud application deployment, greatly reducing cross-cloud data migration and resource wastage while improving data movement efficiency.
Application-based innovation brings greater benefits.
As innovative services become production services and are continuously developed and segmented, there is an increasing gap between computing power and data lifecycles. Therefore, computing power and storage resources need to be flexibly and independently planned and maintained.

More and more enterprises use a decoupled compute-storage IT architecture and expect to build a highly reliable, cost-effective, and efficient solution for segmented scenarios through collaborative innovation of applications, computing, and storage.

Five Innovations of Huawei Scale-Out Storage

By embracing new workloads of the yottabyte era, Huawei OceanStor Pacific scale-out storage aims to build a cutting-edge unified data storage platform that can effectively address the unpredictable demands and challenges of new workloads through a reliable and simple storage infrastructure. OceanStor Pacific also helps simplify management of complex enterprise data, enhance data resilience, unleash the potential of mass data, and drive the intelligent evolution of all enterprise services.

Efficient Hybrid Workloads
Powered by the unique SmartBalance fully balanced system design, the unified storage platform enables one storage system to handle diversified workloads.
FlashLink® native scale-out all-flash architecture and intelligent algorithm innovation through software and hardware collaboration provide fast and stable performance in processing mass data.
Simplified Data Management
From data storage to data management, Huawei scale-out storage enables global data management, on-demand intelligent data mobility, and intelligent O&M (AIOps) between devices, data centers, and clouds, eliminating data silos and improving data center operation efficiency.
New Data Resilience
Always-on services: Reliability is ensured at every level, including I/Os, devices, systems, and solutions. The industry-leading geo-redundant active-active solution across multiple DCs uses the unique adaptive design of data synchronization and quasi-synchronization to ensure the continuity of large-scale services.
Always-secure data: An E2E ransomware protection solution is provided for mass unstructured data. In addition, OceanCyber provides a three-layer protection framework, featuring an industry-leading ransomware detection rate, physically isolated zone, and multiple rapid data recovery schemes, building superb capabilities of security defense against human errors.
Multi-Cloud Oriented
Huawei scale-out storage actively embraces cloud native and builds a global storage resource pool across multiple clouds. It supports multi-cloud access ecosystems, and enables diversified cloud data services such as archiving, backup, and data analytics through cloud virtualization and tiering/replication to cloud.
Scenario-Centric Innovation
DataTurbo data acceleration engine connects applications and storage to implement near-data processing. In emerging analytical application scenarios based on HPC, AI, and big data technologies, a single system can provide a staggering bandwidth capacity of tens of TB/s along with billion-level IOPS, supporting concurrent access of tens of thousands of computing clients.
Industry-leading data reduction and unique SuperCoding technologies support a wide range of data formats and semantic features, achieving lower total cost of ownership (TCO).