Application Workloads: Achieving Peak Performance

HOW DATA DRIVES SUCCESS

Fast Application Performance is Key to Business Success


Every day, applications within an enterprise are constantly changing, requiring businesses to be agile decision-makers. They need to provision IT resources quickly to meet application demands, when and where they are required. The ability to react to the expanding diversity of big and fast data applications is vital; and requires the allocation of more compute, storage, and network resources at scale, and in real time, across the enterprise.

That’s why analysis has become an important part of data capture, enabling organizations to extract insights that could lead to better business decisions, efficiencies in productivity and automation, or unexpected value.

11% in 2018

Enterprise software spending will increase over 11% in 2018 and is expected to generate over $391 billion in revenue1

$22.8B in 2020

Global software business intelligence (BI) and analytics markets are forecast to reach $22.8 billion in revenue in 2020, up from $18.3 billion in 20173

The emergence of Fast Data and computations at the edge creates a factual consequence that moving all of the data back and forth to the cloud for computational analysis is not very efficient. . . . As such, each added edge device brings an incremental increase in the computational power required. Optimization on how and when the data moves is a key factor in the scalability of new architectures.

SOURCE: A NEW ERA OF STORAGE: OPEN COMPUTE WITH RISC-V AND MEMORY FABRICS BY DR. ZVONIMIR BANDIC, WESTERN DIGITAL (EMBEDDED COMPUTING DESIGN, 2/21/18)
OPTIMIZING APPLICATION WORKLOADS

Scaling for Success


As big data and fast data applications proliferate, they are breaking the boundaries of traditional infrastructures. The 'general-purpose' technologies that have served us so well in the past are reaching their limits of scalability, performance, and efficiency. When data-intensive workloads are supported by these architectures, a uniform ratio of resources are used for all compute processing, storage, and network bandwidth requirements. This ‘one-size-fits-all’ approach is not effective for these diverse, data-intensive workloads.


What is required for today’s data-centric architectures are capabilities that enable more control over the blend of resources that each application needs; so that optimized levels of processing, storage, and network bandwidth can be scaled independent of one another to meet specific application needs.

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DATA ACCELERATES BUSINESS
 

Western Digital Offers a Portfolio of Products Designed to Accelerate Application Workloads

Oracle MySQL

Microsoft SQL Server

Oracle Database And Oracle Rac

INDUSTRY EXPERTS AGREE

Data Centers are under increasing pressure to build infrastructures that are responsive to the application workloads of the organization. Understanding what a workload is and what its characteristics are is critical to creating a responsive infrastructure that can satisfy the variety of demands being placed on IT by an organization’s customers, users and application owners…

The ability to capture workload I/O characteristics, analyze that data and regenerate it is a critical capability for data centers to master. Workload profiling enables organizations to troubleshoot and optimize their current environment as well as plan, for the future.

SOURCE: WHAT ARE WORKLOADS AND WHY YOU SHOULD CARE BY GEORGE CRUMP (STORAGE SWITZERLAND, 12/2/15)

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Disclosures

1. Source: Enterprise-Software Spending to Surge 11%: Gartner by Jon Swartz (Barron’s quoted Gartner, 4/9/18)   2. Source: Mobile App Usage - Statistics & Facts, Statista   3. Source: Gartner Says Worldwide Business Intelligence and Analytics Market to Reach $18.3 Billion in 2017, Press Release by Gartner 2/17/17)  
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