ADN Provides Global Reach And Flexibility For Business-Critical Applications
Today, all global companies rely more on cloud to manage their critical business functions and application performances that have become a key issue to meet the demands of their end-users. Further, the difficult economic environment has put a tremendous strain on budgets and infrastructure, forcing companies to rethink about their deployment strategies and resource allocation. Application Delivery Networks (ADN) provide increased performance of dynamic applications without investing in new infrastructure, thereby enabling businesses to expand their reach, improve productivity, brand-loyalty, and reduce associated costs.
Today, all global companies rely more on cloud to manage their critical business functions and application performances that have become a key issue to meet the demands of their end-users. Further, the difficult economic environment has put a tremendous strain on budgets and infrastructure, forcing companies to rethink about their deployment strategies and resource allocation. Application Delivery Networks (ADN) provide increased performance of dynamic applications without investing in new infrastructure, thereby enabling businesses to expand their reach, improve productivity, brand-loyalty, and reduce associated costs.
Majority of the companies are using web-based applications to leverage the global reach, speed and cost of Internet. A web-enabled enterprise can cost effectively for providing corporations with tremendous reach and flexibility for their business-critical applications. However, the nature of applications has changed dramatically over time from static-cacheable content to dynamic-interactive content. Due to this, the business productivity relies on the performance of their applications, as poor performance would lead to losses and reduced customer base. For instance, for public-facing companies, such as e-commerce sites, social media services sites, and interactive corporate sites; the performance of online applications is the most critical focus area.
The ADN leverages the fast-start techniques to increase page-load speeds and overall performance of applications. It also employs protocol optimization techniques to optimize Transmission Control Protocol (TCP) and Hypertext Transfer Protocol (HTTP) specifications, thereby accelerating delivery times. ADN can also be configured as per customers’ specific content need. It can segregate between cacheable and dynamic contents and can deliver it separately as per customers’ needs. For instances where it is difficult to segregate between cacheable and dynamic content, ADN offers dual-mode capability that supports both type of content on the same network. This capability offers highly flexible and cost-effective application delivery solutions.
The ADN solutions are currently finding traction in media and entertainment, high-tech, education, government, banking, and healthcare segments, and are expected to expand their reach into manufacturing and transportation segments in the near future. Moreover, with the proliferation of cloud services, ADN solutions are increasingly adopted by network service providers, carriers, and cloud-operators. Cloud-operators are adopting ADN solutions to manage their bandwidth resources to achieve profitability, thereby delivering superior Quality-of-Experience (QoE) to their customers. The ADN solutions are widely used by online customization-information portals, e-commerce, booking-engine applications, social-media services, and various other verticals.
Some of the major players in the ADN space include F5 Networks, Citrix, Cisco, A10 Networks, Blue Coat Systems, Radware, among others. MarketsandMarkets expects the ADN market to grow from $3.23 billion in 2013 to $5.82 billion by 2018 at a CAGR of 12.5% from 2013 to 2018.
Related Report:
Application Delivery Network (ADN) Market [Application delivery controllers (ADC), WAN Optimization controllers (WOC), Application Security Equipments, Application Gateways] Global Advancements, Worldwide Forecasts & Analysis (2013 - 2018
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