– Lori MacVittie, senior technical marketing manager at F5 Networks (www.f5.com), says:
The problem of “big data” is highly dependent upon to whom you are speaking. It could be an issue of security, of scale, of processing, of transferring from one place to another.
What’s rarely discussed as a problem is that all that data got where it is in the same way: over a network and via an application. What’s also rarely discussed is how it was generated: by users.
If the amount of data at rest is mind-boggling, consider the number of transactions and users that must be involved to create that data in the first place – and how that must impact the network. Which in turn, of course, impacts the users and applications creating it.
It’s a vicious cycle, when you stop and think about it.
This cycle shows no end in sight. The amount of data being transferred over networks, according to Cisco, is only going to grow at a staggering rate – right along with the number of users and variety of devices generating that data. The impact on the network will be increasing amounts of congestion and latency, leading to poorer application performance and greater user frustration.
MITIGATING the RISKS of BIG DATA SIDE EFFECTS
Addressing that frustration and improving performance is critical to maintaining a vibrant and increasingly fickle user community. A Yotta blog detailing the business impact of site performance (compiled from a variety of sources) indicates a serious risk to the business. According to its compilation, a delay of 1 second in page load time results in:
- 7% Loss in Conversions
11% Fewer Pages Viewed
16% Decrease in Customer Satisfaction
This delay is particularly noticeable on mobile networks, where latency is high and bandwidth is low – a deadly combination for those trying to maintain service level agreements with respect to application performance. But users accessing sites over the LAN or Internet are hardly immune from the impact; the increasing pressure on networks inside and outside the data center inevitably result in failures to perform – and frustrated users who are as likely to abandon and never return as are mobile users.
Thus, the importance of optimizing the delivery of applications amidst potentially difficult network conditions is rapidly growing. The definition of “available” is broadening and now includes performance as a key component. A user considers a site or application “available” if it responds within a specific time interval – and that time interval is steadily decreasing. Optimizing the delivery of applications while taking into consideration the network type and conditions is no easy task, and requires a level of intelligence (to apply the right optimization at the right time) that can only be achieved by a solution positioned in a strategic point of control – at the application delivery tier.
Application Delivery Optimization (ADO)
Application delivery optimization (ADO) is a comprehensive, strategic approach to addressing performance issues, period. It is not a focus on mobile, or on cloud, or on wireless networks. It is a strategy that employs visibility and intelligence at a strategic point of control in the data path that enables solutions to apply the right type of optimization at the right time to ensure individual users are assured the best performance possible given their unique set of circumstances.
The technological underpinnings of ADO are both technological and topological, leveraging location along with technologies like load balancing, caching, and protocols to improve performance on a per-session basis. The difficulties in executing on an overarching, comprehensive ADO strategy is addressing variables of myriad environments, networks, devices, and applications with the fewest number of components possible, so as not to compound the problems by introducing more latency due to additional processing and network traversal. A unified platform approach to ADO is necessary to ensure minimal impact from the solution on the results.
ADO must therefore support topology and technology in such a way as to ensure the flexible application of any combination as may be required to mitigate performance problems on demand.
- Symmetric Acceleration
- Front-End Optimization (Asymmetric Acceleration)
Lengthy debate has surrounded the advantages and disadvantages of symmetric and asymmetric optimization techniques. The reality is that both are beneficial to optimization efforts. Each approach has varying benefits in specific scenarios, as each approach focuses on specific problem areas within application delivery chain. Neither is necessarily appropriate for every situation, nor will either one necessarily resolve performance issues in which the root cause lies outside the approach’s intended domain expertise. A successful application delivery optimization strategy is to leverage both techniques when appropriate.
- Protocol Optimization
- Load Balancing
Whether the technology is new – SPDY – or old – hundreds of RFC standards improving on TCP – it is undeniable that technology implementation plays a significant role in improving application performance across a broad spectrum of networks, clients, and applications. From improving upon the way in which existing protocols behave to implementing emerging protocols, from offloading computationally expensive processing to choosing the best location from which to serve a user, the technologies of ADO achieve the best results when applied intelligently and dynamically, taking into consideration real-time conditions across the user-network-server spectrum.
ADO cannot effectively scale as a solution if it focuses on one or two comprising solutions. It must necessarily address what is a polyvariable problem with a polyvariable solution: one that can apply the right set of technological and topological solutions to the problem at hand. That requires a level of collaboration across ADO solutions that is almost impossible to achieve unless the solutions are tightly integrated.
A holistic approach to ADO is the most operationally efficient and effective means of realizing performance gains in the face of increasingly hostile network conditions.