| By Lori MacVittie |
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| April 19, 2012 02:30 AM EDT |
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7,112 |
“Big data” focuses almost entirely on data at rest. But before it was at rest – it was transmitted over the network. That ultimately means trouble for application performance.
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
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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.
