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The market for 2.5G and 3G services is taking shape as mobile providers offer customers capabilities that include Internet browsing, chat, multimedia downloads and online purchasing. These services promise to generate significant incremental revenue for providers, as customers embrace the next-generation mobile experience. They will also be important to other market beneficiaries * including content providers and online merchants * who see the affluent mobile user as an important target.

To ensure the success of their 2.5G and 3G services, however, mobile providers have to grapple with three primary risk factors. First, they obviously have to ensure that the services they offer are the ones buyers want. Only by understanding customers* wants and needs can providers offer a portfolio of services that will generate the necessary take-rates to be profitable. Second, they have to design those services to appeal to users despite small screens, slower access speeds and limited keypad functions. These design skills are essential for optimizing the user experience and market acceptance.

Third, providers must ensure the reliability of these services. It's one thing to tolerate a temporary outage on a free or bundled service. It's quite another thing to lose access to or experience chronically sub-par performance with a service you*re paying for. That's why it's absolutely critical for mobile providers to validate the performance of their 2.5G and 3G services before they roll them out to customers. Application failures are something mobile customers are unlikely to be very forgiving about. In fact, too many failures too early in the game may permanently turn customers off to these money-making services*dooming the market before it has a chance to take hold.

The Service Level Assurance Challenge

Ensuring service levels for 2.5G and 3G services presents special challenges. Multimedia applications, for example, are particularly bandwidth-hungry and are easily prone to session breakdowns due to temporary congestion in the network. In addition, such applications often use multiple session, signaling and data protocols. These complex dependencies often make it difficult to maintain service levels and understand the issues that may compromise the end-user experience.

In fact, providers often find themselves rolling new services out into production without fully understanding how those services will really be experienced by customers under real-world conditions. That's because services are typically tested in laboratory environments that don*t adequately reflect the bandwidth limitations, distance-driven latencies, and capacity contention that exist in the production environment. This is unfortunate, because it exposes providers to the considerable risk that applications won*t perform in production as they did in the lab.

By the same token, the inability to adequately assess the performance of applications before deployment may make success itself a risky proposition. After all, an application that performs perfectly well with several hundred simultaneous users may not survive the onslaught of tens of thousands. So, without appropriate preparation, providers can find themselves unable to cope with the very success they were hoping for!

The Solution: Network-Aware Development

One solution to this problem is to make the real-world conditions of the production network a central design consideration for all applications from the earliest stages of design. In other words, to ensure service quality in the real world AFTER deployment, it is essential to be able to discover any potential performance problems with an application's behavior in the real world BEFORE deployment.

This can only be done, however, if developers have some practical means of modeling those conditions in the lab. Ideally, such a modeling environment will be able to replicate conditions on the production network * including bandwidth constrains, the number of distribution of end-users, etc. If this modeling environment is then connected to the actual server infrastructure that will support the planned applications, the behavior of those applications in the real world can be accurately observed and tested. A variety of *what-if* scenarios can also be generated and observed to determine their impact on service levels: the loss of some portion of the network, an exceptional peak in service utilization, a spike in other types of network traffic, and so forth.

In addition to accurately replicating existing and projected real-world network conditions, an effective modeling environment should also lend itself to collaboration between application development teams and network infrastructure managers. By sharing a common modeling platform, these two groups can reach consensus about issues potentially affecting service levels * as well as the optimal remedy for such issues * rather than getting bogged down in conflict and finger-pointing. A multi-purpose modeling environment also ensures that any investment in modeling technology can be fully leveraged across the entire application lifecycle, including change management, capacity planning and CapEx projection.

Ensure Risk-Free Wireless Deployment

No provider can afford to have their early wireless service efforts tarnished with chronic poor performance. And no one wants to surrender their hard-earned early adopter customer to the competition because of service failures. Mobile providers who want to gain and sustain marketshare in value-added wireless services must therefore make every effort to ensure the reliability and performance of their offerings. And to do so, it is critical that they embrace modeling technologies that are as advanced and sophisticated as their next-generation networks.

To learn more, visit http://www.shunra.com. Shunra empowers enterprise organizations and technology vendors to eliminate the risks associated with rolling out complex, distributed, applications and services. The Shunra Virtual Enterprise (Shunra VE) solution provides accurate, highly granular insight into how networked applications (www.shunra.com) will function, perform and scale for remote end-users. It creates an exact replica of the production network environment, allowing users to safely develop, test and experiment with applications and infrastructure in a lab environment before deployment in production.