BYOD - It Started One Christmas
December 23, 2013

Jim Swepson
Itrinegy

Share this

It started one Christmas! Executive's wives in droves worldwide purchased the latest gadget, the IPAD, for their husbands. These happy guys spent time going online and realizing quickly that they could do more on this nifty tablet than just surf the web. In fact they could pretty much do what they were doing on their laptops. It wasn't long before they took these devices into their offices – not just showing off the latest toy but a new way to make their working lives easier and it wasn't long before they were badgering their IT departments for access to company applications on these new devices.

IT departments enabled the execs and other users of BYOD (Bring Your Own Device) and with increasing confidence BYOD gained momentum as it became pervasive among many of us. But complications ensued as the users wanted this capability everywhere, so what started in the confines of the office (relatively safe LAN) now had to contend with delivering these business applications in coffee houses, on trains, transport, and home territory across WiFi, 2g, 3G home network (ISP)etc.

When enabling BYOD there are 3 main areas to focus on:

- Security, e.g lost information, updating problems and there’s a growing number of protocols being developed around this issue.

- Availability, with questions such as can I use the app? will it work on my device? for example; certain Adobe apps no longer work on the apple iOS mobile devices - this may be a problem for companies who heavily use Adobe.

- Now the first two are obvious, but the third is as important - Is it any good? Are the users getting a good experience in the confines of the office and outside in a WiFi network. Two kinds of networks are available to BYOD: WiFi (which is generally provided by the company itself) and Mobile (3G/2G etc which is completely out of the corporations control).

It's emerged recently that there is a hidden cost in BYOD: the cost of unhappy users. When looking at BYOD, it's essential to not only understand the network usage but also to understand how an organization's application is being experienced and how it is performing.

Wireless networks are not the same as your corporate LAN or MPLS network. You need to know what is required to enable your applications to work well in wireless networks. If your users are receiving a lousy response to a business app, it won't be long before they will find ways around it and that might impact policies around security i.e. storing data on their devices rather than going to a central repository.

Yes, it's obvious that for BYOD to work the application must be available for the device and secured from a corporate perspective. What's often overlooked is poor performance which ultimately will render the applications just as unusable as if they weren't available. So performance factors need to be attended too and as a large amount of these hinge on the unpredictability of the wireless and mobile networks, BYOD devices inevitably are forced to operate and applications perform within these networks.

Many organizations recognize that they must test properly in these types of networks. Network emulators are often the answer. Now, with BYOD this falls to everyone to do and this technology is not just available, but it's a sensible and cost effective solution in understanding how BYOD will work in your environment.

Network emulation covers all the characteristics and conditions of a wireless network, showing in real time how network and wireless conditions impact applications. Some emulators also offer the ability to profile an organization's own networked environment. This is really useful for an accurate view of how bespoke applications will be experienced by the BYOD device users.

BYOD offers benefits for company and users alike but make sure the business understands the limitations and build key applications to suit these challenging network conditions as there is no point in being secure if no one will use it!

Jim Swepson is Pre-sales Technologist at Itrinegy.

Related Links:

www.itrinegy.com

Share this

The Latest

October 17, 2019

As the data generated by organizations grows, APM tools are now required to do a lot more than basic monitoring of metrics. Modern data is often raw and unstructured and requires more advanced methods of analysis. The tools must help dig deep into this data for both forensic analysis and predictive analysis. To extract more accurate and cheaper insights, modern APM tools use Big Data techniques to store, access, and analyze the multi-dimensional data ...

October 16, 2019

Modern enterprises are generating data at an unprecedented rate but aren't taking advantage of all the data available to them in order to drive real-time, actionable insights. According to a recent study commissioned by Actian, more than half of enterprises today are unable to efficiently manage nor effectively use data to drive decision-making ...

October 15, 2019

According to a study by Forrester Research, an enhanced UX design can increase the conversion rate by 400%. If UX has become the ultimate arbiter in determining the success or failure of a product or service, let us first understand what UX is all about ...

October 10, 2019

The requirements of an APM tool are now much more complex than they've ever been. Not only do they need to trace a user transaction across numerous microservices on the same system, but they also need to happen pretty fast ...

October 09, 2019

Performance monitoring is an old problem. As technology has advanced, we've had to evolve how we monitor applications. Initially, performance monitoring largely involved sending ICMP messages to start troubleshooting a down or slow application. Applications have gotten much more complex, so this is no longer enough. Now we need to know not just whether an application is broken, but why it broke. So APM has had to evolve over the years for us to get there. But how did this evolution take place, and what happens next? Let's find out ...

October 08, 2019

There are some IT organizations that are using DevOps methodology but are wary of getting bogged down in ITSM procedures. But without at least some ITSM controls in place, organizations lose their focus on systematic customer engagement, making it harder for them to scale ...

October 07, 2019
OK, I admit it. "Service modeling" is an awkward term, especially when you're trying to frame three rather controversial acronyms in the same overall place: CMDB, CMS and DDM. Nevertheless, that's exactly what we did in EMA's most recent research: <span style="font-style: italic;">Service Modeling in the Age of Cloud and Containers</span>. The goal was to establish a more holistic context for looking at the synergies and differences across all these areas ...
October 03, 2019

If you have deployed a Java application in production, you've probably encountered a situation where the application suddenly starts to take up a large amount of CPU. When this happens, application response becomes sluggish and users begin to complain about slow response. Often the solution to this problem is to restart the application and, lo and behold, the problem goes away — only to reappear a few days later. A key question then is: how to troubleshoot high CPU usage of a Java application? ...

October 02, 2019

Operations are no longer tethered tightly to a main office, as the headquarters-centric model has been retired in favor of a more decentralized enterprise structure. Rather than focus the business around a single location, enterprises are now comprised of a web of remote offices and individuals, where network connectivity has broken down the geographic barriers that in the past limited the availability of talent and resources. Key to the success of the decentralized enterprise model is a new generation of collaboration and communication tools ...

October 01, 2019

To better understand the AI maturity of businesses, Dotscience conducted a survey of 500 industry professionals. Research findings indicate that although enterprises are dedicating significant time and resources towards their AI deployments, many data science and ML teams don't have the adequate tools needed to properly collaborate on, build and deploy AI models efficiently ...