case study or frenetic rider activity , including crashes in the peloton .
The Dimension Data solution enabled ASO to ramp up new environments rapidly , scale technology platforms up or down on demand , and respond to changes or new requirements almost immediately . ASO wasn ’ t required to make large capex investments in depreciating technology assets ; Dimension Data ’ s cloud based solution was simply ‘ put into hibernation ’ until the next cycling race .
Dimension Data ’ s Big Data Truck – a fully mobile data centre – located in the technical zone near the finish line of each stage .
Every day after the end of each stage of the race , Dimension Data ’ s Big Data Truck was driven to the next stage . In total , the truck travelled 4,892.5km during the 2016 race , spending 80 hours on the road .
In 2015 , the data was made available to commentators , the media and fans via a beta version of a live tracking website , which was developed to support 17 million views and up to 2,000 page requests per second , while also being optimised for Apple , Android and other mobile devices . The website , coupled with the live data feeds over social media , enabled ASO to provide a richer and more relevant viewing experience to modern cycling viewers and fans . One important additional consideration around the live data feeds is cyber security . Hosting in the Dimension Data cloud ensures the data is kept secure , and encrypted connectivity allows the race information to be transmitted to broadcasters , the media , the teams and viewers in a secure way .
During the 2015 race , the solution was enhanced many times . To ensure optimal performance , Dimension Data ’ s team on the ground collaborated with support teams situated in Australia , India and the US , using live video , chat feeds and other collaborative tools to continuously enhance and improve the platform . Having teams in multiple time zones enabled Dimension Data to take a round-the-clock development and testing approach to adapt the solution during and after each stage throughout the monthlong Tour .
With the eyes of the world on the race , it had to ensure the solution was both secure and fail-proof , with 100 per cent uptime during the race stages . This was no mean feat in remote environments , such as mountain top finishes or Cols , or during times of bad weather
Enhancements for the 2016 Tour A number of significant improvements have been made to the solution since the 2015 Tour de France . For example , in 2016 , a VCE VxRail enabled virtual SAN solution was added into the mobile data centre for redundancy . In addition to being easy to use and set up , VxRails take up far less space , meaning that the solution can be operated with only half a rack , making hardware more stable and removing risk in the stack when in transit .
The upgraded solution has reduced complexity in the network and in its compute and storage , with the aim of being more operationally efficient . The set up and shutdown process at the start and end of each stage was also reduced by at least 20 minutes each day , sometimes saving as much as an hour a day .
In 2016 , the transmission range of the solution was also enhanced , giving a 10-fold increase over the previous year . This meant fewer dropouts or ‘ gaps ’ in race data , seamless communication and continuity throughout the race .
Dimension Data ’ s Big Data Truck was equipped and set up so that it
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