A few years ago organizations around the world were discussing their migration to the cloud. Now that many of them have moved over what is next? ERIK ZANDBOER, Advisory Specialist EMEA at Dell EMC, shares his thoughts on where the cloud market is headed.
Go back a few years and cloud was very different. It mainly existed in name, hanging on the lips of vendors and the IT channel. Today that has flipped nearly 180 degrees…
“When we started talking about cloud, we spoke about the journey to the cloud. Everyone wanted to get there and nobody knew how. There were all kinds of definitions for cloud. Many people built things they called cloud, but it wasn’t cloud at all. Nowadays we see a shift. It’s the complete opposite. Customers are actually pulling for features. Now we hear ‘Why can’t you support X, because that’s simple.’ Initially we dragged customers, now they are dragging us!”
So says Erik Zandboer, Advisory Specialist EMEA at Dell EMC. While visiting South Africa, he shared his views on where the cloud market stands and is headed.
Cloud is quickly becoming the baseline for current and future technology investment and the reason is simple: cloud represents the rapid commoditization of IT infrastructure. The combination of distributed computing and high-speed connectivity is drastically reducing the cost of raw bit-crunching power, diminishing barriers of entry to such a degree that participating on a cloud platform is the equivalent of a personal (and affordable) supercomputer. Cloud is to industrial-scale computing what the smartphone is to the desktop computer. As a result anyone who wishes to remain relevant are building their applications and solutions in the cloud.
Fortunately the business is not ignorant and many large companies are already exploring the next stages of cloud adoption:
“They are looking at this cloud native stuff. It looks very promising and interesting. It’s way easier to deploy anywhere. You can deploy services to multiple clouds and just connect them together. As long as the microservices can find each other over the network, the application will work. That’s a whole other mode of operation and a lot of companies are willing to go in that direction. There are a lot of questions around Openstack, cloud native, devops and such things.”
Companies are starting to take ownership of this new methodology, jumping between their own exclusive private clouds and robust public clouds as project requirements change:
“We see companies that do development in their private data centres, and when they need to scale it out, they go to a public provider. We also see other companies do the exact opposite: developing in Amazon or similar, because it is so easy and flexible, then running their production on private cloud because most of the time it’s cheaper.”
Eventually workloads – the live versions of apps and data – will dynamically shuttle between various clouds, finding the best and most cost-effective platform for the job. Zandboer says this is already happening with VMware solutions:
“We see that with vCloud Air. You move your workload with very limited downtime from on-premise to off-premise and the other way around. There are complications: you need a low latency, high bandwidth network. The moment you move your workload, it needs to work. So there are a lot of implications. But VMWare is making great strides there.”
Zandboer is confident that in a few years this type of automation will be widespread. Companies will finally get rid of the headache of IT infrastructure they don’t need: “That would be very cool: to have a cloud marketplace and your workloads bound to SLAs, and a system looking at the SLA and the app, assigning the cloud that matches and is cheapest. That’s the ultimate dream for many.”
We aren’t there yet, which is why companies such as VMware and Dell EMC focus on creating seamless hardware and software environments. But that is the future of cloud: a world where infrastructure is irrelevant and the performance of business applications are all that matter.
Data gives coaches new eyes in sports
Collecting and analysing data is entering a new era as it transforms both coaching and strategy across sports ranging from rugby to Formula 1, writes ARTHUR GOLDSTUCK
Coaches and managers have always been among the stars of any sports. They become household names as much as the sports heroes that populate their teams. Now, thanks to the power of data collection and analysis, they are about to raise their game to unprecedented levels.
The evolution of data for fine-tuning sports performance has already been experienced in Formula 1 racing, baseball and American football. All are known for the massive amount of statistic they produce. Typically, however, these were jealously guarded by coaches trying to get an edge over their rivals. Thanks to the science of “big data”, that has changed dramatically.
“American baseball has the most sophisticated data science analytics of any sports in the world because baseball has this long history of stats,” said Ariel Kelman, vice president of worldwide marketing at Amazon Web Services (AWS), the cloud computing giant that is working closely with sports teams and leagues around the world. “It’s an incredibly opaque world. I’ve tried for many years to try and get the teams to talk about it, but it’s their secret sauce and some of these teams have eight, nine or ten data scientist.”
In an interview during the AWS Re:Invent conference in Las Vegas last week, Kelman said that this statistical advantage was not lost on other sports, where forward-thinking coaches fully understood the benefits. In particular, American football, through the National Football League there, was coming on board in a big way.
“The reason they were behind is they didn’t have the player tracking data until recently in in the NFL. They only had the player tracking data three years ago. Now the teams are really investing in it. We did an announcement with the Seattle Seahawks earlier this week; they chose us as their machine learning, data science and cloud provider to do this kind of analysis to help figure out their game strategy.
“They are building models predicting the other teams and looking at players and also evaluating all their practices. They are setting up computer vision systems so that they can track the performance of the players during their practices and have that inform some of the game strategies. The teams then even talk about using it for player evaluation, for example trying to figure out how much should we pay this player.”
Illustrating the trend, during Re:Invent, Kelman hosted a panel discussion featuring Rob Smedley, a technicalconsultant to Formula 1, Cris Collinsworth, a former professional footballer in the NFL and now a renowned broadcaster, and Jason Healy, performance analytics managerat New Zealand Rugby.
Healey in particular represents the extent to which data analysis has crosses sporting codes. He has spent four yearswith All Blacks, after 10 years with the New Zealand Olympic Committee, helping athletes prepare for the OlympicGames.
“The game of rugby is chaos,” he told the audience. “There’s a lot of a lot of things going on. There’s a lot of trauma and violence and it can be difficult to work out the load management of each player. So data collection is a big piece of the technical understanding of the game.
“A problem for us in rugby is the ability to recall what happened. We have to identify what’s situational and what’s systemic. The situational thing that happens, which is very unlikely to be replicated, gets a lot of attention in rugby. That’s the sensational big moment in the game that gets talked about. But it’s the systemic plays and the systemic actions of players that lies underneath the performance. That’s where the big data starts to really provide some powerful answers.
“Coaches have to move away from those sensational andsituational moments. We’re trying to get them to learn what is happening at that systemic level, what is actually happening in the game. How do we adjust? How do we make our decisions? What technical and defensive strategies need to change according to the data?”
Healey said AWS was providing platforms for tracking players and analysing patterns, but the challenge was to bring people on this technology journey.
“We’re asking our coaching staff to change the way they have traditionally worked, by realising that this data does give insights into how they make their decisions.”
Kelman agreed this was an obstacle, not just in sport, but in all sectors.
“Across all of our customers, in all industries, one of the things that’s often underestimated the most is that getting the technology working is only the first step. You have to figure out how to integrate it with the processes that us humans, who dislike change, work with. The vast majority of it is about building knowledge. There’s ways to transfer that learning to performance.”
Of course, data analytics does not assure any side of victory, as the All Blacks discovered during the recent Rugby World Cup, when they were knocked out in the semi-finals, and South Africa went on to win. We asked Healey how the data-poor South Africans succeeded where the data-rich All Blacks couldn’t.
“You have to look at how analytics and insights and all thesetechnologies are available to all the coaches these days,” he said. The piece that often gets missed is the people piece. It’s the transformation of learning that goes into the player’sactual performance on the field. We’re providing them with a platform and the information, but the players have to make the decisions.. We can’t say that this particular piece of technology played a role in winning or losing. It’s simply just a tool.”
The same challenge faces motor racing, which generates massive amounts of data through numerous sensors and cameras mounted in vehicles. Rob Smedley, who spent 25 years working in engineering roles for Formula 1 teams, quipped that his sport had a “big data” problem before the phrase was invented.
“We’ve always been very obsessive about data. Take car telemetry, where we’ve got something like 200 to 300 sensors on the car itself. And that goes into something like two to three thousand data channels. So we’re taking about around 600 Gigabytes of data generated every single lap, per car.
“On top of that, where we’ve also got all the time data and GPS data. The teams are using it for performance advantage. We’re into such marginal gains now because there are no bad teams in Formula 1 anymore. Data analytics provide those marginal gains.”
• Arthur Goldstuck is founder of World Wide Worx and editor-in-chief of Gadget.co.za. Follow him on Twitter and Instagram on @art2gee
IoT faces 5-year gap
In five years, the world will have more than 40 billion devices. Locally, IoT specialist,Eseye, says that South African CIOs are recognising IoT (Internet of Things) and M2M (Machine to Machine) technologies as strategic imperatives, but the journey is still in its infancy.
“As legacy systems start to reach end of life, digital shifts will become inevitable. This, coupled with an increasing demand for improved bottom line results from existing and new markets, makes IoT a more viable option over the next five years. This is particularly prevalent in manufacturing, especially where time to market and product diversification has become necessary for business survival,” says Jeremy Potgieter, Regional Director – Africa, Eseye.
He says that within this sector one thing matters – output: “Fulfilling the product to market lifecycle is what makes a manufacturer successful. Addressing this functionality and production optimisation through technology is becoming more critical as they focus on increasing output and reducing downtime. By monitoring machinery and components in the production line, any concerns that arise, which impacts both the manufacturer and consumers alike, will be more efficiently dealt with by using an IoT approach.”
Potgieter says that there is also the growing strategic approach to increase the bottom line through new markets. As manufacturers seek new revenue streams, Eseye is encouraging the use of rapid IoT enabled device product development : “By addressing the connectivity aspects required at deployment, manufacturers are immediately diversifying their portfolios. Eseye, as an enabler, assists by providing market ready SIMs, which can be embedded into IoT connected devices at OEM level, connecting them to a plethora of services (as designed for) upon entry to market, anywhere in the world.”
In addition, Potgieter says that organisations are increasingly looking towards IoT connectivity managed services to capitalise on specialist expertise and ensure the devices are proactively monitored and managed to ensure maximum uptime, while reducing data costs.
Impacting IoT adoption though, is undoubtedly the network infrastructure required. Potgieter says that this varies significantly and will depend on criteria such as sensor types and corresponding measurements, the overall communication protocols, data volume, response time, and analytics required: “While the majority of IoT implementations can be enabled using cloud-based IoT platform solutions, the infrastructure required still remains important. A cloud platform will simplify infrastructure design and enable easy scaling capability, while also reducing security and data analytics implementation issues.”