SIMULCATION BLOG

There are 8.4 billion connected ‘things’ in use in 2017, according to tech researchers Gartner – up 31% on 2016. In response, over 80% of IT teams want their datacenters to be more reliable and available to handle the pace of growth in IoT. By moving processing to the edge of the network, organizations can combat latency by reducing traffic on the primary network, enabling faster, more efficient decision-making. So, what is edge computing, and how can CIOs ensure their datacenters are ready? Edge computing vs the Cloud Edge computing is where data processing takes place at the edge of a network instead of in the cloud or a centralized datacenter. Edge devices capture streaming data that could be useful in preventing failures, optimizing performance, and dealing with hardware defects without delay. For instance, the device could be a smartphone collecting data from other devices before sending it into the Cloud. In reality, edge computing and the Cloud work regularly in ta...

A quick google of the terms ‘gamification’ and ‘game-based learning’ turns up a surprising lack of clarity about what these terms mean – and, crucially, whether they work. They’re real buzzwords of the moment, and share the common ground of implementing the mechanics of ‘gaming’ to enhance learning, or encourage changes in behavior. Used in everything from marketing strategy to HR policies, various studies have shown the benefits of using ‘gamified systems’. IT staff are perhaps closer than most to the technology that’s shaping how game design and game interaction is revolutionizing professional education. So, what is it, and can these concepts help to cut through some of the current problems with learning new systems and processes for datacenter managers and CIOs? What’s the difference between gamification and game-based learning?   ‘Gamification is using game-based mechanics, aesthetics, and game-thinking to engage people, motivate action, promote learning, and so...

Thanks to our increasing dependence on technology, the growth in Big Data and the Internet of Things, reliability of hardware and software is more crucial than ever. Together, they form the foundation for an organization’s Line of Business (LOB) applications and provide the critical stability needed to support ‘always on’ physical, cloud and Edge environments. So, what do the current risks look like, and how can we learn to mitigate them? Hardware is getting more reliable As reliance increases, server hardware and operating systems are getting more robust, as a recent survey by consultants ITIC testifies . They found that market leading IBM z Systems Enterprise servers had just eight seconds of ‘blink and you’ll miss it’ downtime a month on average. Hardware may be getting more resilient, but that doesn’t mean that datacenter outages are falling – and, with our ever-increasing reliance on connectivity, their effects are getting more catastrophic. Denial of Service (DoS) ...

The Internet of Things (IoT) is predicted to encompass 50 billion units by 2020 , generating more than $1.9trillion over the next six years alone. To put that into context, estimates suggest there are only two billion Windows PCs in the world right now. From wearables to smart fridges, the IoT is expected to take off in a big way. IoT presents an unparalleled opportunity for both businesses and consumers by generating real-time information that can improve usability and productivity. However, it also creates new challenges for datacenter managers and CIOs to navigate, including balancing the need for real-time analytics against security and capacity. Are you IoT ready? Here are four ways it is already shaking up the industry: Capacity The more devices connected, the more consumers using applications, and the more devices learn and adapt to the user, the more data will be generated. That presents a headache for DCMs when anticipating storage management and capacity on ...

Failure is an undeniably painful thing, but it’s often described as the driving force behind success. Thomas Edison famously wrote: ‘ I have not failed. I've just found 10,000 ways that won't work,’ proposing that innovation is forged in the fires of numerous mistakes. For datacenter managers, mistakes can be particularly costly. With high-ticket hardware and expensive service contracts, you must walk a fine line between finding the optimum mix to satisfy your customers and maintaining safety, security and zero downtime. That’s where the science behind simulations could come in, helping you to try out new components and model your decisions before making the plunge in reality. Let's uncover how it all works. Let dissatisfaction drive you Numerous research studies into the value of experiential learning methods – including simulations – suggest that mistakes are a crucial part of the learning process. Professional development (learning for work) can be experie...

Managing a datacenter is more than simply a question of knowledge. With ever-increasing demands for more data from end users and pressure from organizations to make savings in the name of greater efficiency, DCMs must constantly adapt their skills and competencies. Let’s look at five key personal skills recommended by industry recruiters. 1.      Self-motivation and commitment Datacenter managers should be proactive in seeking out new ways to improve their datacenter and its staff, thinking beyond any immediate pressing needs. They should also be highly aware of everything that’s happening in their facility to keep pace with problems when they happen. 2.      Great communication and leadership The datacenter manager should be the glue between the IT facility and the customer or end user. Poor communication is all too often a stumbling block to progress, and can hamper a swift response during customer downtime. Then there’s your st...