EMA Research Blog: Navigating IT and Security Horizons

The EMA Top 3 report for Container Management and DevOps in Production and at Scale is a curated collection of a large number of data points that reflect individual priorities, pain points, technology adoption patterns, requirements, opinions, and so on, of 300 enterprises. It then dives deeper into these individual data points to provide readers with enough context to inform their technology selection process to some degree. However, each reader needs to pick out the nuggets that are the most relevant to him or her and then draw her own conclusions. Look at it this way: the EMA Top 3 polls 300 of your peers on 58 container and DevOps related questions and you can learn from the answers without having 300 separate conversations.

Everyone wants to talk about how analytics is the future of network engineering and operations. The phrase “network analytics” is used by vendors of various stripes to imply that a particular technology is smarter and better than the average solution.

Enterprise networking professionals have a cloud problem, even if they don’t know it. Software-defined WAN (SD-WAN) solutions can help them solve this problem.

Why Machine Learning Diagnoses Cancer but Can’t Run our Hybrid Cloud

Neural Networks Are Key in 2018

Neural networks are back, but please don’t think they are able to emulate the context awareness of the human brain. Don’t get me wrong, I believe that the neural network approach is a viable one, but we do need to be clear about its limitations. All of these limitations are rooted in the limited 'worldview' the neural network is able to take in. This worldview is limited as it relies on a human being with limited time and knowledge creating the neural network topology by providing the following components and enough sample data for the machine to determine how input should be processed.

My constant search for the next ‘cool’ tech toy or app is inspired by my obsession for automation. Trying to teach my 4 and 6 year old kids to think of creative solutions for their repetitive problems (no, there’s not yet a robot that cleans their rooms) surfaced the following 3 top toys and top apps in 2017.

Digital attackers in 2018 need to focus on one key challenge: “how do I deliver the best possible value to my clients, without significantly increasing cost.“

In 2017, CEOs arrived at the conclusion that machine learning and artificial intelligence (ML / AI) will be critical to unlock competitive advantages in the future. However, most enterprises had very little understanding of exactly what is possible today and how much value the investment in various ML / AI technologies can bring. Here are my six key recommendations for 2018:

Now that I’ve predicted that in 2018 machine learning will be available to ‘average Joe developer,’ let me share my experience from this weekend. Note that I’m not trying to be a ‘cool geek’ by doing some hands on work (I’m way too old to still be cool), but based on all the machine learning and artificial intelligence buzz in 2017, I thought my use case should be quick, simple, and most importantly solving a problem that could otherwise not be solved.

For readers who would like to see what happened to our 2017 predictions, please take a look. Jens Soeldner and the EMA Team sat down again this month to look into the crystal ball for 2018.