Welcome!

@ThingsExpo Authors: Zakia Bouachraoui, Elizabeth White, Liz McMillan, Pat Romanski, Yeshim Deniz

Related Topics: @CloudExpo, Java IoT, Linux Containers, @DXWorldExpo, @ThingsExpo, @DevOpsSummit

@CloudExpo: Article

AI and Analytics | @BigDataExpo #ML #IoT #BigData #DigitalTransformation

Artificial intelligence (AI) is finally coming into its own and beginning to demonstrate significant business value

How Artificial Intelligence Is Transforming IT Operation Analytics

After many years of research, misfires and frightening Hollywood plotlines, artificial intelligence (AI) is finally coming into its own and beginning to demonstrate significant business value. The combined forces of big data, human expertise and AI are being used across industries as diverse as healthcare and manufacturing, as well as within all aspects of business. IT operations is one area that AI is beginning to contribute to enormously.

IT infrastructures are changing rapidly today, particularly hybrid cloud environments. While they are increasingly dynamic and agile, they are also extraordinarily complex. Humans are no longer able to sift through the variety, volume and velocity of Big Data streaming out of IT infrastructures in real time, making AI - especially machine learning - a powerful and necessary tool for automating analysis and decision making. By helping teams bridge the gap between Big Data and humans, and by capturing human domain knowledge, machine learning is able to provide the necessary operational intelligence to significantly relieve this burden of near real-time, informed decision-making. Industry analysts agree. In fact, Gartner named machine learning among the top 10 strategic technologies for 2016, noting "The explosion of data sources and complexity of information makes manual classification and analysis infeasible and uneconomical."

However, the current state of IT Ops is that the domain experts - typically IT administrators, IT operators for TechOps and Site Reliability Engineers (SRE) for DevOps - must manually gather this disparate information and apply their domain expertise in an attempt to make informed decisions. While these professionals are great at what they do, trying to analyze so much data from multiple tools leaves the door wide open for human error. On the other hand, analytics that are based on machine learning are quickly becoming a necessity to ensure the availability, reliability, performance and security of applications in today's digital, virtualized and hybrid-cloud network environments.

Historically, these domain experts have used multiple tools, each which monitored a specific element of the system and provided them with information about their network, virtual and physical infrastructure and application performance. While these tools provide pieces of the puzzle, they offer a narrow view of the IT infrastructure and, therefore, only one aspect of the tool chain. The other aspect is service desk tools that manage tickets and change management. Humans more often than not bridge this gap between the siloed monitoring tools of yesterday and service desk applications with their domain expertise.

What Modern Analytics Can Do
Because today's TechOps and DevOps environments are so complex, there is a need to automate, learn and make intelligent, informed decisions based on real-time analysis of Big Data arising out of the entire application infrastructure stack. Following are key analytics for IT operations:

  1. Behavior Profiling - This type of analytics understands the behavior profile of each and every metric, how that flows into the object behavior and then how the object behaviors relate to other object behaviors across the hybrid cloud environment. It is a multi-dimensional problem, and understanding and adapting to "normal" behavior is extremely important.
  2. Anomaly Detection - This is the bedrock of what is typically referred to as diagnostic analytics. Best-of-breed machine learning algorithms should be able to look at contextual, historical and sudden changes in the behavior of objects to detect anomalies. Understanding when there is a real anomaly and more importantly, when there is not, is critical to avoid generating false alarms.
  3. Topology Analysis - Topology is something every IT administrator or SRE should be aware of. This is the understanding of the hierarchal, peer-to-peer and temporal relationship between hybrid cloud elements. This type of analysis should be able to self-learn the inter-relationships of objects and the impact of their performance on one another. Learning those relationships and maintaining that understanding in order to spot trouble in time is extremely important for both TechOps and DevOps environments.
  4. Root Cause - With the ability to zero in on the cause and impact of an incident, root-cause analysis fast-tracks the resolution and reduces mean time to repair substantially.
  5. Predictive - As the name implies, analytics of this kind help operators identify early indicators and provide insights into looming problems that may eventually lead to performance degradation and outages.  Predictive analytics are also good at providing early insights into anomalies to better plan for what's ahead.
  6. Prescriptive - These analytics provide insight-driven recommendations to remediate an incident. These recommendations should capture tribal knowledge gathered over the years in the organization, best practices in the industry and may even be crowd-sourced to capture state-of-the-art knowledge. These analytics provide the opportunity to finally close the loop in automated IT Operations Management.

Real Monitoring Intelligence
The modern IT environment has gone far past the point of staff being able to effectively

react to incidents as well as trying to resolve them after they have spun out of control. Instead, AI provides technologies to help automate many of these tasks in order to handle incidents in advance. The whole notion of automating IT operational tasks, as well as preventing outages in the first place, and getting to the root cause quickly and in an automated way is the next frontier in remediating these issues.

Monitoring data is critical for identifying, predicting and preventing incidents - and it's something humans can no longer do. DevOps and TechOps teams already have so much on their plates that they cannot possibly devote the time needed to address every alert and analyze the masses of data constantly being generated. And today, they don't have to. Artificial intelligence is able to see past siloes for a deep view across the application stack to provide the analytics that help keep apps up and running at desired service levels.

More Stories By Akhil Sahai

Dr. Akhil Sahai is an accomplished management and technology leader with 25+ years of experience at large enterprises and at startups. He came to Perspica from HP Enterprise where as Sr. Director of Product Management, he envisaged, planned and managed the Solutions Program. At Dell, as Director of Products, Akhil led Product Strategy and Management of Dell’s Converged Infrastructure product line. He also led Gale Technologies, as VP of Products to its successful acquisition by Dell.

Prior to that, at Cisco he undertook business development for VCE Coalition, and at VMware, he managed global product strategy and management for vCloud Software with focus on applications, and Virtual Appliances product line.

He has published 80+ peer-reviewed articles, authored a book, edited another, and chaired multiple International IEEE/IFIP Conferences. He has filed 20 technology Patents (with 16 granted). He has a Ph.D. from INRIA France and an MBA from Wharton School.

Comments (0)

Share your thoughts on this story.

Add your comment
You must be signed in to add a comment. Sign-in | Register

In accordance with our Comment Policy, we encourage comments that are on topic, relevant and to-the-point. We will remove comments that include profanity, personal attacks, racial slurs, threats of violence, or other inappropriate material that violates our Terms and Conditions, and will block users who make repeated violations. We ask all readers to expect diversity of opinion and to treat one another with dignity and respect.


IoT & Smart Cities Stories
René Bostic is the Technical VP of the IBM Cloud Unit in North America. Enjoying her career with IBM during the modern millennial technological era, she is an expert in cloud computing, DevOps and emerging cloud technologies such as Blockchain. Her strengths and core competencies include a proven record of accomplishments in consensus building at all levels to assess, plan, and implement enterprise and cloud computing solutions. René is a member of the Society of Women Engineers (SWE) and a m...
Andrew Keys is Co-Founder of ConsenSys Enterprise. He comes to ConsenSys Enterprise with capital markets, technology and entrepreneurial experience. Previously, he worked for UBS investment bank in equities analysis. Later, he was responsible for the creation and distribution of life settlement products to hedge funds and investment banks. After, he co-founded a revenue cycle management company where he learned about Bitcoin and eventually Ethereal. Andrew's role at ConsenSys Enterprise is a mul...
In his general session at 19th Cloud Expo, Manish Dixit, VP of Product and Engineering at Dice, discussed how Dice leverages data insights and tools to help both tech professionals and recruiters better understand how skills relate to each other and which skills are in high demand using interactive visualizations and salary indicator tools to maximize earning potential. Manish Dixit is VP of Product and Engineering at Dice. As the leader of the Product, Engineering and Data Sciences team at D...
Dynatrace is an application performance management software company with products for the information technology departments and digital business owners of medium and large businesses. Building the Future of Monitoring with Artificial Intelligence. Today we can collect lots and lots of performance data. We build beautiful dashboards and even have fancy query languages to access and transform the data. Still performance data is a secret language only a couple of people understand. The more busine...
Nicolas Fierro is CEO of MIMIR Blockchain Solutions. He is a programmer, technologist, and operations dev who has worked with Ethereum and blockchain since 2014. His knowledge in blockchain dates to when he performed dev ops services to the Ethereum Foundation as one the privileged few developers to work with the original core team in Switzerland.
Whenever a new technology hits the high points of hype, everyone starts talking about it like it will solve all their business problems. Blockchain is one of those technologies. According to Gartner's latest report on the hype cycle of emerging technologies, blockchain has just passed the peak of their hype cycle curve. If you read the news articles about it, one would think it has taken over the technology world. No disruptive technology is without its challenges and potential impediments t...
If a machine can invent, does this mean the end of the patent system as we know it? The patent system, both in the US and Europe, allows companies to protect their inventions and helps foster innovation. However, Artificial Intelligence (AI) could be set to disrupt the patent system as we know it. This talk will examine how AI may change the patent landscape in the years to come. Furthermore, ways in which companies can best protect their AI related inventions will be examined from both a US and...
Bill Schmarzo, Tech Chair of "Big Data | Analytics" of upcoming CloudEXPO | DXWorldEXPO New York (November 12-13, 2018, New York City) today announced the outline and schedule of the track. "The track has been designed in experience/degree order," said Schmarzo. "So, that folks who attend the entire track can leave the conference with some of the skills necessary to get their work done when they get back to their offices. It actually ties back to some work that I'm doing at the University of San...
When talking IoT we often focus on the devices, the sensors, the hardware itself. The new smart appliances, the new smart or self-driving cars (which are amalgamations of many ‘things'). When we are looking at the world of IoT, we should take a step back, look at the big picture. What value are these devices providing. IoT is not about the devices, its about the data consumed and generated. The devices are tools, mechanisms, conduits. This paper discusses the considerations when dealing with the...
Bill Schmarzo, author of "Big Data: Understanding How Data Powers Big Business" and "Big Data MBA: Driving Business Strategies with Data Science," is responsible for setting the strategy and defining the Big Data service offerings and capabilities for EMC Global Services Big Data Practice. As the CTO for the Big Data Practice, he is responsible for working with organizations to help them identify where and how to start their big data journeys. He's written several white papers, is an avid blogge...