Top ITOA Predictions for 2016

The ITOA Landscape’s 2016 ITOA Predictions list features exclusive quotes from the recently recognized IT Operations Analytics Leaders list (the ITOA50), as well as the leading analysts focused on ITOA. This collection provides insightful and bold predictions on how IT Operations Analytics (ITOA) will emerge and impact organizations in 2016.

2016 Will See Wider Deployments of ITOA

Operational efficiencies and the need to gain a deeper insight into the operation aspects of delivering IT will drive the demand for greater visibility and transparency, which is exactly what ITOA provides. Ovum predicts 2016 to represent the start of wider deployments of ITOA as organizations look for a competitive edge over rivals and analytics is the tool to provide this information. Ovum concludes that information and insights alone will not transform organizations, it also needs the people with the requisite skills to turn information into knowledge.

Roy Illsley
Principal Analyst, Ovum

Accuracy Will Be the Game Changer for ITOA

Accuracy is the game changer for ITOA in 2016. To do this, we need to collaborate across the organization to ensure our plans and metrics are driven by business and service outcomes. When we help the business balance the IT risk and health of the environment and in a business context, we simplify decisions, control costs, and communicate value.

John Miecielica
Director of Product Management, Teamquest

Analysis in ITOA Tools will Add Context

General operational analysis of machine data, without any understanding of the context and domain knowledge, has its limits.

I expect ITOA tools to blend multiple data sources and correlate them through the prism of change (change has been cited as a true root cause for most performance and availability issues). ITOA tools will be able to look into actual changes and inconsistencies throughout end-to-end IT environments down to the most granular level. Applying machine learning analytics, the next generation in ITOA tools will be able to look into this wide range of data and calculate the resulting risk for any change or difference. IT operations will be able to answer the most vital operational questions – which specific changes are responsible for an incident or which changes may result in performance and availability issues later. This way, IT operations teams will enjoy more actionable insights for slashing mean time to resolution and cutting the amount of incidents they face.

Sasha Gilenson
CEO, Evolven

Application Performance will be a Top Priority

In 2016, application performance will become a top priority for IT operations teams. Performance and IT operations analytics will become more important, becoming a discipline in and of itself and a unifying goal across IT teams. However, this means new capabilities are needed; namely, hybrid performance monitoring, performance analysis across the stack, wait-based analytics and multi-dimensional correlation of resources and events. In short, in 2016, the IT performance expert truly emerges.

Gerardo Dada
Vice President, SolarWinds

Automate Problem Detection and Remediation

With continued advancements in machine learning, systems will continuously learn from their own behavior and associate responses and behavioral patterns to suggest solutions and actions. This will automate problem detection and remediation, resulting in self-learning systems facilitating a pro-active management approach to IT Operations and business management, further reducing Total Cost of Ownership while increasing customer satisfaction.

Nima Homayoun
VP of Products and Strategy, Hewlett Packard Enterprise

Companies Will Feel Compelled to Deploy ITOA

It used to be that there was no such thing as ‘too much data.’ Now that we’re seeing more companies embrace the collection of data from every level of every component of their physical, virtual, and application infrastructures, it seems that some organizations do indeed have ‘too much data’ to analyze effectively using traditional approaches. Even those organization that attempt to be proactive by creating dashboards for every type of data they collect, are finding that unless some human opens the dashboard and looks at the data, then problems still go undetected, and they find themselves sliding back to a reactive IT operations posture.

2016 will be the year where these companies are compelled to deploy ITOA, enlisting the help of automated analysis techniques such as machine-learning-based anomaly detection and other behavioral analytics across their entire IT operations data store so they’ll never complain about ‘too much data’ again!

Mike Paquette
VP of Products, Prelert

Data-driven Decision Support Solutions Drive IT to Business

2016 is the year IT gets closer to the business through the use of data-driven decision support solutions. IT operations teams have the unique opportunity to offer analytics as a service to support the need for fast, accurate decision making, leveraging a data-independent analytics platform that applies machine learning and advanced analytics techniques, including historical and real-time information. This will increase the potential value of Digital Services and strengthen the relationship between IT and the business.

Bill Berutti
President of the Cloud, Data Center and Performance businesses, BMC

Evolution and Adoption of Micro Services

Perhaps the biggest disruption will be the continued adoption and evolution of micro services and containerization, which have really just started to become commodities. While micro services offer a lot of very compelling advantages, they also bring a new level of complexity to ITOA. The number of interacting components that make-up a system impacts all areas of troubleshooting, monitoring, logging, and debugging.

Sven Dummer
Senior Director of Product Marketing, Loggly

ITOA solutions Will Be More Intelligent with Machine Learning Analytics

In 2016, the market will be shaped by more organizations shifting towards truly cognitive capabilities. With IT challenges increasing and the funding and staffing to handle them decreasing, there will be a greater dependency on self-learning and self-healing. ITOA solutions will become more intelligent with their machine learning analytics, and they will extend that with more cognitive capabilities towards resolving IT Operational issues. There will be a significant increase in Cloud adoption of these capabilities, with many enterprises shifting away from traditional on-premises deployments.

Denny O'Brien
Program Director, IBM Operations Analytics Product Management, IBM

ITOA Solutions Will Enable “Autopilot” Model

In 2016 we’ll see ITOA solutions which enable more of an “autopilot” model similar to what we’re seeing in the car industry. Applications will be able to drive more seamlessly from private to hybrid and public cloud locations and the ITOA tools will provide their IT and business owners with a complete real time view of where they are located, how they’re built and what is impacting health and performance. In contrast to traditional ITOM models where IT must keep its hands on lots of individual bottoms-up charts and graphs from different tools this new model provides a holistic tops-down map driven view starting with the overall business process and drilling down to the lowest LUN and VLAN level in just a few clicks when needed.

Just as an auto-pilot car can predict and react to what is happening around it ITOA will converge and analyze vast amounts of historic and real time telemetry from across many different operational sources to enable applications to operate in a safer and more efficient manner. To make this possible ITOA will leverage the same highly scalable streaming analytics and visualization tools and techniques which are already in wide use by the consumer giants like Google, Twitter and LinkedIn.

Ben Eiref
Vice President of Marketing, FixStream, Inc.

ITOA Tools Will Enhance Pattern Discovery and Anomaly Detection

CIOs who are increasingly being measured on service availability and service delivery will drive demand for their ITOA products to augment collection and analysis of domain-specific time series data and unstructured data with metrics related to the end user's experience. As a result, ITOA tools will enhance capabilities in pattern discovery and anomaly detection for IT Ops with the ability to address change management and service level management use cases for CIOs to monitor the success of their strategic IT initiatives.

Mike Marks
Chief Product Evangelist, Aternity

ITOA Tools Will Incorporate Machine Learning

ITOA tools will incorporate machine learning to start to incorporate mid-level intelligence tasks, e.g. anticipating what the tool user wants to do and automatically do it for them (or at least prepare data and configuration ahead of what the user plans to do) - all to accelerate time to execute, scale operations in highly complex environments, and to reduce errors.

Rob Markovich
CMO, Moogsoft

ITOA tools Won't Require Extensive Human Interpretation

Over the last year, the potential of ITOA implementations has gained mindshare with CIOs. Currently, we are witnessing a market-wide shortage of analyst talent. The industry lacks experts that possess the knowledge and the experience to implement, configure and work with complex log consolidation tools. This means that new solutions need to work from day one, right out of the gate, with minimal configuration overhead. In 2016, the challenge will lie in the delivery of real value and out-of-box use-cases; ITOA tools that are able to deliver real business insights without the need for extensive human interpretation will stand a greater chance of success.

Matthew Carr
Business Development Manager, Savision

ITOA will Become Higher on the Agenda of the CTO and CIO

The importance of ITOA continues to grow in 2016 as more organizations understand the value in proactively monitoring their IT to ensure a smooth and continuous operation. With better analytics and technology available in the market, ITOA will become higher on the agenda of the CTO and CIO in 2016.

Mark Van Rijmenam
Founder, Datafloq

IT Gets Closer to Business Through Data-driven Decision Support Solutions

In 2016 ITOA will focus on the fundamentals – problem prevention and resolution for IT. Analytics will provide the prediction as the problem trend starts to form, and furthermore provide actionable recommendations. Users will either execute or tailor these actions, whether it’s to generate an IT ticket, or to restart a segment of a server farm.

Jin Zhang
Sr. Director of Analytics, CA Technologies

ITOA Will Move Beyond Operations

IT Operations Analytics' will continue to move beyond "operations" to deliver critical value for IT service management, development, IT executive stakeholders and business stakeholders. This is because advanced IT analytics (AIA) are increasingly providing a layer of insight to support multiple use cases such as performance, user experience, business impact, change management financial optimization and IT operational efficiencies. As such, AIA is becoming a critical investment not only for solving problems more quickly and effectively, but also for transforming how IT organizations work across domains, and how they support and interact with relevant business stakeholders.

Dennis Drogseth
Vice President, EMA

ITOA Will Optimize Workload Patterns for Public Cloud Applications

Businesses move to the public cloud to avoid upfront capital expenditure, eliminate the expense associated with administering physical servers, and to scale up and down according to their workload requirements. However, the vast majority of businesses are significantly over-provisioned in their use of public cloud resources, resulting in a high monthly expense that undermines the original business case. The reasons for being over-provisioned are two-fold: Firstly, some applications are not architected to take advantage of horizontally-scalable micro-services that lend themselves to auto-scaling; the second reason stems from under-estimating the complexity of measuring and analyzing the multiple dimensions of capacity utilization (CPU, memory and I/O by resource type) and variations in pricing contracts (reserved, on-demand, spot instances.)

The public cloud platforms such as Amazon Web Services (AWS) have the APIs necessary to allow analytics service providers help right-size public cloud resources with confidence. A new generation of IT Operations Analytics (ITOA) will optimize contract types against workload patterns, and detect the need for increase or decrease capacity in real-time based on performance analysis.

Bob Farzami
CEO, Netuitive

Leverage ITOA to Make Business Decisions in Real-time

One of the most common questions asked of IT professionals is, “What keeps you up at night?” While the categories for concern may not have changed, the urgency to find solutions has never been greater.

A sense of urgency helps organizations recognize the need for change, either to take advantage of new opportunities or to deal with issues negatively impacting the business. This is part of a change management process, and it is important to ensure everyone in the organization understands the need for the change and the importance of acting immediately. The ability to leverage ITOA to make the right business decisions in real-time, based on accurate and factual data, is key to aligning IT with the business.

Poul Nielsen
CMO, Nexthink

Log Management will Emerge as the Most Underrated Opportunity for ITOA

Thinking about log data may seem too far in the weeds for most tech industry professionals. However, using IT Operations Analytics to monitor, manage and gather insights from logs will be the only near-perfect way to make sense of the increasingly complex and cloud-based architectures. Soon, we’ll see more vendors trying to move into the log management space, and more organizations trying to use log management to make sense of their big data mess.

Christian Beedgen
Co-founder and CTO, Sumo Logic

New Generation of Layered ITOA Architectures

In 2015 we saw streaming analytics gaining momentum for ITOA use cases such as real-time anomaly detection. As the number of metrics continues to increase, resulting from more distributed application environments, we expect a new generation of layered ITOA architectures to appear. Much like edge analytics is being applied to IoT for scalability purposes, we will see intelligent processing and analysis of data closer to their origin, for example on the collection agent. In addition, we will see layered harvesting of forensic data, where first-line metrics are gathered for problem detection, supplemented by cognitive models and intelligent algorithms to decide the type of second-line data to collect for further triage and root cause analysis.

Peter Arijs
Principal Product Specialist, CoScale

Predictive Analytics To Take Center Stage for Infrastructure Monitoring

This year, we are going to see predictive analytics take center stage for infrastructure monitoring. Rather than being in a reactionary mode, IT teams will now be able to access more data-points and real-time analytics than ever before to help them understand what is happening now and to accurately forecast what will happen in their businesses over time. Predictive analytics will help businesses improve efficiency and up-time which will stimulate long-term growth. Data centers will now be able to closely monitor everything from primary servers to PDUs and HVAC systems to cameras and electronic door locks to identify issues before they become too costly.

Brandon Witte
CEO, Sightline Systems

Predictive ITOA will Generate Insights that will Impact Operations

Predictive ITOA will generate insight that will require operations teams to think differently as their existing processes, based on past events, won’t deal well with future events. In turn this will cause organizations to re-evaluate their attitude to risk. With this insight organizations will need to divert more resource into preventative rather than restorative IT activities.

Operational Analytics will be deemed an essential IT function by risk teams as a means of mitigation. In the same way as techniques such as Monte-Carlo modelling have been used to protect investment funds, IT operations teams will be tasked and rewarded for issue avoidance rather than issue resolution.

Peter Duffy
CTO, Sumerian

Renaissance of Business Service Management

Based on the Agile Data Centre and DevOps uptake we’ve observed in large enterprises through 2015, we expect the auto-discovery "trawl" as a product discipline to become less critical in many organizations. This is due to the emergence of provisioning tools supporting open APIs that can be leveraged to update IT service dependency maps, configuration management databases (CMDBs) and as an enabler for the Service Knowledge Management System (SKMS). Why discover changes in the IT infrastructure after-the-fact when you can maintain a baseline and be notified of changes to the infrastructure in near real-time as they occur?
The emergence of provisioning tools that can be leveraged to update IT service dependency maps and CMDBs without manual intervention as they provision systems will also lead to the renaissance of Business Service Management (BSM) in 2016 as this overcomes some of the maintenance burden traditionally associated with service visualisation and dependency mapping.

Grant Glading
Head of Sales and Marketing, Interlink Software

Use of Predictive Analytics will Expand

Today, ITOA market activity is weighted toward log analysis as IT organizations seek to radically reduce the time needed to discover and resolve root causes of incidents and outages. Use of predictive and application analytics will grow In the future as IT organizations become familiar and confident with using log analysis and move toward adopting more proactive measures to prevent service slowdowns and outages.

Tim Grieser
Program Vice President within the Enterprise System Management Software group IDC

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