Algorithmic IT Operations Drives Digital
April 13, 2017
2019, 25% of global enterprises will have
strategically implemented an AIOps platform
supporting two or more major IT operations
Ahead of the Gartner IT Infrastructure,
Operations and Data Center Summit in Mumbai
in May, we asked Pankaj Prasad, principal
research analyst at Gartner, about trends
and developments in algorithmic IT
operations, and what Indian organizations
should be focusing on this year.
Q. What is algorithmic IT operations (AIOps)?
A. AIOps platform technologies comprise of
multiple layers that address data
collection, storage, analytical engines and
visualization. They enable integration with
other applications via application
programming interfaces (APIs) allowing for a
vendor-agnostic data ingestion capability.
AIOps platforms can thus seamlessly interact
with IT operations management (ITOM)
toolsets because of the ability to deal with
data from any tool irrespective of the data
Q. How is AIOps different from data
A. Over the past 4-5 years IT organization
teams involved in availability and
performance management have made increasing
use of big data and machine assisted
analytics for improving diagnostic and
troubleshooting capabilities of their teams.
While the broader data analytics is
concerned with use-cases and models that
will be based on an organization’s unique
needs, AIOps platform technologies are
designed for typical IT operations use case
which mainly involves:
1.Post-processing of events streams that
come from monitoring tools
2.Bi-directional interaction with IT service
3.Possible integration with automation
toolsets for implementing the prescriptive
information provided by the platform
Q. What are the drivers for AIOps adoption?
A. Early technology adoption of big data and
technologies focused on ITOM toolsets,
purely around data-centric monitoring and
analysis was called "IT operations
analytics" (ITOA). The impact that this
early adoption has created on the
availability and performance discipline is
now reshaping ITOM as a whole and beyond.
This broader trend is what we now call
"algorithmic IT operations". It has an
interesting and important interplay with all
disciplines under IT operations and the
potential for creating an orchestration
across various ITOM toolsets.
Q. What are the challenges inhibiting
A. The main challenge is separating the
marketing jargon from the actual capability
and assessing the effort needed by the
technology user. Machine learning – which is
a key component in analytics platforms –
needs huge amounts of data and more
importantly, interactions with humans in a
real-world scenario. These two components
are critical to extracting value from AIOps
platforms, and they take time. Any
investment into the toolsets needs to
account for the investment in terms of data,
human-machine interaction and time.
Q. How is AIOps relevant to business?
A. The traditional role of analytics is
shifting from merely supporting decision
making, towards increasingly driving
business processes by not only recommending
the best possible actions, but triggering
those actions in an automated manner. In
addition, analytics is being used to predict
preferences of customers to drive better and
more engaging customer experience.
All of this means, analytics platforms are
becoming central drivers of modern business
and I&O teams cannot look at analytics
platforms like a lab environment anymore.
Consistency in performance of data and
analytics platforms is key, and only AIOps
technologies are equipped to monitor the
modern data and analytics platforms.
Q. How is AIOps relevant to India?
India cannot remain immune to the
technological developments if it has to stay
competitive. There is an increase in
adoption of new and emerging technologies
like the Internet of Things (IoT),
containers and microservices, and it is only
a matter of time before these technologies
see increased adoption in production
Existing ITOM tools and IT operations are
ill-equipped to deal with the high-volumes
of data, varying data types and speed of
correlation needed to deal with these new
CIOs in India will need to keep themselves
abreast of AIOps to ensure they leverage the
right technology which will future-proof
their organizations and give their IT teams
the advantage to stay competitive.
Pankaj Prasad covers data center
availability and performance management and
is the primary analyst for IT infrastructure
monitoring (ITIM) at Gartner. In addition,
he covers IT event correlation and analysis
(ECA), IT operations analytics (ITOA),
algorithmic IT operations (AIOps), business
service management (BSM), and IT service
alerting or IT notification.