Page 33 - EngineerIT September 2022

AUTOMATION AND CONTROL

clouds, containers and microservices Reactive to proactive
(to name a few), has resulted in hefty AIOps can fill this need by helping IT teams to anticipate and respond to problems
multi-dimensional data flows generating before they happen by collecting these large amounts of operational data, separating
excessive noise that hinders the ability signal from noise, and generating suggested actions to automatically resolve problems
of IT teams to identify and resolve that would otherwise incapacitate entire IT departments. True AIOps is a combination
service incidents. As IT systems of machine learning and automation capabilities that enable teams to filter out
have evolved from static, There is noise, while identifying and contextualising information faster to accelerate
predictable physical remediation and proactively identify issues before they unfold.
systems to dynamic a deep need for a
software-defined management approach Leveraging complex data
resources capable of that can create order out Combining AI and ML, AIOps uses these massive volumes of historical
change and on-demand of chaos and bring visibility incident data, change data and other operational data such as
reconfiguration, this and predictability in metrics, logs and events to highlight and isolate anomalies before
has created a need they spiral into larger outages. Without the ability to make intelligent
for equally dynamic real-time recommendations, automation tools on their own are limited in what
technology and processes they can accomplish but by pairing automation with AI and ML, companies
to manage them. This demand can remove manual tasks and take the guesswork out of decision-making to truly
for dynamism translates into complexity augment human skills and capabilities.
experienced at three levels:
Wait. So, what is AIOps?
1. System: At the heart of the issue is AIOps empowers operations teams to tame the overwhelming complexity and volume
the complexity created by systems of data generated by modern IT environments and use it to maintain uptime by
that are modular, distributed preventing outages and achieving continuous service assurance. In other words, AIOps
and dynamic with transitory means using ML and data science to solve IT operational problems.
components.
What’s the fuss about AIOps?
2. Data: The second level of complexity AIOps is not a quick fix for every operational headache, but it will provide a specific set
comes in with data generated by of benefits for organisations. These benefits include:
these systems about their internal
operations. Logs, metrics, traces, • Finally achieving simplicity: Complexity has resulted from digital transformation
event records and more, this data and the need to power remote working, particularly through the adoption of hybrid
is highly complex due to its sheer cloud. AIOps can restore simplicity by aggregating information across distributed
volume, specificity, variety and deployments.
redundancy.
• Softening the skills shortage: Given the scarcity of skilled IT professionals, use of
3. Tools: The third level is the their time needs to be optimised. This isn’t using automation to replace human
complexity of the tools required work, it’s about optimising what humans spend their time on. By automating certain
to monitor and manage data and tasks, IT resources are freed to focus on other high-value tasks.
systems. As more tools become
available (with increasingly narrow • Enabling visibility and predictability: AIOps extracts actionable insights from large
functionality) these often have pools of monitoring data gathered from disparate IT applications that delivers
interoperability issues that can operational insights across different layers of the IT infrastructure.
create operational and data silos.
• Cutting costs and saving time: Reducing complexity and the amount of time an IT
Order from chaos team has to spend on certain tasks translates to resource efficiency and savings that
Today’s dynamic IT environments cannot every business can benefit from.
be managed with yesterday’s tools and
outdated information. There is a deep Where digital transformations have stalled due to overwhelming complexity or
need for a management approach that resourcing challenges, AIOps can reignite the journey and organisations can finally
can create order out of chaos and bring achieve the speed and stability they’ve been dreaming of. ML and data science
visibility and predictability in real-time. packaged into AIOps can give IT operations teams a true real-time understanding of any
Organisations need a way to intelligently issues, including new, unforeseen problems that affect the availability and performance
balance critical workloads between of digital services. n
humans and machines to allow teams
to properly manage their most valuable To find out how to transform ITOps into AIOps, download the eBook,
resource-time. ‘Your Guide to Getting Started with AIOps’ or visit www.corrserve.co.za

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