AIOps and the Modern Enterprise
Modern times, modern demands
November 14, 2018

Bhanu Singh
OpsRamp

Share this

Thanks to digital transformation, enterprise application and IT infrastructure stacks have witnessed a dramatic shift. Enterprises have transitioned from monolithic applications, bare metal infrastructure and virtual workloads to agile microservices, public cloud platforms and containerized deployments. To keep pace with dynamic and distributed digital services, enterprise IT teams have turned to monitoring point tools to solve specific pain points.


With a majority of enterprises investing in ten or more monitoring tools, it is no easy task keeping up with the volume, variety, and velocity of events for hybrid IT environments. Analyst firm EMA has estimated that IT admins can waste more than half their day digging through irrelevant or redundant alerts. How can IT teams focus on the critical events that can impact their business instead of wading through false positives? The emerging discipline of AIOps is a much-needed panacea for detecting patterns, identifying anomalies, and making sense of alerts across hybrid infrastructure.

What is AIOps?

AIOps leverages a broad set of technology approaches, including machine learning, network science, combinatorial optimization and other computational approaches for solving everyday IT operational problems at scale. Enterprises can address a wide variety of IT management activities with AIOps, such as intelligent alerting, alert correlation, alert escalation, auto-remediation, root cause(s) analysis and capacity optimization.

How are digital operations teams taking advantage of this new application of machine learning and artificial intelligence? OpsRamp, recently released its Top Trends In AIOps Adoptionreport. We surveyed 120 IT executives at enterprises with 500+ employees to better understand their operational challenges and see how they’re using AIOps tools.

Here are four insights from the report that offer an inside look into how enterprises are using issue identification, pattern discovery, and predictive analytics to improve IT-service performance:

1. AIOps Is No Longer A Science Project

AIOps adoption is gaining momentum, with enterprises either experimenting or actively using machine learning and data science for hybrid infrastructure management. 68% of IT decision-makers are piloting AIOps to better manage the availability and performance of business-critical IT services.

The bottom line? The use cases of advanced analytics and automation for IT management are just gaining traction. Gartner projects an increase of 40% in AIOps adoption by 2022. It’s not going away any time soon.

2. Data Insights and Root Cause Analysis Drive AIOps Usage

Modern IT services combine legacy datacenter and multi-cloud environments with numerous commercial and open-source monitoring products for tracking service health and performance. AIOps tools are ingesting, storing and analyzing monitoring data and delivering intelligent insights to fix IT service visibility issues.

Nearly three-quarters of these IT teams are using AIOps capabilities to gain more meaningful insights (73%) from system generated and monitoring-related alerts. Two-thirds of respondents are also applying AIOps to cut through the noise and determine the root cause (68%) of performance issues.

The bottom line? Across the board, respondents resoundingly agreed: AIOps is a chief solution in the battle against data smog. In fact, using AIOps to extract the signal from the noise is one of the primary use cases.

3. AIOps Provides Much-Needed Relief

The two big benefits of AIOps are the ability to automate routine functions (74%) and avoid costly service disruptions with faster recovery (67%). AIOps can also drive better anomaly detection (58%), by predicting shifts in system behavior across dynamic production environments.

The bottom line? I believe that as AIOps tools grow in sophistication, IT teams can expect to save time and money with actionable event context and data-driven recommendations. AIOps will let them focus on high-visibility projects instead of mundane operational tasks.

4. Data Quality and Talent Crunch Top Concerns For AIOps Adoption

While AIOps adoption is gaining steam, we found that there are a few apprehensions which could prevent wider adoption. The accuracy of prediction models (54%), quality of large datasets (52%) for machine learning models and the IT talent (48%) needed for building machine learning algorithms are all key constraints for scaling AIOps.

The bottom line? Accuracy, data quality, and transparency are the biggest AIOps roadblocks. IT leaders will need to identify emerging AIOps challenges and partner with technology vendors to prioritize the right solutions.

A Future, Unsupervised

AIOps is gaining traction in the modern enterprise, and it’s easy to see why. In 2018, the only effective way to tame alert storms is to combine human intuition with machine intelligence. IDC’s Worldwide CIO Agenda 2019 Predictions shows that 70% of CIOs will leverage artificial intelligence and machine learning for IT operations to increase staff productivity, drive faster incident response and minimize downtime. Our research corroborates these findings. The future will almost assuredly include a degree of self-healing IT operations management. That degree is still uncertain. But the age of AIOps is definitely upon us.

Bhanu Singh is SVP of Product Management and Engineering at OpsRamp
Share this

The Latest

September 28, 2020

In Episode 9, Sean McDermott, President, CEO and Founder of Windward Consulting Group, joins the AI+ITOPS Podcast to discuss how the pandemic has impacted IT and is driving the need for AIOps ...

September 25, 2020

Michael Olson on the AI+ITOPS Podcast: "I really see AIOps as being a core requirement for observability because it ... applies intelligence to your telemetry data and your incident data ... to potentially predict problems before they happen."

September 24, 2020

Enterprise ITOM and ITSM teams have been welcoming of AIOps, believing that it has the potential to deliver great value to them as their IT environments become more distributed, hybrid and complex. Not so with DevOps teams. It's safe to say they've kept AIOps at arm's length, because they don't think it's relevant nor useful for what they do. Instead, to manage the software code they develop and deploy, they've focused on observability ...

September 23, 2020

The post-pandemic environment has resulted in a major shift on where SREs will be located, with nearly 50% of SREs believing they will be working remotely post COVID-19, as compared to only 19% prior to the pandemic, according to the 2020 SRE Survey Report from Catchpoint and the DevOps Institute ...

September 22, 2020

All application traffic travels across the network. While application performance management tools can offer insight into how critical applications are functioning, they do not provide visibility into the broader network environment. In order to optimize application performance, you need a few key capabilities. Let's explore three steps that can help NetOps teams better support the critical applications upon which your business depends ...

September 21, 2020

In Episode 8, Michael Olson, Director of Product Marketing at New Relic, joins the AI+ITOPS Podcast to discuss how AIOps provides real benefits to IT teams ...

September 18, 2020

Will Cappelli on the AI+ITOPS Podcast: "I'll predict that in 5 years time, APM as we know it will have been completely mutated into an observability plus dynamic analytics capability."

September 17, 2020
One of the benefits of doing the EMA Radar Report: AIOps- A Guide for Investing in Innovation was getting data from all 17 vendors on critical areas ranging from deployment and adoption challenges, to cost and pricing, to architectural and functionality insights across everything from heuristics, to automation, and data assimilation ...
September 16, 2020

When you consider that the average end-user interacts with at least 8 applications, then think about how important those applications are in the overall success of the business and how often the interface between the application and the hardware needs to be updated, it's a potential minefield for business operations. Any single update could explode in your face at any time ...

September 15, 2020

Despite the efforts in modernizing and building a robust infrastructure, IT teams routinely deal with the application, database, hardware, or software outages that can last from a few minutes to several days. These types of incidents can cause financial losses to businesses and damage its reputation ...