What Is the Deal with AIOps? - Part 1
July 26, 2021

Akhilesh Tripathi
Digitate

Share this

We are in an era where the rate of technology adoption across nearly all industries has increased significantly in recent years. Growing enterprise complexity has increased demand for new models for business transformation in the form of deployment, scale, and change acceleration. This renewed acceleration of technology adoption is redefining enterprise IT Operations (ITOps).

The increase of instrumentation, monitoring and integrations has increased the amount of data generated by organizations — which created two challenges:

1. making sense of it has become difficult with standard methods.

2. It has also increased noise in the ecosystem, which is leading to high false alerts.

These have led to the need and eventual creation of a new market category within the space of enterprise IT called "AIOps" — the application of Artificial Intelligence (AI) for IT operations.

AIOps is rapidly becoming a de-facto option for enterprises' IT strategies, with nearly immeasurable benefits to be provided. However, AIOps is still a relatively new discipline and misconceptions surrounding the technology's capabilities and uses have caused bottlenecks and roadblocks in its widespread adoption.

So, what should organizations expect from AIOps?

How can organizations that want to digitally transform their IT pursue AIOps for maximum benefit?

What is AIOps? Why AIOps?

First, let's see exactly what AIOps is and why it's critical in today's enterprise IT environment. Recent digital transformation efforts across industries have redefined enterprise IT Operations and led to the emergence of AIOps.

AIOps refers to solutions that leverage AI and Machine Learning (ML) to acquire enterprise IT data, analyze it and take required actions for autonomous IT Operations. It helps transform enterprise IT operations from being slow and reactive to agile and proactive, thus addressing many key IT operational and business challenges.

Automating IT operations enables easy deployment of modern and agile IT systems that support enterprise-wide digital transformation efforts, such as cloud migration and automation enablement. Traditional IT management solutions that involve manual efforts for tedious and repeatable processes cannot keep up with the pace of rapid enterprise IT changes and leaves IT teams facing challenges surrounding infrastructure complexities, long delays in isolating and resolving IT faults, and inconsistent and variable quality of operations. Deploying AIOps helps to overcome these challenges by acting as an intelligent way to assess enterprise system behavior and detect anomalies, prescribe solutions and proactively take action to resolve IT incidents and prevent disruptions in IT operations.

With the increase in scale of enterprise operations, complexity and accelerating change in technology footprints, i.e., the landscape of digital systems across an organization, AIOps is not just an option, but a necessity. The volume and complexity of data generated by, and coming into, any given organization can be quite voluminous and overwhelming. Handling this with traditional IT systems can be quite inadequate. Making sense from this huge amount of information calls for advanced AI/ML based analytics/intelligence layer.

Also, as data might come from correlated sources it can lead to duplicated work and siloed views if handled through a traditional and siloed IT operations approach. This is because it lacks the ability to provide a correlated enterprise-wide view of digital systems and how they interact across business domains. So, it can never match the scale of this data and also cannot reap the full benefits of this data/information.

Simply making sense of the data/information won't solve the problem, it is also necessary to act on the inference drawn from this data, and this is hugely important. Intelligent automation becomes a necessity here. Hence, the need for a highly intelligent, hyper automated and scalable solution that can combine big data, observability, enterprise context, AI/ML based analytics and intelligent automation to help gain full-stack visibility across hybrid environments, understand normal behavior, understand root causes of issues, fix problems, predict failures and their direct impact on IT and business. Thus, providing resilient and efficient IT operations cross organizations — and the answer lies in "AIOps."

Go to What Is the Deal with AIOps? - Part 2, outlining what to keep in mind when considering DevOps, and what results can be expected from AIOps.

Akhilesh Tripathi is CEO at Digitate
Share this

The Latest

December 07, 2021

The Holiday Season means it is time for APMdigest's annual list of Application Performance Management (APM) predictions, the most popular content on APMdigest, viewed by tens of thousands of people in the IT community around the world for more than a decade. Industry experts offer thoughtful, insightful, and often controversial predictions on how APM, AIOps, Observability, Open Telemetry, and related technologies will evolve and impact business in 2022 ...

December 06, 2021

As organizations strive to advance digital acceleration efforts, outpace competitors, and better service customers, the path to better, more secure software lies in AIOps. As DevOps teams continue to adopt progressive delivery models and the volume of production deployments and configuration changes sees even more growth, here are a few of the things that your DevOps teams should keep in mind, as they look to make the most of their IT toolkits via AIOps ...

December 02, 2021

In the old days of monolithic architectures, IT operations teams could manage service-disrupting incidents themselves. But these architectures have evolved, and the systems our digital economy relies on today are too complex and produce too much data for human operators to monitor, let alone fix. Artificial Intelligence for IT Operations (AIOps) solutions automate system monitoring and remediation strategies to help DevOps and SRE teams ensure that services and apps are continuously available ...

December 01, 2021

As global and emerging technology trends continue to drive the network to evolve at an accelerated pace, we wanted to better understand the current trends and challenges these teams face. As a result, LiveAction conducted a survey of networking professionals that on average manage more than 500 networking devices at organizations with more than 600 employees. Let's dive into four of the key insights revealed in this report ...

November 30, 2021

Thanks to pandemic-related work-from-home (WFH) and digital/mobile customer experience initiatives, employees and users are more distributed than ever. At the same time, organizations everywhere are adopting a cloud-first or cloud-smart architecture, distributing their business applications across private and public cloud infrastructures. Private data centers continue to be consolidated, while more and more branch offices are connecting to data centers and the public cloud simultaneously. Maintaining application performance for distributed users in this increasingly hybrid environment is a significant challenge for IT teams ...

November 29, 2021

In a world where constant change is becoming routine, Gartner said that infrastructure and operations (I&O) leaders must shift their traditional focus from efficiency to one of adaptive resilience. I&O leaders must re-imagine how they manage their talent, their platforms and operations, if they want to dynamically and quickly exploit new opportunities ...

November 23, 2021

The holidays are almost upon us, and retailers are preparing well in advance for the onslaught of online consumers during this compressed period. The Friday following Thanksgiving Day has become the busiest shopping day of the year, and online shopping has never been more robust. But with supply chain disruptions limiting merchandise availability, customer experience will make the difference between clicking the purchase button or typing a competitor's web address ...

November 22, 2021

The 2021 holiday season will be an inflection point: As the economy starts to ramp up again while the country still grapples with the pandemic, holiday shopping will be the most digital holiday season in history by a long shot ... The work must begin months before, as organizations learn from the year prior and take steps to improve experiences and operations, fine-tune systems, plug in new data sources to enrich machine-learning algorithms, move more workloads to the cloud, automate, and experiment with new tech. These efforts culminate in "API Tuesday" ...

November 18, 2021

Most (83%) of nearly 1,500 business and IT decision makers believe that at least 25% of their workforce will remain hybrid post-pandemic, according to the Riverbed | Aternity Hybrid Work Global Survey 2021. While all indicators signal hybrid work environments are the future, most organizations are not fully prepared to deliver a seamless hybrid work experience ...

November 17, 2021

The results of the 2021 BMC Mainframe Survey highlight the consistent positive growth outlook as seen in recent years, with 92 percent of respondents viewing the mainframe as a platform for long-term growth and new workloads, and 86 percent of extra-large shops expecting MIPS (millions of instructions per second) to grow in the coming year. This is not surprising, considering the disruptive nature of the modern digital economy ...