Data Matters More Than Ever in AIOps
New study reveals key hurdles on the road to AIOps
May 02, 2019

Bhanu Singh
OpsRamp

Share this

Like any new, potentially disruptive technology, artificial intelligence for IT operations, or AIOps has quickly become a trend, and slowly become a reality. It's only been a few years since Gartner coined the term, and yet, 30% of IT teams in large enterprises will roll out AIOps initiatives by 2023. These IT practitioners are still in experimentation mode with artificial intelligence in many cases, and still have concerns about how credible the technology can be. They have concerns over the results of these implementations, and worry about maintaining service availability and uptime during migration.

Because AIOps is still in its infancy, there hasn't been much reporting on what these concerns specifically are. A recent study from OpsRamp targeted these IT managers who have implemented AIOps, and among other data, reports on the primary concerns of this new approach to operations management.

The Devil is in the Data

The report cites data accuracy as the chief concern for IT pros when it comes to AIOps. Two-thirds (67%) of those surveyed revealed it as their top priority. This could be for a variety of reasons, including:

Data Sources: In a world of distributed, hybrid, multi-cloud infrastructure, it's more difficult than ever to capture data on every level of an organization. Different cloud providers report in different ways. And point tools provide analytics across a host of different metrics. It's next to impossible to compare data sources together for a true contextual view of the organization.

Data Quality: Even when that data is captured, these IT teams aren't necessarily sure that it's accurately reflecting the truth about a system. Modern data can be fragmented, hidden, unparsed or too distributed to make sense.

Data Volume: Today's enterprise infrastructure produces an overwhelming amount of metrics on usage, capacity, performance, availability, security, and more. It's easy to get lost in the noise.

Data Consistency: It's impossible to say, under the crushing weight of data today, that IT teams are seeing consistent reporting and results across the organization. But until data is consistent, it can't be actionable.

Data Culture: This is perhaps the biggest change the world of IT operations will resist as it continues to adopt AIOps. Most organizations today are still process-driven, focusing maniacally on improving, tweaking, and changing the process to get a different result. Tomorrow's AIOps-driven organization will become data-driven, putting that same focus on refining data for better outcomes.

Improving Accuracy by Changing Culture

Becoming a data-driven organization means shifting priorities from process milestones to data-based ones, where data manipulation and governance are critical. It's building an organization where data modeling is as important as product development, and where data drives business outcomes. It's where there's as much focused placed on algorithms as applications. Once this culture is installed, where the focus becomes accuracy, consistency, and context, can an operations team truly trust the data. And this is where AIOps can truly come to life.

Data accuracy isn't the only concern when it comes to AIOps adoption, but it's definitely on the minds of IT managers and infrastructure professionals. Where they once just struggled to find skilled practitioners and leading-edge technology to solve problems, they now must also juggle a focus on data. It's clear that enterprises will need more time to build trust in the relevance and reliability of AIOps recommendations. This also represents an opportunity for AIOps vendors to provide solutions that drive improved accuracy, cleaner data, and greater control. AIOps promises to transform how IT operations is managed and maintained. It's likely to do the same for data.

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

The Latest

March 26, 2020

While remote work policies have been gaining steam for the better part of the past decade across the enterprise space — driven in large part by more agile and scalable, cloud-delivered business solutions — recent events have pushed adoption into overdrive ...

March 25, 2020

Time-critical, unplanned work caused by IT disruptions continues to plague enterprises around the world, leading to lost revenue, significant employee morale problems and missed opportunities to innovate, according to the State of Unplanned Work Report 2020, conducted by Dimensional Research for PagerDuty ...

March 24, 2020

In today's iterative world, development teams care a lot more about how apps are running. There's a demand for fixing actionable items. Developers want to know exactly what's broken, what to fix right now, and what can wait. They want to know, "Do we build or fix?" This trade-off between building new features versus fixing bugs is one of the key factors behind the adoption of Application Stability management tools ...

March 23, 2020

With the rise of mobile apps and iterative development releases, Application Stability has answered the widespread need to monitor applications in a new way, shifting the focus from servers and networks to the customer experience. The emergence of Application Stability has caused some consternation for diehard APM fans. However, these two solutions embody very distinct monitoring focuses, which leads me to believe there's room for both tools, as well as different teams for both ...

March 19, 2020

The 2019 State of E-Commerce Infrastructure Report, from Webscale, analyzes findings from a comprehensive survey of more than 450 ecommerce professionals regarding how their online stores performed during the 2019 holiday season. Some key insights from the report include ...

March 18, 2020

Robinhood is a unicorn startup that has been disrupting the way by which many millennials have been investing and managing their money for the past few years. For Robinhood, the burden of proof was to show that they can provide an infrastructure that is as scalable, reliable and secure as that of major banks who have been developing their trading infrastructure for the last quarter-century. That promise fell flat last week, when the market volatility brought about a set of edge cases that brought Robinhood's trading app to its knees ...

March 17, 2020

Application backend monitoring is the key to acquiring visibility across the enterprise's application stack, from the application layer and underlying infrastructure to third-party API services, web servers and databases, be they on-premises, in a public or private cloud, or in a hybrid model. By tracking and reporting performance in real time, IT teams can ensure applications perform at peak efficiency — and guarantee a seamless customer experience. How can IT operations teams improve application backend monitoring? By embracing artificial intelligence for operations — AIOps ...

March 16, 2020

In 2020, DevOps teams will face heightened expectations for higher speed and frequency of code delivery, which means their IT environments will become even more modular, ephemeral and dynamic — and significantly more complicated to monitor. As a result, AIOps will further cement its position as the most effective technology that DevOps teams can use to see and control what's going on with their applications and their underlying infrastructure, so that they can prevent outages. Here I outline five key trends to watch related to how AIOps will impact DevOps in 2020 and beyond ...

March 12, 2020

With the spread of the coronavirus (COVID-19), CIOs should focus on three short-term actions to increase their organizations' resilience against disruptions and prepare for rebound and growth, according to Gartner ...

March 11, 2020

Whether you consider the first generation of APM or the updates that followed for SOA and microservices, the most basic premise of the tools remains the same — PROVIDE VISIBILITY ...