AI, ML, and AIOps are transforming how IT professionals work in today’s increasingly complicated digital environments—enabling them to automate tasks, detect security threats and performance anomalies, optimize performance, and make better decisions based on data analysis. Because these technologies process such massive amounts of information, they help IT professionals optimize performance by ensuring applications and services are running properly.
By embracing AI and ML, enterprises can better detect, predict, and even prevent application or system crashes and outages by automatically analyzing key performance indicators (KPI)—improving the end-user experience, boosting productivity, and safeguarding profitability. Accomplishing this today is notably challenging because many companies run their systems across multiple clouds and rely on hundreds of applications to get work done. More than simply ensuring applications remain operational, they enable DevOps teams to accelerate innovation and add more value to the business on a continuous basis.
Through AIOps, the benefits of embracing AI and ML can be realized at higher levels of the organization, too. Think back to the scenario of the needle in the haystack. Now imagine you have a virtual farmhand who could autonomously scan the hay to look for anomalies, keep track of searched areas, and detect incoming hay bales for needles—or even new threats entirely.
When you do not need to focus on low-level, in the trenches labor, you’re now free to spend valuable time pursuing other higher-level pursuits, like caring for the animals, training new farmers, make irrigation a priority, or designing plans to install windmills for future profitability and productivity. Or in database terms, you can assist dev teams and business analysts, train data analysts to write more efficient queries, or help build new and better applications.
AIOps bring these benefits to DataOps and IT teams, too. AIOps is a relatively new term Forrester describes as a “practice that combines human and technological applications of AI/ML, advanced analytics, and operational practices with business and operations data.”
AIOps-powered service management allows companies to resolve service issues faster than ever before, reducing toil and relieving the pressure on end-user services teams. Businesses leveraging AIOps are better placed to identify patterns and anomalies that could signal potential problems in an IT environment, quickly correlate vast amounts of data to provide root cause analysis, recommend remediation strategies, and even automate many tasks that are essential “heavy lifting” operations. After all, when “slow is the new down” for your applications, every second counts.
Additionally, AIOps enables end-to-end visibility regardless of a company’s infrastructure or where they may be on their digital transformation journey. More than that, applying AIOps helps organizations take the critical steps toward proactive management of digital services and moves them toward autonomous operations, which require little to no human intervention.
All told, AIOps allows leaders to gain back valuable time and brainpower—not to mention better protection from simple human error—to focus on critical priorities that amplify the business’ ability to serve its customers.
I must caution that AIOps isn’t a replacement for all the work needing to be done. Instead, we should view it as an aid in understanding the information we can’t possibly sift through ourselves. No matter how sophisticated machine learning becomes, it still won’t be able to “think” for itself like humans. It’s not just that AI and human intelligence can work together but when combined, it’s a partnership that unlocks nearly limitless potential at every level of the organization.
The stakes for IT professionals are high, and coping with exploding amounts of data is a skill set unto itself. And in the coming years, we will see organizations giving preference to IT professionals who are effective at using AI tools. Yet effectively monitoring and analyzing this increasing amount of systems information is absolutely critical for any large companies hoping to remain competitive in the decades ahead.
As I’ve said for years as a top industry database and SQL guru, “Better data makes better decisions.” All the data I’ve seen so far points to adoption of AI, ML, and AIOps as being a great decision for any enterprise operating in this day and age.