In today’s hyper-connected world, IT infrastructure is the backbone of every industry—from airlines to banks to retailers. When an outage strikes, the ripple effects are felt everywhere. The ability to quickly detect and respond to issues can make the difference between a minor hiccup and a full-blown crisis. This is where AIOps systems come into play, providing real-time insights and helping organizations manage the fallout from IT failures.
As the product manager of ServiceNow’s AIOps solution, I regularly monitor how our customers are using the product. This allows me to spot patterns in the data and, more importantly, identify potential trends that may indicate larger issues at play. Recently, the data revealed something interesting—a pattern that underscores just how critical AIOps has become.
The AIOps Data
Let’s start with a real example: the global outage that occurred on July 19. It was a significant event that impacted numerous organizations across multiple sectors. Airlines experienced delays, retailers faced disruptions in their supply chains, and banks encountered downtime in their services. As you might expect, this led to a sharp increase in alerts within ServiceNow’s AIOps product.
Below is a graph showing the aggregated daily sum of occurrences across all our customers. As you can see, there’s a clear peak on July 19, correlating with the global outage.
This spike reflects the increased activity as IT teams scrambled to manage the surge of alerts resulting from the widespread outage. ServiceNow’s AIOps was instrumental in helping organizations detect, respond, and resolve these issues in real time. But what’s even more intriguing is the peak that occurred a few days earlier, on July 15. It raises the question: What happened on that day? 🧐
Analyzing the July 15 Peak
The July 15 peak was not as widely publicized as the global outage on July 19, but it still caused a noticeable uptick in activity. This begs the question—was this a general failure affecting a number of customers, or was it an issue isolated to just one or a few customers?
While global outages typically make headlines, smaller, localized issues can be just as disruptive to individual organizations. Whether it was a regional network issue, a service provider failure, or a specific application outage, the spike on July 15 is a reminder that outages don’t always have to be massive to have an impact.
ServiceNow’s AIOps product allows organizations to dive deep into their incident data, analyze patterns, and correlate alerts to understand the root causes of issues. In the case of the July 15 peak, the data could reveal whether this was a widespread problem or a localized issue that impacted one or two major customers.
This is the kind of insight that helps organizations stay ahead of potential disruptions. By continuously monitoring their systems and analyzing alert data, IT teams can identify trends, anticipate problems, and respond before they escalate into full-blown crises.
Lessons from the Data
The spikes in alert activity seen on July 15 and July 19 serve as powerful reminders of the importance of being prepared for outages. They underscore the critical role of AIOps systems in modern IT operations. Without real-time monitoring and analysis, organizations are left in the dark when issues arise, reacting only after the damage has been done.
ServiceNow’s AIOps product provides organizations with the tools they need to be proactive. Continuously monitoring IT infrastructure, identifying potential issues, and correlating alerts across different systems, allows organizations to respond faster and mitigate the impact of outages.
Conclusion
Outages are inevitable in today’s complex IT environments, but how organizations respond to them makes all the difference. ServiceNow’s AIOps solution empowers IT teams to detect, analyze, and resolve issues in real-time, minimizing downtime and ensuring business continuity.
The data from July 15 and July 19 shows that no matter the size or scope of an outage, AIOps systems are crucial in keeping the wheels turning when the unexpected happens.
And as for that July 15 spike? While I won’t reveal exactly which customer it involved, it’s most likely that this was an issue specific to a single organization. Imagine the stress levels in that IT team on a Monday morning as they scrambled to get their systems back on track! Thankfully, with the right tools in place, they were able to detect the problem quickly and work on a resolution.
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