The world is increasingly digital. The U.S. Census Bureau estimates e-commerce grew 14.2% from 2020 to 2021, for a total of $870.8 billion in sales. And just look at the trends in remote work. According to a FlexJob and Global Workplace Analytics report, remote work has grown 44% over the last five years and an astonishing 159% over the last 12.
Indeed, much of America relies on a slew of digital apps and services to get business done every day.
So what does this mean for businesses?
If enterprises are going to successfully navigate this digital-first, cloud-reliant world, they will need to double down on their technology’s availability. After all, today’s technologies are complex, distributed and ephemeral.
But here’s the challenge: we’ve become so dependent on digital apps and services for workforce productivity and customer engagement that it’s no longer enough to just fix digital incidents and outages. We must anticipate potentially disruptive incidents, and that’s only possible with advanced artificial intelligence for IT Operations (AIOps).
However, not all AIOps tools are created equal. First, let’s get clarity on what no longer works for digitally reliant businesses (aka most enterprises operating today).
AIOps of the past — only events won’t cut it
AIOps was birthed in the world of events. If the AIOps tool deemed an event abnormal, the technology would notify teams that an incident occurred. But incidents equate to downtime. Once the tool notified teams about an issue, it was already affecting end-users.
With digital transformation, the game is no longer spotting incidents. It is about spotting incidents before they impact internal and external audiences.
So, if AIOps vendors are just analyzing events, then they’re falling behind. And so will their customers.
AIOps of the future — the entire IT ecosystem
As IT environments become increasingly complex and change by the subsecond, businesses need more intelligence about these systems than just events data can provide. Next-generation AIOps tools ingest data from across the entire IT ecosystem — adding metrics, traces and logs to event data — to identify anomalies early in the incident lifecycle.
After detecting the problem, AIOps expedites its resolution by automating the incident workflow. It notifies the people responsible for mitigating the incident and provides them with valuable context to the problem, enabling quicker detection and resolution.
In the meantime, the tool’s machine learning (ML) capabilities understand which patterns drive continuous availability. After identifying an incident, the AIOps tool ensures it never rears its ugly head again.
The end result? Potentially disruptive incidents are detected and mitigated before they become critical.
Moogsoft sets the pace
Moogsoft has been providing AIOps technology before the term “AIOps” was even invented. Early on, we saw that events-only AIOps was limited. So, we tasked a group of engineers to build a comprehensive solution that would analyze events, metrics, changes and logs and blow our then-technology out of the water. They delivered (to say the least), and that’s the product we use today.
Our patented AIOps platform includes vital early detection that routinely captures incidents before they impact the business. Surprisingly, few vendors can say the same.
Conclusion
The only way to deal with the burgeoning complexity and accelerating rate of change in modern IT environments is to abandon traditional model-based management
Despite its immense capabilities, Moogsoft’s SaaS technology isn’t difficult to implement, nor is it expensive or resource-intensive. We’ve reduced the steps necessary to deploy these platforms along with the resources needed to maintain them and the time necessary to see results.
You can get started today with a Moogsoft free trial. Or, if you prefer more hands-on guidance, take the Moogsoft AIOps Challenge. A dedicated Moogsoft engineer will set up your account and show the value AIOps can provide in just three days!
