

The challenges facing information technology organizations today can be boiled down to three words: stale, scale, speed.
Traditional approaches to managing the IT infrastructure have gone stale, rendered ineffective by significant complexity in dynamic, cloud-native environments. The scale has changed significantly as well, with exponential increases in the amount of data flowing through the infrastructure at any given time. Manual reporting and analysis? Forget it.
Perhaps the most significant factor has been speed, fueled not only by increased processing power, but the ability to spin up containerized environments and generate waves of applications in minutes.
This transformation in the IT world has led to the rise of a new ecosystem of solutions neatly captured in the term “AIOps,” generally defined as artificial intelligence for IT operations. It was originally named by Gartner Inc. two years ago to describe how information in the IT environment could be potentially managed through automation.
It is this new opportunity that companies like ScienceLogic Inc., among others, are seeking to exploit, and it offers a fascinating glimpse into the potential for applying AI to manage the trifecta of IT challenges.
“If we can convince, through a set of really concrete use cases, that the data coming from ScienceLogic at speed and quality can actually improve the configuration management database to the level of really efficient automation, all of a sudden people start to see that as a change, as an opportunity,” said Erik Rudin (pictured), vice president of business development and alliances at ScienceLogic. “That’s where I think AIOps is helping to change the narrative.”
Rudin spoke with Stu Miniman (@stu), host of theCUBE, SiliconANGLE Media’s mobile livestreaming studio, during the ScienceLogic Symposium in Washington, D.C. They discussed how ScienceLogic provides a unified view of the IT infrastructure, tools needed to generate real-time data context at scale, and the necessity of automation to manage operations (see the full interview with transcript here. (* Disclosure below.)
This week, theCUBE features Erik Rudin as its Guest of the Week.
Wikibon Inc.’s research has identified two broad solution categories for AIOps. One involves use of AI tools to accelerate and automate application workloads, already one of the hottest trends in the IT business, according to Wikibon research analyst James Kobielus.
The other key solution leverages AI to scale and optimize IT infrastructures at every level. This is where the ability of AIOps to handle vast amounts of data becomes critical.
ScienceLogic’s platform provides a unified overview of the IT infrastructure, in the cloud or on-premises, that includes monitoring application performance and how that impacts the total picture.
“We drive automation in the classic sense to trigger a workflow or update another system of record,” Rudin said. “Engaging in an IT service management process is a core part of AIOps, as much as data collection and driving other forms of automation.”
The problem facing many IT organizations today is that data generated by monitoring tools remains massively siloed. A recent survey of 6,000 global IT leaders conducted by AppDynamics LLC reported that 91% of respondents said that the monitoring tools they used only provided data on one specific area of responsibility.
ScienceLogic’s solution was evaluated in a Forrester Research Inc. report that highlighted the company’s AI-driven monitoring solutions for multicloud management and ranked them in the top two for both current offering and strategy. The company’s core product — the SL1 platform — uses an algorithmic approach to generate real-time context within an operational data lake. This provides IT organizations with a measure of predictive information to source potential resource issues before they become infrastructure tire fires.
“If we see something out of a policy, we can set an alarm,” Rudin explained. “Maybe my storage costs are going to accelerate because somebody made a bad change. There’s different ways that we can apply automation to the lifecycle, but enhancing the service management component perhaps is one of the most impactful ones.”
When ScienceLogic launched its SL1 platform one year ago, the company emphasized how the new offering generated topology maps to enable real-time health views of underlying IT infrastructure. That means breaking down the data silos for a comprehensive view that involves processing a lot of stored data.
This is where the promise of AI and its ability to automate at scale has the potential to reshape IT operations management for the foreseeable future. Humans are simply not up to the task.
“There’s no human that can process the amount of machine information from the amount of technologies that you have,” Rudin stated. “You have to use automation to manage that huge amount of different data sources. ScienceLogic is in a really interesting position right now to help with that process but more importantly accelerate the value by being able to process it and make it intelligent.”
An example of how ScienceLogic’s AI-driven data management works for one IT organization can be found in its deployment within Cisco Systems Inc. In an interview published last year, ScienceLogic’s vice president of global solutions, Raj Patnam, described how Cisco turned to the SL1 platform to gain a better view of performance from a range of data sources.
This included application performance data from AppDynamics, information from various security products, and router metrics generated through Meraki. Cisco uses SL1 within 10 of its data centers to manage 120,000 elements and 17 million unique data points collected daily, according to Patnam.
“Automation can be really applied, rather than being this mystical concept that’s hard to do,” Rudin said. “People don’t like to think that a robot is taking their job. I think what’s going to happen is machine learning algorithms are going to make jobs easier.”
ScienceLogic has publicly proclaimed itself as a disruptor of today’s IT management sector and takes pains to point out that it’s not the largest firm in the space or one with the deepest pockets. Instead, it offers the promise of automation to transform its own industry.
“We feel like we’re a disruptor in the AIOps market,” Rudin said. “We’re not done. We’re continuing on this journey.”
Watch the complete video interview below, and be sure to check out more of SiliconANGLE’s and theCUBE’s coverage of the ScienceLogic Symposium. (* Disclosure: TheCUBE is a paid media partner for the ScienceLogic Symposium event. Neither ScienceLogic Inc., the sponsor for theCUBE’s event coverage, nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)
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