AIOps use cases AIOps may already be at work in your IT portfolio without you even knowing it. Advanced CRM or ERP systems often have intelligent management built in. Most major cloud platforms make use of machine learningâpowered monitoring and management tools as well. But relying on built-in functionality within point solutions has its downsides. Sixty-five percent of IT organizations in an AIOps Exchange survey said they still rely on monitoring approaches â whether intelligent or not â that are either siloed, rules-based or donât cover the needs of their entire IT environment. Moreover, according to a recent BigPanda survey, 42 percent of IT organizations use more than 10 different monitoring tools for their IT environments. That was how Carhartt started with AIOps. âPreviously, for the different environments, weâd have to monitor them independently,â Hill says. To manage this complexity, Hill opted to combine monitoring onto two platforms, settling first on AppDynamics for application performance monitoring, and later adding Turbonomic to keep tabs on Carharttâs infrastructure. Performance issues on the companyâs website during Black Friday and Cyber Monday shopping rushes forced the need for a change. By the time the company saw the problems, customers had already felt the service degradation, Hill says.
Since Carhartt deployed AppDynamics in the fall of 2017, spikes during Black Friday and Cyber Monday have been met with zero downtime. âWe had record growth,â he says. âWe grew double the rate of the industry as a whole, without any of the outages or performance degradation that we had experienced previously.â Carhartt added Turbonomic in early 2019 for resource management of both on-prem and cloud environments. With the new system, utilization has increased from 70 to 92 percent, he says. âIt probably saved us 25 percent of infrastructure costs.â Increased utilization needs are processed automatically, without human intervention, while decreases in capacity still require human approval.
âIt sees that weâve got a capacity challenge and it puts a change request through to ServiceNow,â Hill says. âWhen we have too much capacity, it creates a ticket in ServiceNow, and someone looks at it first. Itâs a quick review â just a click. For now, I donât need to automate it.â
The next step for the company is automating business tasks, such as processing customer orders using text recognition and natural language processing. AIOps adoption By 2023, 40 percent of companies will be using AIOps for application and infrastructure monitoring, according to Gartner. But by all accounts, AIOps adoption is still in its early stages. According to a 2019 survey sponsored by Loom Systems, only 5 percent of companies have implemented AIOps so far.One thing hurting adoption is that there are a lot of vendors in the market, says Akash Bhatia, managing director and partner at Boston Consulting Group. âAlmost too many.â
And with 59 percent of organizations in the exploration phase, according to the Loom Systems report, itâs still hard for customers to figure out exactly what theyâre offering. Plus, many vendors operate in just one segment of AIOps, Bhatia says, such as application performance monitoring, infrastructure management, or network performance monitoring and diagnostics. But the market is showing signs of consolidation as the technology matures, he adds.
IDC predicts the AIOps market, which it calls IT operations analytics, will grow from $2.9 billion in 2018 to $4.5 billion in 2023, with most of the growth coming from AIOps as a service. And while AIOps is often bundled in with enterprise software platforms or cloud services, larger enterprises are beginning to invest in AIOps as a standalone budget item, says Stephen Elliot, analyst and program vice president for AIOps at IDC.
âTheyâre realizing that theyâre in a multicloud world,â he says. âAnd they have agile transformation happening, and they have DevOps teams, and theyâre realizing that theyâve got to move faster and that complexity is increasing.â AIOps value proposition Companies that leverage AIOps are beginning to see the importance of shifting from systems that perform analysis and predictions to those that make decisions on their own. Enter automation.
âThey need tools that can collect massive pools of information, apply analytics, reduce the noise, and drive faster problem identification and resolution,â Elliot says.
Automation also requires greater AIOps integration. A problem with application performance may be due to a software issue, a networking issue, or a hardware issue. In a multi-cloud environment, the root cause can be in one cloud, or in another cloud, or be the result of a combination of factors. If your AIOps infrastructure is fragmented, finding and fixing the root causes of problems can be a challenge.
âThen youâre back to hand-to-hand combat, where every group has its own tools,â says David Link, CEO at ScienceLogic, an AIOps vendor. âIf you have a unique tool for every application initiative, you canât scale the enterprise that way.â
Meanwhile, companies that have deployed AIOps, like Carhartt, are finding that their investments are paying off. According to a survey by Enterprise Management Associates, 81 percent of enterprises using AIOps report a positive return on investment. In fact, 42 percent said that the value of AIOps âdramaticallyâ exceeds the costs.
According to EMA, the six most common use cases for AIOps are cross-domain application infrastructure and performance, capacity management and infrastructure optimization, DevOps and agile, customer and end-user experience management and business alignment, cost management and change management. AIOps as a revenue generator Cincinnati Bellâs CBTS subsidiary provides communication services to enterprise customers. CBTS used to stand for âCincinnati Bell Technology Solutionsâ but as the company expanded to other geographies, it now stands for âConsult Build Transform Support,â says Joe Putnick, the companyâs chief innovation officer.
Moving to AIOps was critical to helping improve reaction times, he says, but has now become a source of new business opportunities. For example, before the company turned to AIOps, it would take hours, days or âneverâ to get customer equipment into the CBTS monitoring, management and billing systems, Putnick says.
âNow Iâve taken provisioning from five hours down to two minutes,â Putnick says. âAnd when I say provisioning, I mean the full provisioning across the whole IT service management and event management systems. I know that those statistics are pretty compelling.â
The company is also using AIOps to analyze usage patterns and automate responses. âWeâre applying AIOps to predict where the capacity needs to be so that we can maintain maximum uptime and maximum customer satisfaction,â he says.
AIOps has helped CBTS grow from less than 40 sites per month, to more than 500 average installs per month, says Putnick â with almost the same number of people.
CBTS uses a combination of tools built into AWS, its own custom-coded applications inside of ServiceNow, custom machine learning and adaptive algorithms, as well as AIOps tools from ScienceLogic. Next up: value-added services for its customers. For example, customer service chatbots that CBTS provides its customers can be made more intelligent and responsive using the data, analytics and predictions that come out of its AIOps systems. AIOps and managed services
providers But to see the full potential of AIOps, you should look no further than the managed services provider (MSP) industry.
âItâs probably the largest part of the market right now,â says Justin Richie, data science director at Nerdery, a digital services consultancy. âTheyâre definitely trying to invest in algorithmic support where they can. They know, outside the hardware, their largest expense is human capital.â
For MSPs, AIOps means higher efficiency, lower costs, and faster resolution times â all significant competitive differentiators in this sector.
âItâs one half of our value proposition for AIOps,â says Raghu Kamath, senior vice president of strategy and operations at San Jose-based MSP NetEnrich, which has rolled out AIOps across more than 1,000 clients. âWe started to implement it across a few customers, then gradually extended it across our customer base over the last twelve months. Now, over 50 percent of our customers are on the AIOps platform.â
One of the most obvious and immediate benefits for NetEnrich was a reduction in noise. False alarms create unnecessary work for employees, and slow down response times for customers.
âOur response time to detect and take action has increased â our mean time to repair has become at least 30 percent faster after implementing AIOps,â Kamath says. âAnd it will continue to increase as AIOps becomes more mature and brings in more inference models.â
Because NetEnrich uses AIOps in so many different customer environments, Kamath has a unique perspective on the technology. First, he has found that the more homogeneous the environment, the easier it is to deploy AIOps.
âIt becomes a lot more complex when you start integrating all these different environments,â he says.
Also, customers that use public cloud infrastructure have a leg up because the environments are more consistent. Still, there are occasional hurdles in getting cloud vendors to open up their systems.
âBut the public cloud vendors are shifting their position,â he says. âIf you look at the amount of data you had access to two years ago, to now, it has gotten a lot better.â
Leveraging AIOps for legacy applications and hardware is tricky, Kamath says. âIf you donât have enough logs, it becomes pretty difficult to infer anything. That is why we encourage our customers to accelerate their digital transformations and modernize their applications.â |
