Cisco added new predictive services to its Business Critical Services portfolio that uses artificial intelligence (AI) and machine learning to anticipate and prevent IT infrastructure failure, among other things.
The subscription service, called Business Critical Services, uses automation and orchestration to reduce network complexity and opex. It also uses analytics and machine learning to provide insights and recommend infrastructure changes. And with today’s update, Cisco extended these capabilities to provide visibility into other vendors’ technology.
The company first rolled out the Business Critical Services a year ago.
As an example of how companies use the services: a European enterprise converged three disparate IT networks into one unified architecture, James Mobley, VP and GM of emerging technologies and innovation at Cisco, wrote in a blog. This customer also lowered opex costs because of a 15 percent overall efficiency improvement in the second year, which then jumped to 30 percent by the third year of using the services.
“We were hearing time and time again from our customers that they were struggling with operating very complex and often very large enterprises, while at the same time experiencing a shortage of skills and talent,” Mobley said in an interview with SDxCentral. “So we began to think about what we could create that would allow us to solve that problem, free up opex, and allows customers to shift to transforming their business.”
That’s how Cisco came up with version 1.0 of the services, Mobley said.
Today, Cisco added new services to the predictive services portfolio and launched Business Critical Services 2.0. This includes three new or expanded capabilities to improve IT management.
New Predictive Services
Fingerprinting uses machine learning to profile each Cisco device in a customer’s environment, aggregate that data with crash information from Cisco’s global data base, and predict endpoints with the highest risk of problems. Additionally, it makes recommendations on how to pre-empt disruption and reduce risk.
“It does amazingly powerful things to allow you to get predictive and pre-emptive on devices that may be moving toward downtime and disruption,” Mobley said. “This truly leverages machine learning across these big data sets to attack the high-availability requirements our customers have.”
Cisco also updated the Automated Fault Management feature, which detects problems in real-time and automatically open cases without human intervention. With version 2.0, this feature can support complex sequences of events and in November will integrate with ServiceNow through APIs. “This really takes automation into what is a heavily-manual effort and reduce time to resolution,” Mobley said, citing a large cable operator customer that used Automated Fault Management to reach resolution 30 percent faster and prevent an $8 million loss in subscriber revenue during a one-year timespan.
The third update extends the reach of Business Critical Insights beyond Cisco hardware and software and gives customers visibility across a range of third-party platforms. This capability now reports on inventory, software upgrades, configuration changes, and software and configuration compliance. “1.0 was Cisco only, and in 2.0 we are also announcing an open API that will allow our customers to create their own customized set of reporting capabilities,” Mobley said.
If all of this sounds similar to Cisco’s intent-based networking, that’s because it is.
Both are about “expertise powered by analytics and automation,” Mobley said. As Cisco’s intent-based networking continues to evolve, the technology underneath such as AI and automation will become increasingly aligned with Business Critical Services and those capabilities. “Business Critical Services leverages a lot of the same types of capabilities you will see in our intent-based networking platform,” he said.