A closer look at the key technologies enabling core business system modernization

BrandPost By Lafe Low
Sep 18, 2019
IT Leadership

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Credit: iStock

In today’s hybrid blend of on-premises and virtual servers, public and private cloud platforms, and mobile devices of all types, it is more critical than ever to identify, resolve, and mitigate potential outages or performance issues. And these issues are now more difficult to detect and identify, much less remediate. Both the volume and variety of network and application traffic that data enterprises are generating have skyrocketed.

To effectively monitor and manage IT operating at this level of complexity, organizations are turning to artificial intelligence for IT operations, or what’s called AIOps. The term AIOps describes using artificial intelligence (AI), machine learning (ML), and other advanced data analytics technologies to automate the processes of identifying and resolving IT performance issues. AIOps uses the massive amounts of data generated by IT systems and services—both physical and virtual—to monitor all those enterprise assets, proactively examine network and application traffic data, and achieve full visibility into all applications and system dependencies.

With its advanced capabilities, AIOps can immediately identify and resolve any potentially damaging problem, often either as it’s happening or before it even happens, by identifying other conditions or situations that precede the problem. Enterprises put AIOps in place to take in and analyze IT operational data to augment and automate all major IT operations.

Once that data has been analyzed and events prioritized, the AIOps system presents that data in a dashboard view to IT managers so they can respond appropriately. AIOps gives them the tools and immediate feedback to stay on top of IT operations. Gartner predicts larger enterprises’ use of AIOps and digital experience monitoring tools for monitoring applications and infrastructure will rise from 5% in 2018 to 30% in 2023.

Automation Is Essential

Automation, which is critical to running AIOps smoothly and efficiently, helps drive AIOps to perform:

  • Automated monitoring: discover the full environment and identify when new endpoints, such as a virtual server or machine, a new mobile device, or even a new cloud platform, are brought up
  • Automated AIOps: run AIOps while adhering to established policies and dependency mapping and requiring no advance configuration
  • Automated remediation: quickly and efficiently execute the necessary steps to resolve any fault or performance events

AIOps helps enterprises consolidate and analyze infrastructure operational data coming at them at a rapidly increasing pace from myriad sources. It can actually reduce the overall volume of potentially damaging events, provide alerts to conditions that could cause an outage, isolate the cause of those events, and apply process automation to remediate events. AIOps increases the effectiveness of infrastructure resources, expedites service request and problem resolution, and generates consistent value from the underlying IT infrastructure and its ability to fully support new and ongoing business initiatives.

Benefits of an Automated AIOps Solution

Bringing the power of automation into AIOps conveys several significant benefits for enterprise-wide IT operations. It can greatly increase the effectiveness of AIOps tools and services, lowering expenses and saving time while increasing efficiency. It can also reduce the amount of effort and time required to process service requests and resolve potential outages or performance issues. All of this adds up to significantly reducing business risk, improving service performance, and shortening time-to-market for new innovations and initiatives.

“AIOps without automation provides only part of the advantage. Setting up monitoring and actually fixing the problem manually is time-consuming,” says Michael Procopio, product marketing manager at Micro Focus. “Without automating monitoring, you will miss events. Without automating runbook remediation, it can take two to five times as long to get the problem fixed. Either way, your business team will not be happy with you.”

Automated AIOps follows a three-phase approach: automated discovery, conducting AIOps itself, then automated remediation. Another way to think of this model is “sense, analyze, and adapt.” The solution would first sense the environment to detect what is there, next analyze the environment and identify any events in process or about to occur, and then adapt to what is happening (this is where the automation component truly comes into play) to resolve and remediate any potential issues.

  • In today’s dynamic, hybrid IT environments, entire applications or even application components go up and down nearly every second. Without engaging in automated discovery, it would be easy to miss much of what is occurring within an environment at runtime speed. IT operations staff need that comprehensive visibility into the entire infrastructure, all activity—whether physical or virtual, on-premises, or in the cloud—and all mobile network endpoints through end-to-end infrastructure, application, and data monitoring.
  • AIOps is based on ML, and there are two types of ML—supervised and unsupervised. Unsupervised ML, which is automatic, learns on its own and requires no human configuration. With it, AIOps can reveal application dependencies and all available IT resource data for instant problem resolution. AI-based analytics helps automate log and event management. Events are discovered and monitored, but that monitoring also reveals the cause of events. AIOps positions event logs in context for continuous real-time correlation, historical analysis, and predictive analytics. It should be able to analyze data from any source, in any format, and at any scale. The extent of this comprehensive analysis can even help reduce events by as much as 90%.
  • Once AIOps identifies a problem or even a potential problem, automating remediation functions helps resolve issues quickly, easily, and with agility. By streamlining and automating such complex tasks, regulated industries can strengthen their regulatory compliance standing by eliminating opportunities for manual input errors.

The Future of AIOps

Enhanced IT operations management powered by automated AIOps can help enterprises more closely and accurately monitor infrastructure, applications, and data; proactively detect potentially damaging outage problems; and then more quickly resolve those problems. All of this brings enterprises to a position where they are better equipped to fulfill strategic initiatives, reduce overall business risk, and shorten time-to-market.

To learn more about how AIOps can help enterprises more efficiently manage their diverse infrastructure, go to www.microfocus.com/opsbridgeanalytics.