The Role of Machine Learning and AIOps in Network Performance Management

Before the pandemic brought a shift in business operations and financial instability to the world, businesses were asking IT teams to do more with less. But as the global pandemic continues, businesses are working harder than ever to manage competing network resources, growing user demands, complex troubleshooting challenges, new digital transformation initiatives and technologies, and more. IT leaders are redoubling their efforts to find effective ways to improve their networks while reducing operational costs. Many tend to lean on specialized tools, or engineers with a broader skill set to accomplish these goals. But in most cases, businesses need to consider a more holistic, foundational approach. The question is, what is the best strategy?

AIOps is an approach to simplifying IT operations that has gained widespread adoption over the past few years. Let’s explore the role of machine learning (ML) and AIOps in modern network management and the many ways it can help IT administrators transform their networks to meet today’s challenges.

Understanding AIOps

What is AIOps? According to Gartner, it “combines big data and machine learning to automate IT operations processes.” In other words, it is the next generation of IT operations, enhanced by ML and artificial intelligence (AI).

True AIOps technology consists of three key components. The first is the ability to ingest large amounts of useful data in your IT environment. This includes data in motion and at rest, as well as real-time and historical insights from a variety of sources (flow data, packet data, APIs, etc.). Next, it must use advanced ML to dynamically analyze across all of these data sources to identify patterns and correlations. This enables the platform to contextualize big data, identify root causes, and even provide predictive insights. Finally, AIOps technology allows you to proactively respond to problems as they arise. As the system learns patterns and becomes smarter, it should be able to recommend or apply remedial actions through automation. Some solutions rely on pure statistical processing to improve IT operations, but AIOps technology takes a more complex approach that includes all three components.

Transforming IT Operations

AIOps provides the intelligence you need by establishing an accurate baseline for your network from a multi-dimensional perspective. How many users do you need to accommodate? From which locations do they typically operate? Which applications and services require the most bandwidth, and at what time? Automating the management and monitoring of these types of key insights gives your team better visibility into any potential anomalies. This enables you to be more agile and proactive in resolving network issues before they impact user experience and the bottom line. It also enables you to identify and eliminate network resource waste and inefficiencies.

With AIOps, you can apply advanced, ML- and AI-based analytics to automate a wide range of tasks that are part of daily management. This includes everything from continuous monitoring to in-depth troubleshooting processes. The end result is that the level of automation reduces the skills and training requirements for your current and future team members and enables them to spend their time on other business-critical tasks.

Network tool sprawl is another major challenge that AIOps technology can solve for IT teams. According to the EMA Network Management Trends Survey, more than half of network operations teams rely on four to ten tools. These IT tools are often specialized to examine specific data sources and handle a precise set of problems. For example, application performance monitoring (APM) solutions often can't help with network degradation anomalies, while IT infrastructure management (ITIM) tools are powerless when it comes to resolving application downtime issues. AIOps can help reduce IT tool sprawl by ingesting disparate data sources and correlating insights to provide a level of visibility that would otherwise require multiple tools and solutions. This can alleviate the productivity challenges IT teams experience when switching between a handful of network tools every day.

Additionally, as many businesses rapidly move to cloud services, AIOps can provide deep network visibility that significantly reduces the operational risk of cloud migration. The added agility and flexibility can free up time and resources, allowing your IT team to directly plan and execute new digital transformation initiatives to better support the business. In addition, AIOps technology can support more effective DevOps planning and adoption through more advanced network visibility and insights. In short, in addition to the many direct benefits of AIOps technology, it can also drive and support other IT initiatives.

The road ahead

Relatively speaking, AIOps is an early-stage technology, and some enterprises are still hesitant. But one thing is certain: IT departments are in desperate need of modernization and a tangible path to minimize time and resource constraints. AIOps holds the key to a more automated, streamlined, and optimized approach to IT management, and it can help your team identify and resolve network issues more quickly and effectively.

Those who are unsure about its role in the future of network performance management and IT operations should consider how quickly ML and AI use cases are transforming other industries such as healthcare and financial services. With this in mind, it’s safe to say that AIOps will be one of the most revolutionary technologies in the coming years.