Machine learning makes self-optimizing networks and applications possible. The use of machine learning in performance management strategies enhances the experience for both the end-users and the IT professionals tasked with monitoring the network and application performance.
Performance management is the strategic process and incorporated tools that track and observe data to identify any issues that will obstruct a network’s or application’s performance. The two most referenced tools are application performance management (APM) and network performance management (NPM). The objective of these tools is to prevent adverse network/application experience to the end user. While immensely beneficial, these tools at times miss critical factors that cause performance issues that can lead IT professionals to react after the fact instead of being proactive. Coupled with machine learning, however, these tools will significantly prevent bottlenecks and performance issues in a network.
Machine learning is the ability of machines to continually learn from data it gathered without being programmed to do so. By recognizing recurring problems that affect a network, machine learning targets the problem in real-time, either resolving the issue immediately before it causes performance buildups or alerting the IT admin of potential security threats.
A few products that currently use machine learning in analyzing performance management data include the AppDynamic (acquired by Cisco) analytics platform, which detects baselines. AppDynamic’s pairing of business metrics with the noise-canceling abilities of machine learning makes it able to determine “the root cause of business-impacting problems.” ExtraHop’s Addy platform discovers anomalies in cloud computing as well as anomalies in wire-data metrics via machine learning. Its product enables “the visibility infrastructure to learn about changes and anomalies on the wire and make problem resolution and security detection far more intuitive, proactive, and immediate through this added intelligence and automation.”
Here are some of the useful benefits of machine learning in performance management:
Key Benefits of Machine Learning in Performance Management
- At the 2017 Mobile World Congress, Patrick Ostiguy, founder and CEO of Accedian, notes that machine learning alleviates performance management tasks for the IT admins. In his presentation slides, he talks about “successful, self-optimizing networks, in 100 easy steps, ” touching upon how automation of performance management will allow network administrators to focus on more complex issues within their enterprise.
- Machine learning in performance management also boosts customer experience with the network or application by using predictive analytics to prevent issues that will turn into a performance blockage.
- It also is capable of detection and identification of security threats that will alert the IT team to investigate further and to install the appropriate protections.
- Machine learning responds in real-time to network and application performance issues.
