How AI, Machine Learning Will Benefit Network Management
Artificial intelligence (AI) and machine learning will benefit network management and network monitoring going forward. And MSPs will need to know exactly how AI and machine learning will benefit them in order to use them effectively for customers.
In-house enterprise IT management will look more and more to outsource their network management and monitoring. And AI- and machine learning-powered analytics will be needed to manage and troubleshoot network issues as public cloud and private cloud models change.
“To fully realize the vision of autonomous networking requires breaking free from the boundaries of traditional, closed hardware-centric architecture and moving toward more flexible solutions,” said Rob Shore, senior vice president of marketing at Infinera, supplier of intelligent network solutions. “From a cost perspective, AI and machine learning speed up resolution by minimizing downtime with preemptive maintenance allowing for putting proactive steps in place. Network monitoring reduces operational expenditure by reducing the number of steps and the need for skilled planning.”
In addition, AI and machine learning (ML) are in the process of revolutionizing network monitoring. Adding AI/ML to IT operations – including network monitoring – is commonly referred to as AIOps, a term coined by Gartner a few years ago.
“Given the growing scale and complexity of modern networks, AI/ML is becoming imperative for maintaining business agility,” said Steve Kazan, VP of channels and alliances at Moogsoft, a provider of AIOps solutions. “Intelligent automation of AIOps consolidates alerts into critical incidents, powers root-cause analysis, and helps ops teams take swifter action to remediate problems. AIOps delivers concrete business benefit, including lower mean-time-to-resolution, improved SLAs and cost reduction. For MSPs and MSSPs, AI/ML can be used to identify event patterns and trends across customers to resolve common issues. AI and ML are also being built into security products to identify anomalous behavior indicating malware, ransomware, breaches, and other network incidents.”
Security, AI, Machine Learning and Network Monitoring
When it comes to how AI and machine learning will benefit network management and network monitoring, MSPs and MSSPs should remember that no panaceas exist. Sophisticated human understanding must balance AI-driven automation.
“AI and automation technologies extend a security analyst’s hands, allowing for quick analysis of massive amounts of data at scale — with efficiency no human analyst can match,” said Landon Lewis, CEO of Pondurance, a cybersecurity services provider specializing in managed detection and response. “Believing AI is the silver bullet that can address all cybersecurity challenges is as dangerous as the bad actors themselves. Although it can be used to detect unknown threats, AI still needs humans to provide reliable data to be effective. A lack of quality data leads to poor results. Even with quality data, trained AI tends to produce false-positives and is not good at explaining how it arrived at certain conclusions — it lacks the ability to understand context. For this reason, humans remain crucial.”
AI, Machine Learning, and Cause and Effect
Because AI and machine learning cannot determine causation – meaning that they are not able to tell why something happened – human understanding remains irreplaceable. And understanding “why” in outsourced managed cybersecurity services still has mission-critical written all over it, especially related to security incident investigations and analysis.
“Based on how AI is often marketed, many assume that AI-powered cybersecurity technology can simply replace humans,” said Jordan Mauriello, senior vice president at Critical Start, a security integrator, MDR and professional services provider. “And while its ability to ingest and process vast amounts of information is important, AI’s lack of causal reasoning is why human intelligence – especially from experienced security analysts – is still critical. Highly trained security analysts play an important role in …