GUEST OPINION: Infrastructure monitoring is the observational and analytical backbone of any IT landscape, giving businesses a comprehensive view of operations that goes beyond simple component surveillance.
Given IT infrastructure supports business operations directly, the insights gained from monitoring are critical for maintaining business continuity, improving service delivery, and achieving business objectives. The ability to predict and prevent downtime, optimise performance, and manage an IT environment with a holistic view means that businesses can avoid costly disruptions, maintain a competitive edge through high performance, and ensure customer satisfaction by providing reliable services.
However, without proactive infrastructure monitoring tools, 74 per cent of IT leaders report spending more than a full business day each week troubleshooting and reacting to incidents, according to LogicMonitor’s Future Further report.[1]
Nitin Navare, chief technology officer, LogicMonitor, said, “Infrastructure monitoring is a critical element of many businesses’ daily operations, delivering essential insights into system performance, interaction, and the potential impact on overall service delivery. Relying on manual processes for infrastructure monitoring results in teams that are constantly reacting, troubleshooting, and on the receiving end of complaints, demands, and blame.
“Increasingly, organisations are turning to artificial intelligence (AI) technologies to enhance their infrastructure monitoring processes and improve operational efficiency and safety. Importantly, AI-driven solutions optimise the maintenance and functionality of critical infrastructure, as well as significantly reduce costs and downtime, bolstering economic resilience and sustainability. Organisations that fail to modernise their manual infrastructure monitoring processes risk being left behind by their competitors who embrace more technologically advanced solutions.”
AI adoption in infrastructure monitoring delivers several key benefits to businesses, including increased efficiency, enhanced safety, cost reduction, and data-driven decision-making. AI technologies, including machine learning (ML), neural networks, and deep learning, are key in processing and analysing vast amounts of data generated by infrastructure systems. These technologies facilitate applications such as predictive maintenance, which uses data from sensors and other sources to forecast potential failures before they occur. This proactive approach helps in scheduling maintenance only when necessary, reducing downtime and extending the life of equipment.
In this way, AI-driven infrastructure monitoring systems streamline operations, minimise manual interventions, and automate routine tasks, contributing to safer infrastructure, preventing accidents, and ensuring greater safety by identifying potential issues early. Additionally, AI also helps in reducing operational and maintenance costs by predicting failures and optimising resource allocation, giving decision-makers access to more comprehensive, accurate data analysis to make informed choices about infrastructure management.
Navare said, “AI integration into infrastructure monitoring can be challenging. Setting up AI systems requires significant upfront investment in technology and training. The extensive data required for AI applications raises concerns about privacy and data protection, necessitating robust security measures. There is also a need for skilled professionals who can develop, maintain, and interpret AI systems in the context of infrastructure. Over-reliance on AI could also lead to vulnerabilities, especially if systems fail or fall victim to cyberattacks.
“Businesses can address the challenges associated with AI integration by partnering with a specialist in AI solutions, providing the necessary expertise and resources to streamline the implementation process, mitigating the high initial investment and technical complexities involved. Such a partnership can also offer training and support to develop the in-house skills required to manage and optimise AI systems effectively while ensuring that AI applications adhere to stringent data privacy and protection standards, alleviating security concerns.”
The primary benefit of AI-driven infrastructure monitoring is a cohesive IT infrastructure monitoring approach that pairs intelligence with alerts, so teams aren’t forced to react all the time. Businesses will see how their technology is connected to the customer immediately by gaining full observability into their IT across clouds, networks, and data centres. This will ultimately position organisations for long-term resiliency and growth while freeing up time and resources to turn ideas into meaningful actions.
[1] https://www.logicmonitor.com/press/future-further-new-logicmonitor-research-shows-hybrid-it-infrastructure-is-here-to-stay