IT Complexity Drives the Need for AI-Powered Performance Monitoring

When we think about IT complexity, we often visualize stacks of hardware appliances. But there’s growing complexity in what you don’t see — the systems, services, and tools that underlie modern applications. According to a recent study conducted by Vanson Bourne, the typical mobile or web application transaction crosses 37 different technology systems or components. This increase in complexity makes it harder for organizations to manage application performance. The study found that IT teams now spend one-third of their time dealing with application performance problems, costing organizations an average of $3.3 million annually. That’s an increase of 34 percent over the $2.5 million reported in 2018. Despite these investments in time and resources, IT teams are struggling to meet business requirements. On average, organizations reported six IT outages in the preceding 12 months in which revenue, operations or the user experience were impacted. Challenges in the Cloud Much of this complexity is being driven by multi cloud adoption. The cloud enables greater speed and agility, but it also represents a fundamental shift in how applications are built, deployed and operated. More than three-quarters (76 percent) of CIOs say they lack complete visibility into application performance in cloud native architectures. Traditional performance monitoring solutions drown IT teams in alerts that offer more questions than answers. On an average day, IT and cloud operations teams receive 2,973 alerts from their monitoring and management tools, a 19 percent increase in the past 12 months. Just 26 percent of these alerts require action, but the excessive volume of alerts causes 70 percent of IT teams to experience problems that should have been prevented. Simply put, traditional monitoring tools were not designed to handle the volume, velocity, and variety of data generated by applications running in multi-cloud cloud environments. What’s more, many organizations have multiple, siloed tools that lack the broader context of events taking place across the entire technology stack. IT teams must manually integrate and correlate alerts to filter out duplicates and false positives before manually identifying the underlying root cause of issues. AI to the Rescue? Artificial intelligence (AI) will be critical to IT’s ability to master increasing complexity, according to 88 percent of CIOs. AI-powered monitoring tools don’t just gather discrete data points and compare them to preset thresholds. They detect anomalies and analyze them in the context of multiple application components. This makes it possible to pinpoint the source of the problem automatically, saving IT teams hours if not days of effort and allowing issues to be resolved more quickly. Achieving these benefits can be difficult. You have to identify the right sources of performance data and convert that data into a common format so that it can be analyzed effectively. The latest AI-powered performance monitoring tools do some of the work by automatically discovering application components and providing a graphical display of data flows. It’s highly likely, however, that customization will be required to get the analytics you need. How Rahi Can Help The networking team at Rahi Systems has expertise in performance monitoring tools and can help you select the right solution for your environment. We can then help you determine which data sources to use and prepare the data for ingestion. Virtually every organization is becoming a software company. Applications drive interactions with customers and revenue-generating opportunities, putting pressure on IT to ensure that software is performing optimally. Let Rahi help you leverage AI-based performance monitoring to improve the efficiency and effectiveness of your operations.