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Comprehensive IT monitoring is a crucial part of any operations strategy. It enables IT ops teams to ensure systems and applications perform as they should, as well as anticipate future performance trends. From foundational infrastructure monitoring to time-series forecasting, there is no shortage of methods and tools available to keep track of it all.
Before you embark on an IT monitoring strategy, review these key terms to know which metrics and methods to prioritize.
Core categories of IT monitoring
IT infrastructure monitoring: IT infrastructure monitoring tracks the performance of enterprise hardware and software to ensure standards for systems operations. It can include server monitoring, which analyzes metrics such as compute capacity and uptime, as well as network and storage monitoring. In virtualized environments, IT infrastructure monitoring also focuses on the performance of VMs, along with VM host utilization.
Time-series monitoring: Time-series monitoring helps ops teams predict long-term trends based on patterns found in historical data. This type of monitoring digs into past metrics to forecast what's likely to occur next in a system. Organizations can use time-series monitoring to predict trends around autoscaling, required capacity and more. The time-series method can also support more accurate troubleshooting due to the expansive range of data collected over time.
Application performance monitoring (APM): APM tools track the performance of enterprise software. They monitor an application over time, offering data around demands, code execution, network bandwidth and disk read/write speeds. Admins can use this data to evaluate how an app's dependencies might affect its performance and to pinpoint the cause of any performance issues.
End-user experience monitoring: This category of monitoring measures IT performance, based specifically on the perspective of end users. It might track, for example, the response time of a virtual desktop or other user-facing applications. While end-user experience monitoring doesn't directly focus on underlying infrastructure components, such as servers or storage systems, ops teams can still use data from this type of monitoring to inform their infrastructure-related decisions. For instance, if an app runs with a higher storage resource limit, users won't face delays when they all launch the app at the start of the workday.
Real-time monitoring: Real-time monitoring provides continuous, up-to-date information on an IT environment. These monitoring tools react quickly to present events to offer a constant stream of information to admins. Real-time monitoring is especially helpful to predict equipment maintenance requirements or failures in a data center.
More helpful monitoring terms
Agent and agentless: A monitoring tool can use, or not use, what's called an agent -- a software program that IT teams need to install onto the systems or devices they wish to monitor. Agentless monitoring tools use existing communications protocols and do not require the installation of an agent program. In general, agent-based monitoring tools can provide more detailed or extensive metrics on a system's performance than an agentless tool, but they can also be more expensive and complicated to deploy.
Monitoring thresholds: Monitoring thresholds notify IT operations teams when a system's resource usage approaches certain limits. A threshold is intended to send alerts about potential issues early on so IT teams can address them before end users experience any performance lags. Admins can generally choose between static or dynamic thresholds. Static thresholds place set values on system limits -- such as CPU utilization reaching a certain percentage -- while dynamic thresholds learn the standard performance range of a system over time and alert teams when anything falls outside that range.
Dashboard: A dashboard is a console that provides a unified and visual representation of monitoring data. It can display data across a range of monitoring categories, and IT teams can customize a dashboard to show the specific metrics they choose.