Network monitoring tools are specialized solutions that help you track the performance, availability, and overall health of IT infrastructure components such as routers, firewalls, servers, switches, and applications. They fetch monitoring data from different segments of your IT stack and provide a consolidated view in a single console. This enables IT teams to identify issues proactively, analyze trends, and ensure optimal performance. On this page we will discuss the following topics:
Modern enterprise networks are hybrid (a combination of on-prem and cloud) and distributed, spanning across geographic locations with multiple branch offices and data centers. A network monitoring tool simplifies monitoring, providing complete visibility into the health and performance of every device, application, and interface. With comprehensive visibility across your network and AI/ML-powered intelligent monitoring, businesses can identify and address potential issues before they affect operations.
| Type | Pros | Cons |
|---|---|---|
|
Agent-Based |
✅The agents operate locally on the monitored devices, collecting metrics, logs, and performance data independently. This means it can continue collecting performance metrics uninterrupted, even if the central monitoring system temporarily goes down. ✅As agents are deployed locally on the device, it offloads the burden from the central system. This means agent-based monitoring scales efficiently. |
❌Data collection is fully dependent on the agent. So if the agent goes down, it can hamper data collection. ❌Agents require regular maintenance and periodic version upgrades to avoid security vulnerabilities and ensure compatibility with the latest features. |
|
Agentless |
✅Since no agent needs to be deployed on target devices, it reduces administrative overhead and simplifies deployment. ✅Since agentless monitoring uses standard protocols, it can support a wide variety of devices. |
❌In large-scale networks with thousands of devices, the total polling requests can put significant load on both the monitoring server and the network, causing slower data collection. ❌Because the monitoring system actively queries each device over the network for metrics, agentless monitoring consumes more bandwidth compared to agent-based solutions. |
Whatever industry you maybe in, one fact remains constant: network performance directly influences business outcomes. Disruptions in service delivery don’t just affect IT infrastructure, they often translate into revenue loss, poor customer experience, and operational inefficiencies.
The following are some of the core performance metrics that are common across any industry. Tracking them enables IT teams to keep systems healthy, maintain responsive services, and ensure maximum business continuity
| Metric | Description |
|---|---|
| CPU Usage | Measures processor utilization. Sudden or sustained spikes often signal resource strain or runaway processes. |
| Memory Usage | Tracks RAM consumption. Persistent high usage indicates contention, risking application slowdowns. |
| Latency | High latency degrades application performance. It can occur due to physical barriers or problems in routing protocols. |
| Throughput | Amount of data transmitted across the network within a set time. Low throughput suggests congestion or bandwidth bottlenecks. |
| Bandwidth Utilization | Percentage of available bandwidth being consumed. Helps identify overutilization, capacity needs, or traffic spikes and aids in resource optimization. |
| Response Time | Measures the time a server or application takes to respond to requests. Critical for user experience. |
| MOS (Mean Opinion Score) | A standard for evaluating voice quality in WAN/VoIP. Higher scores indicate better audio clarity. |
| Jitter | Variation in packet arrival times. High jitter disrupts VoIP calls, video meetings, and other real-time services. |
| Packet Loss | Percentage of data packets lost in transmission. Even small losses can cause dropped calls, video freezes, or transaction failures. |
Monitoring a single metric alone isn’t enough. Tracking values like CPU utilization or network latency in isolation gives only a partial view of your IT environment. To get the full picture, it’s essential to correlate metrics and understand the context behind them. Here are some best practices to keep in mind while monitoring:
Every device in your network has different importance. Critical production servers may require constant monitoring of CPU, memory, and disk usage, whereas test or development machines might need more focus on the applications or specific processes running on it. Instead of adopting the “one-size-fits-all” approach; determine the metrics that should be monitored for each type of device and prioritze them.
Polling frequency determines how often your monitoring tool collects data from devices. High-frequency polling (e.g., every minute) is not necessary for all devices and can strain the monitoring solution impacting its performance. So, set intervals based on device criticality. This optimizes system performance while still identifying potential issues in time.
Not everyone should see or have access to all monitoring data. Implement role-based access to ensure team members see only what is relevant to their responsibilities. Provide credentials with minimal privileges. For example, on a Windows machine, SNMP access is usually enough for monitoring purpose, while WMI access allow critical operations like stopping processes. By providing only the required access privileges you can avoid accidental or malicious changes to servers and devices.
Certain industries like finance, healthcare, or telecom have strict rules about system availability. Downtime beyond a defined threshold can lead to fines, penalties, or regulatory action. Ensure your polling intervals, thresholds, and alerting mechanisms are set to meet these compliance requirements. Regularly audit and adjust monitoring configurations to align with current regulations and organizational policies.
When selecting a network monitoring tool, look for capabilities that go beyond basic monitoring, here are five best practices which will be useful to you during the tool evaluation phase.
Modern network monitoring tools leverage AI and ML to handle massive volumes of data more effectively. They leverage ML techniques to set dynamic thresholds and detect anomalies and enabling you to focus on critical issues, reducing noise from false alerts. Through event correlation and root cause analysis (RCA), these tools quickly identify the underlying problem, while ML-driven forecasting predicts potential future issues and their impact, often providing actionable recommendations.
Advanced tools can even take automated corrective actions, helping prevent downtime and empowering you to take a proactive approach to network management. When selecting a monitoring solution, prioritize vendors with these AI/ML capabilities to move from reactive to intelligent monitoring.
Manual effort in performing repetitive monitoring tasks and prone to human error. With automation you can streamline routine tasks and troubleshooting, saving time and improving incident response.
In addition, check whether the tool integrates with ITSM platforms, as this can greatly enhance incident management. Features such as synchronized visualization, automatic ticket updates across systems, and CMDB synchronization ensure that issues are tracked consistently and resolved faster, providing a more connected and efficient workflow.
Troubleshooting complex issues can be challenging, especially in large IT environments. With advanced root cause analysis (RCA) capabilities, modern monitoring tools bring all relevant data into a single view, making it easier to correlate events, analyze dependencies, and quickly narrow down the source of problems.
Further with AI/ML-driven insights, these tools can even forecast potential issues and highlight why they might occur, enabling IT teams to proactively fix problems before they cascade into major outages.
When evaluating network monitoring tools, it’s important to look for full-stack observability that provides visibility across your entire IT environment, including network connectivity, servers, applications, databases, cloud and containers.
Observability goes beyond traditional monitoring by not just collecting metrics, logs and traces but correlating them to provide actionable, context-rich insights. This allows IT teams to identify the root cause of issues, predict potential failures, and proactively optimize performance.
Anlayze if any customer in your domain has used and benefited from the vendor. Whenever possible, request real-world case studies that mirror your industry needs to see the tangible impact achieved. This approach will help you choose the most suitable a vendor that not just fits your requirements but also delivers proven value.
OpManager is a vendor-agnostic network performance monitoring solution designed to manage a hybrid IT environments with ease. It supports 11000+ device templates and 53000+ metrics out-of-the-box providing end-to-end visibility across your IT stack from a centralized console.
Considered an affordable solution with robust features, it fits businesses of all sizes. Its latest Zia-powered features, including dashboards, insights, and chatbot capabilities demonstrate its commitment to meet the demands that evolve based on the industry trends.
