Network monitoring tools are essential for keeping networks up and running in 2026. IT teams deploy monitoring tools in all shapes and sizes to check the uptime of their devices, monitor performance metrics, and diagnose hardware health issues. While they are unquestionably important in maintaining network operations, there is one catch. If network monitoring tools are not deployed properly, they can cause more visibility gaps than they solve. In this guide, we start from the basics and explain the best practices you can take when deploying a network monitoring tool.
Some pre-requisites to read before we get started
Set role-based access control
User access management is the cornerstone of modern cybersecurity. Identity has replaced the traditional network perimeter. Most breaches involve leaked credentials, secure and partitioned user access acts as the first line of defense.
When you're setting up a network monitoring tool, you have to consider the people who are going to run it day to day. Not everyone needs access to everything. Network admins need access to the network devices. SRE teams need access to a particular site. CIOs need dashboards detailing overall system performance.
Setting up role-based access control ensures this. By linking user login and credentials to a defined role, you can restrict their access to exactly what they need. This minimizes the chance of data exfiltration and compliance violations. It also makes auditing easier.
Add devices to be monitored
Once role-based access controls are set up, you have to add devices that have to be monitored. When you're adding devices, it's essential to follow an organized approach. Adding all the devices in your network without supervision can do more harm than help.
- It increases the load on the monitoring tool
- Your monitoring dashboard becomes cluttered
- License costs goes up
- You lose visibility into critical devices
Therefore, before you start adding the devices into your monitoring tool. You should take stock of your infrastructure and ask the following questions. These questions can come in handy during the latest stage of your network monitoring tool setup as well.
- How important is this device in my day to day ITOps?
- Can I afford one hour of downtime for this device?
- How easy is it to troubleshoot and fix this device when it goes down?
Based on these questions, you can prioritize the devices in your IT infrastructure and organize them effectively. Once you have stock of your infrastructure, you can start the network discovery.
Choose the right discovery mechanism
Network discovery is the process of finding devices in your network and adding them to your monitoring inventory. Network monitoring tools use IP addresses or DNS names to identify devices and offer multiple mechanisms for discovering them.
IP subnets and ranges: This is the most common network discovery mechanisms. IP addresses are scanned from a manually configured range or a defined subnet. IP scans are perfect for organizations that enforce network access control and DDI governance.
Importing from the Active Directory (AD): Many organizations use AD to implement user authentication, policy implementation, and access control. For them, importing devices directly from the AD simplifies network discovery.
Importing devices from a CSV file: This is the most straightforward discovery mechanism. Device records are uploaded into the monitoring tool from a CSV file. This is suited for smaller organizations that do not exercise active DDI governance.
Using vendor technologies: Many device technologies like Cisco Meraki and Nutanix HCI can be discovered with their vendor APIs. All you need to provide is the API and the entire tech stack is discovered in the monitoring tool.
Syncing from the helpdesk: If your organization is incident response-focused, it makes sense to tightly integrate your monitoring tool and helpdesk. In such integrations, you can discover devices from your helpdesk.
Choose safe and secure credentials
Network monitoring credentials are the authorization keys and login details like SNMP community strings, SSH/Telnet logins, and WMI/Windows parameters, configured within network monitoring tools. Credentials ensure that the tool can access your network data securely. with credential vaults, rotating credentials.
Least-privilege access: When choosing credentials, it's recommended to use dedicated monitoring-only credentials. This ensures that the tool only has read access, protecting the infrastructure if the monitoring tool is compromised.
- For SNMP v1 and v2c community strings, you can disable write access while setting up the credentials. For SNMP v3, advanced authentication and encryption methods like SHA and AES is available.
- For WMI credentials in Windows devices, you can avoid using the domain admin account for setting credentials. You can create a standard domain user and use these credentials.
- It's recommended to use SSH for setting up Linux credentials. You can also map the SSH key to a non-root user with no sudo rights to further restrict access.
Credential vaults: Tools like ManageEngine OpManager comes with storage vaults where you can add credentials. Once added, you can easily access them as a credential library to associate them during device discovery. Configured passwords are not revealed. This ensures additional security for sensitive credentials.
Rotating credentials: Credential rotation is the practice of changing monitoring passwords, keys, and community strings on a schedule to reduce the risk of breaches. While setting up credentials, you can plan a rotation schedule and share the rotating credentials with trusted users. Using dedicated password management tools further streamlines and secures this.
Schedule discovery scans
Networks are dynamic: devices are added and decommissioned regularly. This often results in inconsistencies between what you're monitoring and what's actually running your network. To avoid this, you can schedule network discovery runs at regular intervals. For instance, you can add an IP range where you'll add newly discovered device and configure a rule to remove devices from the monitoring inventory if the IP address is not found.
It's recommended to align discovery scans close to the time when you're making changes to the network. For instance, if your planned maintenance window falls on a Thursday night, you should schedule discovery on Friday. This reduces the time window for which your devices are unmonitored.
With network monitoring tools like OpManager, it's possible to add discovery rule automation and discovery filters. This allows you to define what devices to add based on the device type, vendors, IP address etc. This limits blind discovery runs and waste of monitoring load.
Leverage dynamic topology maps
Network monitoring tools use topology maps to draw layer 2 networks and their connections. They usually use protocols like LLDP, CDP, ARP, and FDB for this. You can enable regular mapping from a core device for these.
As long as your core device remains unchanged, you get a dynamically updating topology map. This helps you visualize changing network topology, rather than seeing it in a list or a spreadsheet.
Keep scalability in mind
It's recommended to keep scalability in mind always, even before you start monitoring. You might be monitoring a manageable amount of devices now, but you should also account for the expected growth a few years down the line.
- Add custom fields: Custom fields or meta tags help provide additional context for discovered devices. For instance, your monitoring tool will identify the vendor and model of your device, but things like department, location, and ownership is additional context that you can associate with it. This comes in handy for organizing and managing devices once you scale up.
- Add devices to groups: Once your infrastructure scales into the thousands, groups remain the only meaningful way to manage them. Adding devices to the right groups from the start makes scaling up easier in the long run.
Define what you're monitoring
Once discovery is done and you've refined the infrastructure you want to monitor from the others, you can start to think about what to monitor. Monitoring metrics come with important nuances. Without clarity into the metrics and why you are monitoring them, you could be surprised with outages and faults even when your network monitoring tool gives you an 'all clear' sign.
How can you be clear about what you're monitoring?
- Does the metric indicate the health of the device as a whole or just a component?
- Does it behave in a predictable way? Can you correlate this metric with downtime or outages?
- What are the minimum number of metrics you can monitor for a device without losing visibility into its operations?
- Will this metric provide insights for fixing this device and restoring services during outages?
- Does monitoring this metric prevent permanent degradation to the device?
- What role does this metric play in business service delivery?
By asking these questions, you and your team know what metrics to monitor, why they are important, and what will be impacted when they cross a certain limit. Furthermore, this would aid in troubleshooting down devices and assessing network performance.
The following are some metrics that are commonly monitored by IT teams. Tracking them helps teams to keep systems healthy, maintain services, and ensure 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. |
Set monitoring intervals
You've chosen what to monitor, now you have to decide how often to monitor them. The less the monitoring interval, the higher the load on your monitoring tool. Setting monitoring intervals is usually a question of how important that metric is to you and how much time you can afford without actively checking it.
For instance, a server that hosts the electronic health record in a hospital is critical for day to day operations. You might want to monitor it every minute to ensure minimum disruptions. At the same time, the WiFi in the cafeteria is less important, you can set a monitoring interval of one hour or more.
Choose monitoring mechanisms
Monitoring mechanisms dictate how your network monitoring tool collects information. Based on the technology used, the device monitored, and the level of detail presented, you can choose different types of monitoring mechanisms:
Network protocols: Network protocols like SNMP, Telnet, SSH, and WMI are used to collect data on-demand over the network. The network monitoring tool queries the monitored device using this protocol and retrieves the data. These monitoring mechanisms are suited for network devices and servers you want to monitor at a regular rate.
Monitoring agents: Monitoring agents are lightweight software packages that reside within your devices. They send monitoring data at regular intervals to your monitoring tool. Agents communicate over an outbound port without the need for inbound ports. They are useful when you require strict security that network protocols cannot provide.
Streaming telemetry: Streaming telemetry use push-based communication standards to stream real-time data to monitoring tools. gNMI is the modern standard for streaming telemetry in network hardware. YANG Push is an older telemetry standard. These are useful when monitoring mission critical devices where you want data at sub-second intervals.
Passive monitoring: Passive monitoring mechanisms like Syslogs and SNMP traps are a useful low-overhead fail safe for devices that you don't have to monitor until they fail. Syslog and trap receivers allow monitoring tools to listen for these signals.
Calculate baseline performance
No matter how good your monitoring is, when they're not configured to alert you, they are useless. To configure alerts, you need to know what constitutes as normal performance and what is alarming. Most network monitoring tools allow you set thresholds or limits for monitored metrics. If these are violated, you get alerted.
As an IT admin, you can guess the normal limits of good performance for a router or a server, but this may not always hold true. If you set it too low, you'll start getting a flood of alerts from devices that do not need your immediate attention.
On the flip side, setting the baseline too high might make it look like your systems are perfectly fine. Until your app goes down without warning and you have no idea whether it was the database, network, or the DNS.
You can calculate the baseline for each device and assign the right threshold. But annoyingly, they vary from device to device, peak hours, and seasonal variations. Scale this up to hundreds and thousands of devices and you have an unmanageable situation.
Network monitoring tools like ManageEngine OpManager uses machine learning to automate this process. The tool trains the ML engine with past monitored data. The ML engine calculates the baselines for your devices and sets alarm thresholds at just the right limit. These values are automatically adapted to adjust to peak hours and seasonal variations. The best part is that ML engines get more accurate with more data, ensuring more precise monitoring as time goes by.
When to choose hard limits and when to resort to adaptive thresholds
Adaptive thresholds enhance scalability and monitoring efficiency by calculating and updating network performance baselines automatically. However, for certain devices and metrics, static limits can be useful.
For instance, you may use GPU chip-sets with a thermal threshold, beyond this threshold, the GPU might throttle its performance to protect its silicon. In this case, you can set up a static threshold below the GPU's thermal threshold. This lets you know when the GPU is about to throttle and take preventative action.
How to ensure accuracy for machine learning models?
Machine learning engines time and data to learn network behavior. It's recommended to monitor the network normally for up to two weeks before deploying machine learning powered adaptive thresholds.
Know your SLA terms
Before you configure a single alert, you need to know what you've actually promised, and to whom. Service Level Agreements set the bar for uptime, response, and resolution that your infrastructure needs to clear. That commitment might come from a vendor to you, or from your team to the rest of the business. Either way, your monitoring tool is what tells you if you're meeting it.
A few terms come up again and again when you're working with SLAs:
- Uptime percentage: the share of time a service is expected to stay available, usually written in "nines." Small differences in the decimal add up fast.
- MTTR (Mean Time to Recovery): how long it takes, on average, to restore a service once it goes down.
- MTTA (Mean Time to Acknowledge): how long it takes, on average, for someone to notice and respond to an alert.
- MTBF (Mean Time Between Failures): how often a device or service tends to fail between one recovery and the next.
| Uptime % | Downtime allowed per year |
|---|---|
| 99% | 3.65 days |
| 99.9% | 8.76 hours |
| 99.95% | 4.38 hours |
| 99.99% | 52.6 minutes |
| 99.999% | 5.26 minutes |
Take a payment gateway promised at 99.99% uptime. That leaves under an hour of downtime a year. A single undetected outage could burn through most of that budget on its own. Once you know the SLA behind a device or service, you can work backwards from it. Tighten monitoring intervals, alert thresholds, and escalation timers until they catch problems inside your allowed window, not after you've already broken it.
Configure high availability
A monitoring tool that goes down creates a dangerous blind spot, especially when your team assumes everything is still being watched. By the time someone notices the dashboards have stopped updating, the SLA clock from the last section could already be running out.
High availability protects against exactly this. Instead of running your monitoring tool on a single server, you set up a secondary instance that can take over the moment the primary fails.
- Primary-secondary failover: the secondary server stays on standby, syncing configuration and monitored data from the primary. If the primary goes down, the secondary picks up polling within minutes, sometimes seconds.
- Distributed polling engines: for organizations with multiple sites, a central server can delegate polling to local probes at each location. If the link to one site drops, the rest of your network stays monitored.
- Database replication: your monitoring database holds your device inventory, historical performance data, and alert configurations. Replicating it to a standby server means you don't lose this history if the primary database fails.
Tools like ManageEngine OpManager let you set up this kind of primary-secondary failover directly, so switching over doesn't depend on someone rebuilding a server by hand at 2 a.m.
It's worth testing your failover setup on a schedule, not just trusting it'll work when you need it. A failover that hasn't been tested in six months is a guess, not a guarantee.
Set up notification channels
An outage nobody hears about isn't really being monitored. It's just being logged. Once you've set your baselines and thresholds, you need a way to put that information in front of the right person, fast.
Choosing the right notification channels:
- Email/SMS: the most universal option, and often the default. Email suits lower-priority alerts that can wait for someone to check their inbox. SMS works better for urgent alerts, since it doesn't depend on an internet connection or an app being left open.
- Mobile apps & push notifications: these reach the on-call engineer wherever they are, without the delivery delays email sometimes has. Many teams pair this with an acknowledgement feature, so the alert stops repeating once someone confirms they've seen it.
- REST API/Webhooks: webhooks let your monitoring tool notify any external system that can accept an HTTP request. Think ChatOps tools, custom dashboards, or in-house scripts. This is the most flexible option, though it takes some setup on the receiving end.
- Third party integrations: prebuilt integrations with tools like Slack and Microsoft Teams save you from building your own webhook receivers. These usually come with routing, scheduling, and on-call rotations already handled by the third-party tool.
Most teams end up using more than one channel: SMS and push for critical alerts, email or a chat channel for everything else. Match the urgency of the notification method to the urgency of the alert. A flood of SMS messages for minor warnings just trains people to ignore them.
Plan incident response
An alert firing is just the beginning. What happens next decides whether it turns into a five-minute fix or a multi-hour outage. Who gets notified, what they do, and how the incident gets tracked, all play a part.
Alerting the right team
Sending every alert to every engineer only guarantees that people start ignoring them. Just like the role-based access you set up earlier, you can configure alert routing so the right team hears about an issue based on device type, location, or severity.
Integrating your monitoring tool with your helpdesk or ITSM platform takes this further. Tools like ServiceDesk Plus, ServiceNow, and Jira Service Management all support this kind of integration. Instead of an alert just sitting in a dashboard, it opens a ticket on its own, assigns it to the team on call, and starts the escalation clock. If nobody acknowledges it within your MTTA target, it escalates to the next tier automatically.
Creating automated workflows
Some incidents follow a pattern you can predict, and predictable problems don't need a human in the loop every single time. Automated workflows let your monitoring tool take a first pass at fixing common issues before anyone gets paged.
A disk nearing capacity can trigger a script that clears temporary files. A service that's stopped responding can be restarted on its own. An unresponsive device can be pinged with a diagnostic script to gather logs before an engineer even opens the ticket.
These workflows won't replace human judgment for complex incidents. But they cut the noise, so the alerts that do reach your team are the ones that actually need attention.
Create dashboards and reports
Different people need different views of the same network. Going back to the roles you set up at the start, a network admin troubleshooting a switch needs different information than a CIO reviewing overall system health.
- NOC dashboards: real-time, detail-heavy views built for the team actively watching the network. These usually show device status, active alerts, and topology maps side by side.
- Team or site dashboards: scoped to the devices a specific team or location is responsible for, so engineers aren't wading through data that isn't theirs to manage.
- Executive dashboards: high-level summaries, uptime percentages, SLA compliance, and trends over time, built for people who need the headline, not the packet-level detail.
Reports serve a different purpose than dashboards. A dashboard shows you what's happening right now. A report shows you what happened over time, which is useful for spotting trends, planning capacity, and proving SLA compliance to stakeholders who'll never log into the monitoring tool themselves. Schedule these reports to generate and send on their own. Weekly works well for operational reviews; monthly or quarterly suits SLA and capacity reports. That way, the right people see them without anyone having to remember to pull the data by hand.
Monitor the monitoring tool
By this point, your monitoring tool has become the single source of truth for your network's health. That's exactly why it can't be a blind spot itself.
Monitoring the monitoring tool starts with the resources of the server it runs on: CPU, memory, disk space, and database size. A monitoring tool that runs out of any of these can quietly stop collecting data long before anyone notices the dashboards have gone stale. It also means watching the tool's own internal health. Polling queues that back up, or a growing list of devices stuck showing as unreachable, are both early signs it's struggling to keep pace with your network.
A lightweight, independent heartbeat check is worth setting up here, something outside the monitoring tool itself that simply confirms it's up and polling on schedule. It's a small addition, but it closes the last gap in an otherwise well-monitored network: the one blind spot where the tool watching everything else could stop working without anyone noticing.
Get started with ManageEngine OpManager
Interested to set up a network monitoring tool with these best practices? Head over to ManageEngine OpManager's thirty-day free trial to get started right now. You can also build a custom demo of OpManager with the help of our product team.
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By Visakh,
ManageEngine Team