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Top 10 Network Monitoring Best Practices in 2024

Updated on May 14
4 min read
Written by
Cem Dilmegani
Cem Dilmegani
Cem Dilmegani

Cem is the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per Similarweb) including 60% of Fortune 500 every month.

Cem's work focuses on how enterprises can leverage new technologies in AI, automation, cybersecurity(including network security, application security), data collection including web data collection and process intelligence.

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Top 10 Network Monitoring Best Practices in 2024Top 10 Network Monitoring Best Practices in 2024

The efficiency of network infrastructure play pivotal roles in the overall performance and reliability of IT services. The network monitoring is essential as networks become more complex, integrating numerous devices, applications, and protocols. It is essential for maintaining network performance and security, offering insights into traffic, reoccurring issues.

Implementing network monitoring best practices requires a structured approach. This article will delve into the best practices of network monitoring, offering a structured approach.

Network Monitoring Best Practices: Carry out initial diagnostic & setup

1. Analyze historical data

Collecting and analyzing historical data is valuable for capacity planning and understanding how network performance changes.

  • Collect and store historical data: Ensure the system retains historical performance data for analysis.
  • Trend analysis and capacity planning: Analyze this data to identify long-term trends and plan for future network capacity needs.

2. Assess network infrastructure

Monitor all network components to ensure complete visibility across the network infrastructure.

  • Inventory network devices: List all devices within network, including routers, switches, servers, and endpoints.
  • Understand network architecture: Get a clear view of how network is structured, including its topology and critical components.

3. Set up a network monitoring system

This phase involves selecting the appropriate tools and configuring them to suit network’s unique characteristics and needs.

  • Select a network monitoring tool: Choose a tool that fits the network size, complexity, and specific requirements. Consider tools like SolarWinds, AKIPS, PRTG Network Monitor, Zabbix, or ManageEngine OpManager.
  • Configure initial settings: Install network monitoring software and configure it to recognize all the network devices and components.

4. Automate monitoring and management

Automate the diagnostics and remediation processes to resolve issues more quickly. This reduces downtime and the manual effort required from IT staff.

  • Implement real-time monitoring: Ensure system can monitor network performance and security in real time.
  • Automate responses: Where possible, automate responses to common issues, such as restarting a service or blocking suspicious traffic.

5. Utilize automation for problem resolution

Incorporating automated remediation into the network monitoring strategy can improve response times and reduce manual intervention for common issues.

  • Integrate with change management systems: Ensure automated remediation actions are logged and integrated with the organization’s change management systems. This provides visibility into automated actions taken and allows for audit trails.
  • Test automation scripts regularly: Regularly review and test automation scripts to ensure they perform as expected. This practice helps avoid unintended consequences of automated actions under different network conditions.

Network Monitoring Best Practices: Facilitate continuous monitoring with alerts and dashboards

6. Establish baselines and alerts

Establish baseline metrics for normal network behavior and use them to detect anomalies. Understanding what is normal helps in identifying potential problems or security breaches.

  • Monitor key performance indicators (KPIs): Identify and monitor KPIs relevant to network’s performance, such as bandwidth usage, packet loss, latency, and error rates.
  • Set baseline metrics: Determine what normal network behavior looks like by establishing baseline metrics for each KPI.
  • Configure alerts: Set up alerts for when metrics deviate significantly from baseline levels, indicating potential issues.

7. Customize dashboards

Using customized dashboards ensure that stakeholders have access to the data they need. For example, Amazon has a network infrastructure that requires constant monitoring to ensure smooth operations. The IT department uses network monitoring software that provides the ability to create customized dashboards.1

  • Personalize views: Customize network monitoring dashboard to display the most critical information at a glance, tailored to different roles within IT team.
  • Interactive and dynamic data visualization: The dashboard includes interactive elements like graphs and charts, which allow users to drill down into the data for more detailed analysis
aws dynamic monitoring dashboard


Network Monitoring Best Practices: Collaborate with internal and external stakeholders

8. Integrate security

Integrate network monitoring with security infrastructure to detect and respond to potential security threats alongside performance issues.

  • Combine monitoring and security tools: Integrate network monitoring solution with security infrastructure to monitor for both performance and security threats simultaneously.
  • Regularly update and patch: Keep all network devices and monitoring tools up to date with the latest security patches.

9. Document and collaborate

Developing an effective escalation strategy requires identifying what qualifies as a problem, deciding on the notification chain, and specifying the actions needed to resolve the issue.

  • Document setup and processes: Keep detailed records of network monitoring configuration and processes.
  • Promote team collaboration: Encourage IT team to share insights and collaborate on resolving network issues based on monitoring data.

10. Engage with vendor support and community

Leveraging the expertise provided by the network monitoring tool’s vendor, as well as participating in user communities, can significantly enhance the system’s efficiency and team’s knowledge.

  • Utilize vendor support: Take advantage of support and training offered by network monitoring tool’s vendor.
  • Participate in user communities: Engage with online forums or user groups related to monitoring tools for additional tips and best practices.


What is network monitoring?

Network monitoring is the continuous observation of a network’s performance to identify and address issues proactively. It involves tracking the operations of network components like routers, switches, firewalls, and servers to ensure they function optimally and securely.

How does network monitoring work?

Network monitoring tools collect data from various network devices using protocols such as SNMP, ICMP, and WMI. They analyze this data to track performance metrics, detect anomalies, and alert administrators about potential issues.

What is SNMP?

SNMP, or Simple Network Management Protocol, is a standard internet protocol used for managing devices on IP networks. It enables network administrators to manage network performance, find and solve network problems, and plan for network growth. SNMP works by exchanging management information between network devices like routers, switches, servers, printers, and other network-attached devices. It operates based on a manager-agent model where the manager software monitors and controls agents installed on the network devices.

What is the difference between network monitoring and network management?

Network monitoring is a subset of network management. Monitoring focuses on observing and reporting network performance, while management encompasses a broader range of activities, including the configuration, optimization, and maintenance of network resources.

For more on network monitoring

Access Cem's 2 decades of B2B tech experience as a tech consultant, enterprise leader, startup entrepreneur & industry analyst. Leverage insights informing top Fortune 500 every month.
Cem Dilmegani
Principal Analyst
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Cem Dilmegani
Principal Analyst

Cem is the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per Similarweb) including 60% of Fortune 500 every month.

Cem's work focuses on how enterprises can leverage new technologies in AI, automation, cybersecurity(including network security, application security), data collection including web data collection and process intelligence.

Cem's work has been cited by leading global publications including Business Insider, Forbes, Washington Post, global firms like Deloitte, HPE, NGOs like World Economic Forum and supranational organizations like European Commission. You can see more reputable companies and media that referenced AIMultiple.

Cem's hands-on enterprise software experience contributes to the insights that he generates. He oversees AIMultiple benchmarks in dynamic application security testing (DAST), data loss prevention (DLP), email marketing and web data collection. Other AIMultiple industry analysts and tech team support Cem in designing, running and evaluating benchmarks.

Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised enterprises on their technology decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization.

He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider.

Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.

Sources: Traffic Analytics, Ranking & Audience, Similarweb.
Why Microsoft, IBM, and Google Are Ramping up Efforts on AI Ethics, Business Insider.
Microsoft invests $1 billion in OpenAI to pursue artificial intelligence that’s smarter than we are, Washington Post.
Data management barriers to AI success, Deloitte.
Empowering AI Leadership: AI C-Suite Toolkit, World Economic Forum.
Science, Research and Innovation Performance of the EU, European Commission.
Public-sector digitization: The trillion-dollar challenge, McKinsey & Company.
Hypatos gets $11.8M for a deep learning approach to document processing, TechCrunch.
We got an exclusive look at the pitch deck AI startup Hypatos used to raise $11 million, Business Insider.

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