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    June 20, 2023

    Understanding Network Traffic Monitoring

    Network traffic monitoring has become critical in today's digital age, where businesses rely on various applications and services to operate. As the amount of data transmitted over networks continues to grow exponentially, network administrators must keep a close eye on the traffic to ensure optimal network performance and security. Network administrators must have a deep understanding of packet flows, collection methods, and analytics to ensure that their networks are secure and performing optimally.

    This blog post will explore these topics in detail and provide insights into the best practices for effective network traffic monitoring.

    What is a packet flow, and why is it essential for network administration?

    One of the most effective ways to monitor network traffic is through the observation of packet flows.

    A packet flow refers to the pattern of network traffic, including the source and destination IP addresses, the protocol, and the port numbers used. Understanding packet flows is crucial for network administration because it provides visibility into how traffic is moving across the network, which applications are in use, and where congestion and bottlenecks may be occurring. Packet flows help network administrators troubleshoot issues, optimize network performance, and identify security threats.

    Packet flows are influenced by various network parameters, including VLANs, QoS, routing, and congestion. For example, network administrators monitor packet flows to implement VLANs to segregate network traffic, prioritize QoS to ensure bandwidth is available for critical applications, and optimize routing to avoid congestion. Packet flows also provide information about potential cyberattacks, anomalous behavior, and application usage patterns.

    How to get network flow information

    Several methods can be used to get network flow information, including packet capture/DPI, NetFlow, IPFIX, sFlow, and proprietary implementations like NBAR and J-Flow. Each method has its advantages and disadvantages, especially in relation to how it fits with the distributed nature of networks and the load generated on devices.

    • Packet capture and Deep Packet Inspection (DPI) are network analysis and security techniques that involve intercepting and capturing all network traffic passing through a particular network interface or device, and then analyzing the contents of each packet to identify the applications in use.These methods provide detailed information about the network traffic but generates a high volume of data that requires significant processing power and storage capacity. It is also worth noting, however, that when network data is encrypted, Deep Packet Inspection is hampered since the contents of the packets are scrambled and unreadable by DPI tools, making it harder to analyze the traffic.
    • NetFlow: NetFlow is a flow-based protocol developed by Cisco that provides a summary of network traffic by collecting and aggregating packets into flows. NetFlow can be implemented on network devices (such as routers and switches) and provides a more scalable solution than packet capture/DPI. However, NetFlow provides less detailed information than packet capture/DPI and may not capture all packets.
    • IPFIX: IP Flow Information Export (IPFIX) is a standardized, vendor-neutral version of NetFlow that provides similar flow-based data. IPFIX provides better scalability than NetFlow and can capture more detailed information. However, IPFIX requires more processing power and may require additional configuration.
    • sFlow is a network monitoring technology that samples packet flows and generates sFlow packets containing information about the traffic. It's a lightweight method that provides real-time visibility into network traffic, making it ideal for monitoring large, distributed networks.
    • Proprietary implementations like NBAR and J-Flow are specific to Cisco and Juniper devices, respectively. These protocols provide additional functionality, such as application identification and classification, but they are not widely supported by other network devices.

    Types of network flow collection methods and where they are applied

    When it comes to flow collection, there are several options, including hardware probes, software probes, and collection through network devices. Each method has its strengths and weaknesses and is best suited for different situations depending on the network architecture and the level of granularity required.

    Flow collection through devices

    This method involves collecting flow data directly from network devices, such as routers and switches. It is straightforward to implement but can generate a high load on devices and may not be suitable for large-scale networks.

    Hardware probes

    These are dedicated devices that collect flow data passively from network segments. They are suitable for large, high-speed networks that generate a lot of traffic. This method places a low load on network devices, but it can be costly to implement.

    Software probes

    These are applications that run on servers or virtual machines and collect flow data using packet capture or other methods. They are ideal for cloud-based networks or distributed networks with a significant number of endpoints. This method is relatively easy to implement and places no additional load on network devices, but it requires more significant storage and processing resources.

    Traffic data insights to monitor

    Once network flow information has been collected, the next step is to analyze the data and extract valuable insights. For example, network administrators can use flow analytics to monitor application traffic, VoIP, and video traffic. They can also use flow analytics to detect traffic anomalies and potential cyberattacks as well as plan for capacity and projections.

    Some of the insights to look for include:

    • Application Traffic Insights: Monitoring network traffic can provide insights into how applications are being used, which ones are most popular, and how much bandwidth is being consumed by each application. This information can help organizations optimize their network infrastructure to ensure that critical applications do not slow down due to bandwidth issues.
    • VoIP and Video Insights: Network traffic data can also provide insights into how much bandwidth is being consumed by VoIP and video traffic. This information can help organizations identify if there are issues with the quality of the calls or videos, or if there is a need to upgrade available bandwidth to handle higher-quality video conferencing or other demanding communication applications.
    • Anomaly Detection Insights: Traffic data can also be used to detect anomalies in traffic patterns that could indicate a potential cyberattack. By monitoring traffic data regularly, organizations can identify abnormal traffic patterns and take the necessary actions to prevent further damage.
    • Cyberattacks: Flow data can help identify potential cyberattacks, including scanning activity or traffic from known malicious IP addresses. Network administrators can use this information to block suspicious traffic and take other measures to prevent cyberattacks.
    • Capacity Planning/Projections: Flow data can help network administrators plan for future capacity needs by providing insights into how much traffic is being generated by different applications and how this traffic is expected to grow over time. This information can be used to plan for capacity upgrades and optimize network infrastructure.

    Conclusion

    Network traffic monitoring is now critical for maintaining optimal network performance and security in today's digital age. However, it is important to use the right methods to collect flow information and gain insights from the data. By doing so, network administrators can ensure that their networks are running smoothly and securely, even in the face of increasing amounts of data traffic.

    Faith Kilonzi

    Faith Kilonzi is a full-stack software engineer, technical writer, and a DevOps enthusiast, with a passion for problem-solving through implementation of high-quality software products. She holds a bachelor’s degree in Computer Science from Ashesi University. She has experience working in academia, fin-tech,...

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