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BGP Peering Analytics For Network Traffic Flow Optimization

[fa icon="calendar"] Dec 12, 2017 2:41:34 PM / by Valentín Carela

Valentín Carela


Internet usage across the world is skyrocketing and data traffic is increasing even faster. According to Cisco, annual global IP traffic will increase by almost three times in the next few years, from 1.2 ZB in 2016 to 3.3 ZB in 2021. Internet speed is greatly improving thanks to the introduction of fibre optic connections and better routers. New generations are used to this velocity and demand ever shorter loading times for their apps, websites and tools.

Meanwhile, cybersecurity becomes a more serious threat every year as attackers and intruders become more sophisticated. Finally, cost control remains an ever more important issue for peering managers, capacity planners and network procurement. As a result, solutions are needed to help Internet providers (and their customers) deal with all these problems related to Internet usage: speed, security, cost. A useful tool for trying to overcome these challenges is BGP Peering Analytics.

BGP Peering Analytics

BGP stands for Border Gateway Protocol, a standardized exterior gateway protocol designed to exchange routing and reachability information among autonomous systems on the Internet. It’s what makes the Internet work, therefore BGP primarily concerns Internet Service Providers rather than companies themselves, although some large corporations do operate their own autonomous systems. BGP Peering describes the act of determining who to connect to on your network, and creating those relationships. BGP Peering Analytics is therefore used to identify the optimum peer connections in order to increase traffic flow speed, lower costs and optimize the movement of data for business in real-time.

How does BGP Peering Analytics work?

Most advanced  BGP Peering Analytics tools combine, for example, your raw flow records, such as NetFlow, IPFIX and sFlow, and integrate them with your BGP data in real-time. For instance, with Talaia, all you need to do is peer your network device to our platform so Talaia can get access to your routing information to compute the BGP paths metrics in your network.

Then you can dive directly into analytics by selecting your preferred time range, traffic flow destination, measure units and taking advantage of our vast variety of filters to get access to specific insights that will help you improve your routing and network traffic flow.


To filter your data set, you can look at specific IP addresses, ports, interfaces and protocols or you can choose to only view traffic flow of a certain byte or packet sizes, or simply analyze unique ASNs. You could also visualize the traffic flow of particular applications in order to optimize and prioritize your most important IT services. For example, due to its high-bandwidth consumption, it’s critical to understand the different jumps that your traffic is making to reach Netflix. In this case, Netflix provides certain ISPs that match their requirements with an Open Connect Appliance (OCA) device that replicates Netflix content within a local network. To demonstrate that an ISP complies with Netflix requirements in order to receive an OCA, some BGP Peering Analytics would be necessary.

Why you should use BGP Peering Analytics

BGP Peering Analytics have evolved because network engineers and system administrators require more powerful solutions to proactively manage and optimize network traffic flow. Here are some of the biggest advantages of using BGP Peering Analytics and some specific use cases.


  • Easy and fast identification of any traffic path or peering anomalies
  • Complete overview of traffic source, paths and destination for specific peers, sites and apps
  • Visualization of paths with the ability to select any specific traffic-infused path to observe detail within, and evolutions over time
  • Insights into geographical traffic destination
  • Ability to predict cost of traffic paths

Use Cases

There are several great examples of how you can apply BGP Peering Analytics to improve your networks and traffic flow. For example, it can be employed for network planning of uncertain traffic demands. By using BGP to calculate the best route, you can reduce the required link capacities for unknown outgoing border routers. You could also leverage it to pin down who your traffic is going to, how it gets there and in which country it finally ends up. It can also be applied to nail down how much traffic flow stems from a specific server or peer, where it goes to and how much it costs you.

Moreover, it can also be helpful in ensuring your peers are picking up the traffic you want them to. Another common application method is to identify who you should interconnect with directly and which transit provider you should choose for your next circuit purchase. Additionally, it can be also used to figure out whether new circuits need to be added to your network, and whether they should be internal or external. ISPs can benefit from BGP Peering Analytics to locate new sales opportunities by identifying potential customers that aren’t connected yet, but whom they’re already sending traffic to.


BGP Paths Analytics give you a clear overview of what paths you're using and how much data flows through each of them

In addition, using BGP Peering Analytics with Talaia opens up a whole new field of use cases. For instance, you could compare the results of BGP paths with the application identification option in order to ascertain which type of traffic is flowing for each BGP path. Moreover, you can also apply it to compare data with the anomaly detection tab in order to see the paths that internal attacks were taking. Finally, by leveraging the Top N tab you can find out which paths are following the IP address that produces the biggest amount of network traffic. Of course, there are countless other use cases. If you want to get a better idea and understanding of BGP Peering Analytics, you can experiment with our free trial here.


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Topics: Cyber-Security

Written by Valentín Carela

Valentín is currently Product Manager and Lead Researcher at Talaia. He is also an external collaborator at the Broadband Communications Research Group (CBA) from UPC BarcelonaTech, where he obtained his Ph.D. in Computer Science about network traffic analysis and classification using Deep Packet Inspection and Machine Learning techniques.