The Internet plays an important role in modern society, and its network performance impacts billions of users every day. For many network applications, network latency has a large impact on the quality of experience for the end user. Due to a lack of extensive network latency monitoring, the observability of network latency in real networks is often limited. This poses a problem for understanding network latency on the Internet today, and for assessing the impact various solutions that aim to reduce network latency have once they are deployed in the wild. This thesis addresses shortcomings with current solutions for monitoring network latency, in particular the performance of passive monitoring solutions on general-purpose commodity hardware, aiming to enable more ubiquitous latency monitoring and ultimately provide a comprehensive view of real-world network latency. We utilize the recently emerging eBPF technology to implement passive network latency monitoring inside the Linux kernel. Through experiments on a testbed, we show that our solution can monitor packets at over an order of magnitude higher rates than comparable previous solutions, allowing it to successfully monitor the latency for multi-gigabit traffic on general-purpose commodity hardware. Additionally, we demonstrate the feasibility of continuously monitoring network latency by deploying our solution inside an Internet Service Provider and monitoring the network latency for all customer traffic. Through an extensive analysis of the collected latency data, we show large differences in how network latency is distributed across different parts of the network. 

The Internet plays a vital role in modern society, and its performance affects billions of users daily. Network latency often has a significant impact on the end users' experience. However, due to limited monitoring of network latency, the observability of latency in real networks is often poor. This hinders our understanding of latency on the Internet today and makes it challenging to assess how the deployment of new networking technologies impacts latency. This thesis uses the emerging eBPF technology to improve the performance of passive network latency monitoring, aiming to enable latency monitoring on more network devices to create a more comprehensive view of latency on the Internet. By conducting controlled experiments on a testbed, we find that our solution is over an order of magnitude faster than previous solutions, making it possible to monitor multi-gigabit traffic on general-purpose commodity hardware. Furthermore, we demonstrate the feasibility of continuously monitoring latency by deploying our solution inside the network of an Internet Service Provider to monitor all their traffic. Our analysis of the latency data reveals large differences in how latency is distributed across different parts of the network.