Optimizing VXLAN Network Management
Nguyen, Tuan Anh (2023)
2023
Master's Programme in Information Technology
Informaatioteknologian ja viestinnän tiedekunta - Faculty of Information Technology and Communication Sciences
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Hyväksymispäivämäärä
2023-12-11
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:tuni-2023120410449
https://urn.fi/URN:NBN:fi:tuni-2023120410449
Tiivistelmä
This thesis presents an in-depth exploration of Virtual Extensible LAN (VXLAN) technology, a key development in modern networking. VXLAN has emerged as a solution to the limitations of traditional VLANs, particularly in scalability and segmentation, which are essential in the context of large-scale data centers and cloud computing environments. The study focuses on the key components of VXLAN, such as VXLAN Tunnel Endpoints (VTEPs) and VXLAN Network Identifiers (VNI) and their role in the facilitation of advanced networking capabilities. It positions VXLAN within the 'Programmable Age' of networking, linking it with important technologies like Software-Defined Networking (SDN) and Network Function Virtualization (NFV), crucial for supporting containerization and the complexities of contemporary multi-tenant environments.
The thesis explores the integration and management of VXLAN networks, highlighting the need for advanced integrated network management tools to handle the complexities inherent in these advanced networks. The exploration covers various tools and technologies, including SDN, Ansible, Prometheus, Grafana, Zabbix, and the PLG stack, focusing on Grafana Loki and Promtail for log aggregation and analysis. The interaction between these tools and their roles in improving operational efficiency, security, and performance within VXLAN networks is carefully examined.
A crucial component of this study is the Proof-of-Concept (PoC) conducted to demonstrate the practical application and interoperability of these tools within a VXLAN environment. The PoC involved the use of two droplets in Digital Ocean to simulate a VXLAN network, employ Open vSwitch for connections, and deploy network management tools within Docker containers. This practical application not only bridged the gap between theoretical research and real-world implementation, but also provided insightful observations into the challenges and solutions inherent in VXLAN network management.
Furthermore, the thesis points out several avenues for future research, including enhanced traffic flow control through SDN controllers in VXLAN, the incorporation of deep learning strategies to improve QoS, and the application of zero-trust security principles in VXLAN environments. Each of these areas presents exciting opportunities to further develop the field of network management.
In summary, this thesis provides a detailed examination of VXLAN technology, its critical role in modern networking, and the importance of an integrated approach to network management. The insights gained from this study make a significant contribution to the network management domain, offering useful perspectives for academic research and practical applications in the changing landscape of network technology.
The thesis explores the integration and management of VXLAN networks, highlighting the need for advanced integrated network management tools to handle the complexities inherent in these advanced networks. The exploration covers various tools and technologies, including SDN, Ansible, Prometheus, Grafana, Zabbix, and the PLG stack, focusing on Grafana Loki and Promtail for log aggregation and analysis. The interaction between these tools and their roles in improving operational efficiency, security, and performance within VXLAN networks is carefully examined.
A crucial component of this study is the Proof-of-Concept (PoC) conducted to demonstrate the practical application and interoperability of these tools within a VXLAN environment. The PoC involved the use of two droplets in Digital Ocean to simulate a VXLAN network, employ Open vSwitch for connections, and deploy network management tools within Docker containers. This practical application not only bridged the gap between theoretical research and real-world implementation, but also provided insightful observations into the challenges and solutions inherent in VXLAN network management.
Furthermore, the thesis points out several avenues for future research, including enhanced traffic flow control through SDN controllers in VXLAN, the incorporation of deep learning strategies to improve QoS, and the application of zero-trust security principles in VXLAN environments. Each of these areas presents exciting opportunities to further develop the field of network management.
In summary, this thesis provides a detailed examination of VXLAN technology, its critical role in modern networking, and the importance of an integrated approach to network management. The insights gained from this study make a significant contribution to the network management domain, offering useful perspectives for academic research and practical applications in the changing landscape of network technology.