In the early 1990s, as the digital world stood on the cusp of an explosive expansion, the foundational structure of the internet faced a critical challenge: the classful IP addressing system was buckling under its own rigidity and inefficiency. Locked into fixed classes (A, B, and C), this system squandered valuable IP space, leaving the burgeoning network gasping for air as it grappled with rapidly depleting IP addresses.

A VPN, or Virtual Private Network, enables secure communications over an untrusted network. It enables users to connect to servers and networks from virtually anywhere, creating a secure tunnel between the user and a remote network or server. VPNs ensure data privacy and prevent unauthorized access, ensuring the data transmitted remains confidential and protected from external threats.

Network admins are no strangers to the challenges posed by the ever-growing demand for bandwidth, the diversity of applications, and the varying network traffic requirements. Amidst this complexity, one key player stands tall for optimal network performance – Quality of Service, also known as QoS. In networking, the term QoS holds significant weight, yet its true essence can sometimes elude even the most seasoned administrators.

Managing incoming web traffic for your applications is essential to ensuring optimal performance, preventing abuse, and maintaining the security of your cloud infrastructure. To accomplish this, one of the tools HAProxy Enterprise users have at their disposal is rate limiting—the practice of preventing clients from making too many requests and using system resources unfairly.

Despite the siren song of AI in the keynotes, visitors were far more focused on solving real-world problems. These are the issues that have plagued IT practitioners for years, if not decades: troubleshooting and validating performance and availability of their applications, services, and infrastructure.

As per a survey by Comcast Business, around 85% of IT leaders trust AI networking tools for meeting their organization’s goals. This stat alone is enough to show how big of a role AI is playing in network monitoring. And it’s just the beginning, with rapid development in Artificial Intelligence, we might see a lot more sophisticated AI use cases for network monitoring. But how exactly does AI help in network monitoring? What its roles, benefits, challenges, and how to implement it?

Businesses adopting new technologies are looking for a digital transition that assures streamlined performance upgrades while cutting costs. Servers, an important endpoint of the network, have a great influence on both aspects. Given its significance, proactively monitoring server traffic trends, bottlenecks, and optimizing the network to lessen outages or downtime is indispensable. However, monitoring without powerful strategies and tools that fulfill your business objectives is a lost cause.

Inspired by our own conversations with you at AWS re:Invent 2023, here’s what we think should be on your radar for 2024.

In the intricate landscape of contemporary network management, comprehensive and insightful tools have never been more critical. One tool that stalwartly deciphers the complexities of network traffic is NetFlow. Developed by Cisco Systems, NetFlow is a robust protocol that serves as a cornerstone for understanding, monitoring, and optimizing the flow of data within a network.