Kubernetes is an excellent solution for building a flexible and scalable infrastructure to run dynamic workloads. However, as our cluster expands, we might face the inevitable situation of scaling and managing multiple clusters concurrently. This notion can introduce a lot of complexity for our day-to-day workload maintenance and adds difficulty to keep all our policies and services up to date in all environments.

For extremely high throughput web applications, it is important to load balance the traffic across multiple servers. However, load balancing the traffic alone is not enough at times. The reverse proxy server that handles the workload needs to be performant, too. In our previous article, we discussed the NGINX reverse proxy server and understood how to monitor it. In this article, we set up monitoring for an even more performant reverse proxy server - HAProxy.

Network traffic analysis is an important aspect of computer network management. Organizations can gain valuable insights into the behavior of their network infrastructure, identify potential security threats, and optimize network performance by monitoring and analyzing network traffic. Several network traffic analysis tools have been developed to aid in this process, each with its own set of features and capabilities. What Is Network Traffic Analysis?

Today’s networks support a lot of traffic data, especially with the adoption of embedded systems. Furthermore, the complexity of the data passing through networks has significantly increased. Yet system administrators have to manage and secure these networks effectively. A network protocol analyzer is an essential component of network security and management that every administrator needs.

MSPs (Managed Service Providers) have a lot of responsibility on their shoulders. They need to look after the IT infrastructures or networks of their customers to ensure that they’re always up and running. But, what happens when the MSP network itself isn’t performing like it should? Like a business organization, an MSP also faces repercussions due to network downtime. Even a minute of downtime can prevent an MSP from offering the necessary services to its clients.

In the dynamic world of IT, traditional network monitoring approaches are no longer sufficient to manage the complexities of today’s networks—be they wired or wireless. To stay ahead of network events, IT administrators must shift from being reactive to adopting a proactive stance. This transition involves a comprehensive approach to network monitoring that includes forecasting future network requirements with the help of machine learning (ML) technology.