re is an issue and there is damage to the rack, the servers in the cluster from the other rack would be able to service the traffic. Power source redundancy: There should be more than one power source for each rack and server. If there is an issue with one power supply, the other one should take over. Server redundancy: Server issues are most common in the network as each server has multiple components in it, such as memory, storage, CPUs, and network interface cards that can become faulty over a certain period. Hence, it is always advisable to spread an application over a cluster spanning multiple servers, preferably in separate racks. Router and switch redundancy: There should at least be two instances of each router/switch SO that, in case of a failure, there is an alternative path along which traffic can flow. NF redundancy: At each site, there should be two instances of the same NF, preferably in different clusters so that a software or hardware issue on one does not cause a service interruption. Similarly, a geo-redundant instance of an NF should be planned SO that it has enough capacity to deal with the failover traffic in addition to the local data center traffic. It is best to avoid a single point of failure at every level of design. Keeping these points in mind, a resilient network can be designed that can deal with single failures seamlessly. Network failures are one of the key reasons for network performance and the network Key Performance Indicators (KPIs) to dip. In the upcoming section, we will delve into network performance analysis. Network performance analysis Once a network has been deployed successfully, the next important step is to measure the performance of the network. Network performance tests can be conducted at many points and in several ways in the network. Let us go over some of the basic network performance tests: Single UE test: A single UE is attached in a cell with no other devices in that cell and tested for maximum throughput. This test will give the maximum throughput that can 