ns an orchestration engine, which acts as the brain of this system. Orchestration is most popularly used for the deployment of services, cloud-native functions, and network functions, which can also be virtualized network functions. But it is not limited to the deployment operation. A network orchestrator participates in every aspect of life cycle management. Most network function vendors have their own life cycle management tools. An orchestrator works to integrate all of them to provide a one-stop shop for all life cycle management activities. As the network functions can be deployed on any cloud or on-premises solution, it becomes all the more important to have a simple integrated solution for life cycle management. Imagine a scenario where an MNO has network functions from multiple independent software vendors deployed on multiple clouds. Operating, maintaining, and monitoring such a network would be a gruesome task. Hence, an automated solution such as an orchestrator can manage all the deployments from single point of operation. Similar to monitoring the various clouds and performance of the network function, its logging and collection of KPIs can be done by one pervasive orchestrator and this can, in turn, be consumed by AI/ML algorithms to provide cohesive and correlated trend analysis, which can be treated like a closed loop mechanism to improve network and business intelligence. We will discuss a few unique use cases of network orchestration and the value it can bring to the operator. Auto scale-in and scale-out A 5G network typically has its component network functions deployed over hundreds of servers. Most of this network is built considering a certain capacity in terms of transactions per second and throughput, which correlate to the usage of the server resources such as memory, CPU, and storage. Now, we would need to understand that not all network functions may use all the resources dedicated to them. For example, on a game night, there would be heavy streaming, and hence, high throughput demand. 