etwork issues. Over the last 15 years, AT&T has moved much of its operations to the predictive or proactive stance by leveraging many sources of data to identify potential issues before they are visible to the end customers. Work on adaptive operations is underway and one of the fundamental principles of the SDN/NFV transfor- mation is to use data in a virtuous cycle to automate, learn, and adapt. Operations models and processes are dynamic and are influenced by a variety of factors such as new technologies, new network-based services, operating economics, the market landscape, regula- tory policies, and corporate business objectives. Significant changes to modern operations began to take place in the 1970s when engineers realized how computer technology could be applied to net- work operations to make those operations more efficient. Computer-based operations support sys- tems (OSSs) enabled many operational functions to be centralized and performed remotely. As the number of network elements increased by orders of magnitude, the number of operations personnel required to perform planning, administration, and maintenance increased at a much slower rate due to the increasing functionality of operations systems including the ability to correlate related alarms in a fault condition, auto-test to assist in fault isolation, and perform automated actions to clear fault conditions. Figure 15.1 illustrates related statistics over a 3-year period. This figure illustrates that even though the number of network alarms has been growing, in some cases significantly, there has been automation delivered to ensure that ticketable events (events that require human operator engagement) do not scale linearly with the number of alarms. 15.1.1 OPERATIONS AND ENGINEERING TEAMS In a typical large network operator, like AT&T, the operating structure consists of an engineering team that performs fundamental and current network planning and an operations team. The engi- neering team is responsible for introducing new technology into the 