A method for deriving one or more projected sources of an outage in a datacenter, the method comprising: obtaining a set of input data providing various parameters relating to a datacenter and a listing of devices in the data center and applications executing on the devices in the datacenter; detecting an outage of at least one functionality of the datacenter based at least in part on the obtained set of input data; responsive to detecting the outage, processing the set of input data using a model to derive one or more projected sources of the outage, the model incorporating a set of rules specifying correlations between the set of input data and the devices or the applications executing on the devices as the one or more projected sources of the outage, wherein deriving the one or more projected sources of the outage includes: generating, using the set of rules accessible to the model, a predicted level for each parameter included in the set of input data using historical data relating to each parameter; comparing the predicted level for each parameter with an actual level of each parameter included in the set of input data to identify one or more anomalous parameters that include actual levels with a threshold deviation from each corresponding predicted level; and identifying one or more devices and/or an application that corresponds to each of the identified anomalous parameters, wherein each of the identified one or more devices and/or the application is included as the one or more projected sources of the outage; and generating an outage notification message providing the one or more projected sources of the outage based at least in part on processing the set of input data, wherein the set of input data includes a location of each of the devices in the datacenter and a device type of each device in the datacenter, wherein the method further comprises: processing the set of input data to identify a data type and one or more associated devices relating to each portion of the set of input data; assigning, to each portion of the set of input data, a timestamp indicating a time of obtaining each portion of the set of input data; and storing the set of input data in a database by the identified data type and the assigned timestamp. obtaining a set of input data providing various parameters relating to a datacenter and a listing of devices in the data center and applications executing on the devices in the datacenter; detecting an outage of at least one functionality of the datacenter based at least in part on the obtained set of input data; responsive to detecting the outage, processing the set of input data using a model to derive one or more projected sources of the outage, the model incorporating a set of rules specifying correlations between the set of input data and the devices or the applications executing on the devices as the one or more projected sources of the outage, wherein deriving the one or more projected sources of the outage includes: generating, using the set of rules accessible to the model, a predicted level for each parameter included in the set of input data using historical data relating to each parameter; comparing the predicted level for each parameter with an actual level of each parameter included in the set of input data to identify one or more anomalous parameters that include actual levels with a threshold deviation from each corresponding predicted level; and identifying one or more devices and/or an application that corresponds to each of the identified anomalous parameters, wherein each of the identified one or more devices and/or the application is included as the one or more projected sources of the outage; and generating an outage notification message providing the one or more projected sources of the outage based at least in part on processing the set of input data, generating, using the set of rules accessible to the model, a predicted level for each parameter included in the set of input data using historical data relating to each parameter; comparing the predicted level for each parameter with an actual level of each parameter included in the set of input data to identify one or more anomalous parameters that include actual levels with a threshold deviation from each corresponding predicted level; and identifying one or more devices and/or an application that corresponds to each of the identified anomalous parameters, wherein each of the identified one or more devices and/or the application is included as the one or more projected sources of the outage; and generating an outage notification message providing the one or more projected sources of the outage based at least in part on processing the set of input data, wherein the set of input data includes a location of each of the devices in the datacenter and a device type of each device in the datacenter, wherein the method further comprises: processing the set of input data to identify a data type and one or more associated devices relating to each portion of the set of input data; assigning, to each portion of the set of input data, a timestamp indicating a time of obtaining each portion of the set of input data; and storing the set of input data in a database by the identified data type and the assigned timestamp. processing the set of input data to identify a data type and one or more associated devices relating to each portion of the set of input data; assigning, to each portion of the set of input data, a timestamp indicating a time of obtaining each portion of the set of input data; and storing the set of input data in a database by the identified data type and the assigned timestamp.