A private cloud provides resources such as compute, storage and networks to customers. These resources could be monitored for resource utilization, application performance, and operational health. The notion is borrowed from a public cloud such as AWS where Amazon CloudWatch is a monitoring service for AWS cloud resources and the applications that run on AWS. It provides system wide visibility and helps us keep the application running which can help customers keep the operations running smoothly.  They can also use this service to set up alerts and notifications that are of interest to them about their resources. 

This kind of resource monitoring is different from Cloud Service monitoring because the former is useful for customers while the latter is useful for the cloud provider. The latter is used mostly for the health of the services which are offered to more than one customer. The former can be customer specific depending on the registrations or resources and subscriptions for events.  

The implementation is also very different between the two. For example, the cloud services often report metrics directly to a metrics database from which health check reports are drawn. Usually the data is often aged and stored in a time series database for cumulative charts. The transformation of data from collection to a time series database for reporting is usually paid by the query requesting the charts. 

CloudWatch on the other hand is an event collection framework. In real time, events can be collected, archived, filtered and used for subsequent analysis. The collection of data again flows into a database from which queries can be meaning fully read and sent out. The events are much like the messages in a message broker except that it is tuned for high performance and cloud scale. The events have several attributes and are often extensible as name value pairs by the event producers who register different types of event formats. The actual collection of each event, its firing and its subsequent handling is all done within the event framework. This kind of framework has to rely on small packet sizes for the events and a robust and fast message broker functionality within the event broker. Handlers can be registered for each type of events or queues on which the events are stored.  

Thus while the former is based on a time series database for metrics, the latter is based on an event collection and handling engine also referred to as an event driven framework. 

#codingexercise

Replace every element with the least greater element to the right. For example, 

Input: [8, 58, 71, 18, 31, 32, 63, 92, 

         43, 3, 91, 93, 25, 80, 28]
Output: [18, 63, 80, 25, 32, 43, 80, 93, 

         80, 25, 93, -1, 28, -1, -1]
void Replace(ref List<int>A)
{
for (int i = 0; i < A.Count; i++)
{
  int min = INT_MAX;
   for (int j = i+1; j < A.Count; j++)
          if (A[j] < min && A[j] > A[i])
              min = A[j];
  if (min == INT_MAX)
               min = -1;
   A[i] = min;
}
}