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  • Round Robin type data store - Basically any kind of storage that is fixed in size, and does semi-automatic data aggregation.  The basic idea is that for a period X you have the full details of whatever data you log.  Then after X has elapsed, the data is aggregated in one, or several ways (average, minimum, maximum).  This aggregate data is then stored for another period Y.  Repeat until the data is  no longer relevant and can be dropped from the store.
  • Data Collection - Since Synapse is on Amazon's Elastic Beanstalk, there is the possibility that data usage must be aggregated from several different Synapse instances.  In addition, certain data (like user activity) is most easily collected from other sources than the services (like the Crowd servers).  Thus some kind of data collection mechanism is needed.
  • Data Interpretation - Since both metrics so far proposed (User and project activity levels) are somewhat expensive to compute (if it's even possible), ideally the front-end GUI will not request that this data be recomputed ever.  Some background process - whether it is hosted in the metrics web server, or run independently - is needed to do any kind of pre-processing to the data before it is entered into the data store.
Proposed Solutions

Amazon Cloudwatch - An attractive system for several reasons:

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  • Length of storage - it's not completely clear whether Cloudwatch does any data aggregation.  However, they are very clear that they only keep the original data around for two weeks.  Since this is far less than the period of time that we would like at least some of our metrics to be stored for if Cloudwatch is used, a supplementary data store may be needed.
  • Data expectations - According to Amazon's promotional materials, they expect Cloudwatch to be used for things like "CPU utilization, latency, and request counts".  The thing about these metrics is that they are all time series, that is, it is natural to want to measure these metrics at consistent intervals, and have the data related across time.  On the other hand,  This is not entirely suited to the way we need to gather the data for User and Project Activity.  While it could still be useful as the data collection tool, that seems like a waste of resources if it's just going to be an auxiliary component to the real data store.
Overall: probably not suitable
Custom EC2 Instance with RDS
  • No storage limitations except cost
  • No data expectations to workaround
  • This EC2 instance would be able to act as both the data collection mechanism and the data store, allowing it to keep it's back end storage mechanism in a consistent state.

Cons:

  • Another custom application/library to build and maintain

Data Requirements

User Activity

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Persistent daily data needed:

  • Current activity status
  • Creation date
  • Last login date
  • Number of total logins
Project Activity

Basically the same source data as for User activity is available (or could be), and the method for calculating it is essentially the same.  So it's essentially the same metric, just for projects, not users.  There may be the additional information on what type of usage it was (data access, data modification, data addition etc.), but otherwise the same.