Recommendations for the Real time mongodb Analytics

• An OLTP application generates millions of small and random IO requests. To handle these type of IO requests, you must design your application infrastructure to get higher IOPS.
• A data warehousing application generates large and sequential IO requests. To handle these type of IO requests, you must design your application infrastructure to get higher Bandwidth or Throughput
• Disk Caching Enable ReadOnly Cache on premium storage disks with Read heavy operations to get higher Read IOPS.
• Need to remove the refNum from the queries if the tenant doesn't have a multi region and aslo unset the refNum field(Use namespacing tricks for your collections. In other words, create separate collections for recommendations in different refnums, rather than storing a refnum key within each collection document)
• Need to remove the unsed indexes.
• Connections management : the number of connections between the applications and the database can overwhelm the ability of the server to handle requests.Spikes in the number of connections can also be the result of application or driver errors. All of the officially supported MongoDB drivers implement connection pooling, which allows clients to use and reuse connections more efficiently. Extremely high numbers of connections, particularly without corresponding workload is often indicative of a driver or other configuration error.

• db.serverStatus().tcmalloc.tcmalloc.formattedString to get the memory stats
  
  1.refNum remove in queries 
  2.dailyuserjobhistory : unwinding 
  3.unsed indexes