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  • folio_circulation-2.0.0
  • Item Check-in (folio_checkin-2.0.1)
  • Item Check-out (folio_checkout-3.0.2)

Folio build was deployed with 50+ ECS services distributed randomly across four Environment:

  • 55 back-end modules deployed in 110 ECS services
  • 3 okapi ECS services
  • 8 m5.large  EC2

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  • instances
  •  db.r5.xlarge AWS RDS instance

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  • INFO logging level

High Level Summary

  1. Overall check in, check out time in seconds


    Average (seconds)50th %tile (seconds)75th %tile (seconds)95th %tile  (seconds)

    Check-inCheck-outCheck-inCheck-outCheck-inCheck-outCheck-inCheck-out
    1 user1.0151.2340.961.2771.0711.4091.3221.653
    5 users1.2361.4881.1561.3931.4641.8691.7042.219
    8 users1.5121.7511.4031.8521.7412.0312.022.274
    20 users1.6491.8981.5351.9961.8962.2112.2522.539


  2. Slow APIs taking more than 100 ms to return

    API1 user (75th %tile)5 users (75th %tile)8 users (75th %tile)20 Users (75th %tile)
    POST checkout-by-barcode615 ms905 ms906 ms988 ms

    POST checkin-by-barcode 

    548 ms830 ms1053 ms1137 ms
    Get circulation/loans283 ms346 ms449 ms479 ms
    Get inventory/items217 ms232 ms237 ms281 ms


  3. Excess logging of missing indexes - 64K lines in  45 minutes run. Logging level could be reduced to WARNING or INFO, but at the cost of having less data to work with should there be a need to troubleshoot.


  4. JVM profiling shows JSON de/serialization operations one of the slowest operations.

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Database

Database does not show much CPU usage for 1, 5, 8 and 20 users runs.  At maximum only 25% CPU usage for the high case of 20 users.

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