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In this workflow, we are checking the performance of the renewal of loan items for the Goldenrod release.

We tested it with 1, 2 virtual users for 30 minutes.  

Backend:

• mod-users-17.1.0
• mod-users-bl-6.0.0
• mod-authtoken-2.5.1
• mod-permissions-5.11.2
• mod-circulation-19.0.9
• mod-circulation-storage-12.0.1
• okapi-3.1.1

Environment:

• 55 back-end modules deployed in 110 ECS services
• 3 okapi ECS services
• 8 m5.large  EC2 instances
• 1  db.r5.xlarge AWS RDS instance
• INFO logging level

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Results

1. Renew all loans by barcode

   Total Users for 30 minutes	Loans	Renew all loans (Average)	POST_/circulation/renew-by-barcode (Average)
   1 user	10	6.52 seconds	585.11 ms
   	50	31.81 seconds	637.48 ms
   	100	1.06 minutes	650.15 ms
   	200	2.09 minutes	673.40 ms
   2 users	10	7.42 seconds	683.76 ms
   	50	32.61 seconds	686.65 ms
   	100	1.10 minutes	705.37 ms
   	200	2.27 minutes	747.04 ms

   
   

   
   

2. Below is the dependency graph generated from Giraffe for single POST_/circulation/renew-by-barcode API. It shows individual calls made by renew-by-barcode to gather prerequisite data from different APIs such as item-storage, location-units, loan-types, request-storage, notice-policy, locations, and mod-authtoken. In all, this call took 990 ms, and 6% of that is consumed by mod-authtoken and the remaining 94% of the time is taken by other APIs to gather prerequisite data.

Database CPU Utilization

The database CPU usage increases gradually for 1, 2  users run. At maximum 9% CPU usage for 1 user. For 2 users, max CPU utilization increases and then stabilizes as the number of loans increases, mostly because RDS Postgresql is caching the most frequent query results. Therefore, CPU utilization is relatively on the lower side.

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Recommended Improvements 

Anchor
recommendedImprovements recommendedImprovements

• The following JIRAs has been created for mod-authtoken optimization:

Appendix

See Attached user_loanRenewals-test-report.xlsx for details