FameFlower Test Results

• Overview
• Test Runs
• Results
  • 1. High level FameFlower results data
  • 2.  CPU Utilization comparisons
  • 3.  Memory trends
  • 4.  Database CPU trends  
  • 5.  Slow queries
  • 6. Missing indexes
• Summary
  • Issues

Overview

Using the Carrier-io framework for capturing and analyzing performance test results, the following tests for the export instance UUIDs workflows were executed.

The testing was provided with the modules:

Backend:
- mod-inventory-storage-19.1.2
- mod-inventory-14.1.3
- mod-authtoken-2.4.0
- mod-permissions-5.9.0
- okapi-2.38.0
Frontend:
- folio_inventory-2.0.2

Test Runs

• 30-min Runs for export instance UUIDs workflow:

  Test	Virtual Users	Duration	OKAPI log level	Profiled	Ramp up (total time in seconds)	Size of records
  1. FameFlower	1	30 min	INFO	No	5	10K~50K instances
  2. FameFlower	1	30 min	INFO	No	1	50K~100K instances
  3. FameFlower	1	30 min	INFO	Yes	10	10K~50K instances
  4. FameFlower	1	30 min	INFO	Yes	10	50K~100K instances
  5. FameFlower	5	30 min	INFO	No	50	10K~50K instances
  6. FameFlower	5	30 min	INFO	No	10	50K~100K instances
  7. FameFlower	5	30 min	INFO	Yes	50	10K~50K instances
  8. FameFlower	5	30 min	INFO	Yes	50	50K~100K instances

  
  

  Results

  *All numbers are in milliseconds except for those in the Delta % column, which indicates the difference in percentage going from 1 to 5 users, 10K~50K instances

  1. High level FameFlower results data

  1 and 5 users tests runs, 10K~50K instances

  
  

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1 and 5 users tests runs, 50K~100K instances

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• The chart shows the overall high-level API stats obtained by JMeter calling various APIs in the save instance UUIDs worfklow. It breaks down average response times for 1 and 5 users tests per API call. 

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Summary

        See Attached FameFlower Performance Test Runs.xlsx for details 

• FOLIO performs better without being profiled when the tests are running 

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