Details
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Task
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Resolution: Fixed
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L3 - Default
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None
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None
Description
Ensure that optimize imports data correctly when the engine is actively producing new data under considerable load.
AT:
- the following scenario is tested:
- start the platform
- start Elasticsearch
- start the Optimize and with that automatically the import
- generate/start 100 000 process instances while the import is running
- compare the results with of the number of activity instances, process instance, process definitions, process definition xmls and variable instances are the same in the engine and in Optimize
- I can read documentation about how to start this test (e.g. in a readme)
- There is a jenkins job running nightly to execute this test.
Hints:
- The qa/import-performance-tests already contain the code to check if the entitiy count in Optimize and the engine are the same. Maybe we can extract the code from there.
- the qa/data-generation module can be used to generate the 100 000 process instances with diagrams and variables.
- in the .ci/jobs you will find the jenkins jobs. Here you can use the performance-large-dataset job as a template since it is already running nightly.
mgm-controller-panel
This is the controller panel for Smart Panels app
Attachments
1.
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Improve import fetch to cope with concurrent engine updates |
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Done | Unassigned |
2.
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Create QA test that verifies the import catches all entities while concurrently generating data from the engine |
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Done | Unassigned |
3.
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Create jenkins pipeline to execute the concurrent data generation import test |
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Done | Unassigned |
4.
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Fix duplicate variables persisted during import |
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Done | Unassigned |