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https://issues.apache.org/jira/browse/BEAM-4430?focusedWorklogId=112786&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-112786
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ASF GitHub Bot logged work on BEAM-4430:
----------------------------------------
Author: ASF GitHub Bot
Created on: 18/Jun/18 15:49
Start Date: 18/Jun/18 15:49
Worklog Time Spent: 10m
Work Description: chamikaramj commented on a change in pull request #465:
[BEAM-4430] Improve Performance Testing Documentation
URL: https://github.com/apache/beam-site/pull/465#discussion_r196124182
##########
File path: src/documentation/io/testing.md
##########
@@ -147,21 +147,30 @@ However, **PerfKit Benchmarker is not required for
running integration tests**.
Prerequisites:
1. [Install PerfKit
Benchmarker](https://github.com/GoogleCloudPlatform/PerfKitBenchmarker)
-1. Have a running Kubernetes cluster you can connect to locally using kubectl
+1. Have a running Kubernetes cluster you can connect to locally using
kubectl. A cluster hosted on Google Kubernetes Engine might be the best fit as
it is used to run the tests on Beam's Jenkins.
Review comment:
You mean "since Jenkins machines are authenticated to connect to GCP." ?
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Issue Time Tracking
-------------------
Worklog Id: (was: 112786)
Time Spent: 1h (was: 50m)
> Improve Performance Testing Documentation
> -----------------------------------------
>
> Key: BEAM-4430
> URL: https://issues.apache.org/jira/browse/BEAM-4430
> Project: Beam
> Issue Type: Wish
> Components: testing
> Reporter: Łukasz Gajowy
> Assignee: Łukasz Gajowy
> Priority: Critical
> Time Spent: 1h
> Remaining Estimate: 0h
>
> Currently, the only documentation regarding IO Performance Testing can be
> found here:
> [https://beam.apache.org/documentation/io/testing/#i-o-transform-integration-tests].
> This is certainly not enough given that the performance testing framework
> currently allows to run tests:
> - on local or hdfs filesystems
> - on direct or dataflow runners
> - manually using integrationTest task
> - automatically using performanceTest task
> - using pkb.py tool directly (PerfKitBenchmarker)
> - on demand from pending Pull Requests
> - detecting anomalies
> - gathering results in dashboards
> All the above bullets (and maybe others - to be investigated) need more
> explanation in the docs to make the Performance Testing Framework usable by
> the broader community.
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