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https://issues.apache.org/jira/browse/BEAM-4430?focusedWorklogId=119374&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-119374
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ASF GitHub Bot logged work on BEAM-4430:
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Author: ASF GitHub Bot
Created on: 05/Jul/18 14:12
Start Date: 05/Jul/18 14:12
Worklog Time Spent: 10m
Work Description: szewi commented on issue #465: [BEAM-4430] Improve
Performance Testing Documentation
URL: https://github.com/apache/beam-site/pull/465#issuecomment-402735484
Ok, so I went through this and it looks good to me. One thing that I'm
considering is using local kubernetes clusters for development purposes. Some
users may want to recreate infra on locally available clusters via minikube and
of course, there will be the different port used as minikube uses ports >30000
and we need to override default ports when running pipelines. Simple services
that use a single port (like Postgres 5432)could handle that(we just override
Postgres port 5432 with some 300xx port), but when we run complex multi-port
services like hdfs that simply won't work. What I mean is the most suitable
infra to develop is having GKE on GCP, rather than using minikube or local
kubernetes clusters. For simple datastores minikube is ok, but for complex it's
painful. The advantage of having kubernetes on GCP is also the fact that infra
would be the same as the one created by Jenkins. TLdr; we should suggest using
GKE rather than local kubernetes clusters.
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Issue Time Tracking
-------------------
Worklog Id: (was: 119374)
Time Spent: 2h (was: 1h 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: Lukasz Gajowy
> Assignee: Lukasz Gajowy
> Priority: Critical
> Time Spent: 2h
> 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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