chibenwa commented on pull request #255:
URL: https://github.com/apache/james-project/pull/255#issuecomment-736297452
For one of our upcoming deployments, we are performing a load-testing
campaign against a testing infrastructure. This load testing campain aims at
finding the limits of the aforementioned platform.
We successfully succeeded to load James JMAP endpoint to a breakpoint at
5400 users (isolation).
Above that number, evidence suggest that we are CPU bound (requests )
On a Cassandra standpoints, there is a high CPU usage (load of 10) that we
linked to the usage of lightweight transactions / paxos usage, for ACLs [1] [2]
[3] [4]. Detailed analysis is on the references.
Once again, this is a topic I'm arguing for months [5], I need all of your
support to have us take a strong decision here, and enforce it.
Infrastructure:
- 3x Cassandra nodes (8 cores, 32 GB RAM, 200 GB SSD)
- 4x James server (4 cores, 8 GB RAM)
- ElasticSearch servers: not measured.
# Action to conduct
- Perform a test run with ACL paxos turned off.
-> This aims at confirming the deletarious impact of their usage
-> Benoit & René are responsible to deploy and test a modified instance of
James on PRE-PROD, with ACL turned off
-> Benoit will continue lobbying AGAINST the usage of strong consistency
in the community [5], which is overall a Cassandra bad practice and a mis-fit.
-> If conclusive, Benoit will present a data-race proofed ACL
implementation on top of Cassandra leveraging CRDT and eventual consistency.
- Perform a run with more James CPU (4 * 6 cpus?) (René & Benoit)
-> The goal is to see if we are James CPU bound or Cassandra CPU bound
- Vincent should give us a full access, as soon as possible to a metric
system, allowing us to refine our analysis.
- We need access to a log collection Kibana to do a review of errors
encountered
- Some connections were refused. Is there a limit to the connection backlog
here? (Vincent & Andy)
# Runs details
[6] [7] shows a (successfull!) run of JMAP scenario alone on top of James.
[8] [9] shows a run hitting a throughtput limit point (5400 simultaneous
users, 320 req/s) from which the performance highly downgrades. This is the
system breaking point.
# References
[1] https://blog.pythian.com/lightweight-transactions-cassandra/ documents
the CPU / memory / bandwith impact of using LWT.
[dstat-cassandra.txt](https://github.com/apache/james-project/files/5621066/dstat-cassandra.txt)
[2] dstat-cassandra.txt highlights a CPU over-usage on Cassandra node. This
behavior is NOT NORMAL. Read-heavy workload are not supposed to be CPU-bound.
[cassandra-tablestats.txt](https://github.com/apache/james-project/files/5621067/cassandra-tablestats.txt)
[3] cassandra-tablestats.txt shouws table usage. We can notice BY FAR that
our most used table is the system.paxos table.
[compaction-history.txt](https://github.com/apache/james-project/files/5621070/compaction-history.txt)
[4] compaction-history.txt highlights how often we do compact the paxos
system table in comparison to other tables further higlighting this to be a
hot-spot.
[5] Benoit proposition to review lightweight transaction / paxos usage in
James: https://github.com/apache/james-project/pull/255
[6] 4000-stats.png shows good statistics of a run with 4000 users
[7] 4000-latency.png shows latency evolution in regard to the number of
users with 4000 users
[8] 6000-stats.png shows good statistics of a run with 6000 users
[9] 6000-latency.png shows latency evolution in regard to the number of
users with 6000 users. Preformance breackage can be seen at 5400 users.
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