I have been trying to get the docs fixed for this for the past 3 months, and
there already is a ticket open for changing the defaults. I don't feel like
I've had a small amount of evidence here. All observation in the 3 years of
work in the field suggests compaction keeps coming up as the bottleneck when
you push Cassandra ingest.0.6 as an initial setting has fixed 20+ broken
clusters in practice and it improved overall performance in every case from
defaults of 0.33 to defaults of 0.03 (yaml suggests per core flush writers, add
in the prevelance of HT and you see a lot of 24+ flush writer systems in the
wild)
No disrespect intended but that default hasn't worked out well at all in my
exposure to it, and 0.6 has never been worse than the default yet. Obviously
write patterns, heap configuration, memtable size limits and what not affect
the exact optimal setting and I've rarely had it end up 0.6 after a tuning
exercise. I never intended that as a blanket recommendation, just a starting
one.
_____________________________
From: Benedict Elliott Smith <bened...@apache.org>
Sent: Friday, August 26, 2016 9:40 AM
Subject: Re: Guidelines for configuring Thresholds for Cassandra metrics
To: <user@cassandra.apache.org>
The default when I wrote it was 0.4 but it was found this did not saturate
flush writers in JBOD configurations. Iirc it now defaults to 1/(1+#disks)
which is not a terrible default, but obviously comes out much lower if you have
many disks.
This smaller value behaves better for peak performance, but in a live system
where compaction is king not saturating flush in return for lower write
amplification (from flushing larger memtables) will indeed often be a win.
0.6, however, is probably not the best default unless you have a lot of tables
being actively written to, in which case even 0.8 would be fine. With a single
main table receiving your writes at a given time, 0.4 is probably an optimal
value, when making this trade off against peak performance.
Anyway, it's probably better to file a ticket to discuss defaults and
documentation than making a statement like this without justification. I can
see where you're coming from, but it's confusing for users to have such blanket
guidance that counters the defaults. If the defaults can be improved (which I
agree they can) it's probably better to do that, along with better
documentation, so the nuance is accounted for.
On Friday, 26 August 2016, Ryan Svihla <r...@foundev.pro> wrote:
Forgot the most important thing. LogsERROR you should investigateWARN you
should have a list of known ones. Use case dependent. Ideally you change
configuration accordingly.*PoolCleaner (slab or native) - good indication node
is tuned badly if you see a ton of this. Set memtable_cleanup_threshold to 0.6
as an initial attempt to configure this correctly. This is a complex topic to
dive into, so that may not be the best number, it'll likely be better than the
default, why its not the default is a big conversation.There are a bunch of
other logs I look for that are escaping me at present but that's a good start
-regards,
Ryan Svihla
On Fri, Aug 26, 2016 at 7:21 AM -0500, "Ryan Svihla" <r...@foundev.pro> wrote:
Thomas,
Not all metrics are KPIs and are only useful when researching a specific issue
or after a use case specific threshold has been set.
The main "canaries" I monitor are:* Pending compactions (dependent on the
compaction strategy chosen but 1000 is a sign of severe issues in all cases)*
dropped mutations (more than one I treat as a event to investigate, I believe
in allowing operational overhead and any evidence of load shedding suggests I
may not have as much as I thought)* blocked anything (flush writers, etc..more
than one I investigate)* system hints ( More than 1k I investigate)* heap usage
and gc time vary a lot by use case and collector chosen, I aim for below 65%
usage as an average with g1, but this again varies by use case a great deal.
Sometimes I just looks the chart and query patterns and if they don't line up I
have to do other deeper investigations* read and write latencies exceeding SLA
is also use case dependent. Those that have none I tend to push towards p99
with a middle end SSD based system having 100ms and a spindle based system
having 600ms with CL one and assuming a "typical" query pattern (again query
patterns and CL so vary here)* cell count and partition size vary greatly by
hardware and gc tuning but I like to in the absence of all other relevant
information like to keep cell count for a partition below 100k and size below
100mb. I however have many successful use cases running more and I've had some
fail well before that. Hardware and tuning tradeoff a shift this around a
lot.There is unfortunately as you'll note a lot of nuance and the load out
really changes what looks right (down to the model of SSDs I have different
expectations for p99s if it's a model I haven't used before I'll do some
comparative testing).
The reason so much of this is general and vague is my selection bias. I'm
brought in when people are complaining about performance or some grand systemic
crash because they were monitoring nothing. I have little ability to change
hardware initially so I have to be willing to allow the hardware to do the best
it can an establish levels where it can no longer keep up with the customers
goals. This may mean for some use cases 10 pending compactions is an actionable
event for them, for another customer 100 is. The better approach is to
establish a baseline for when these metrics start to indicate a serious issue
is occurring in that particular app. Basically when people notice a problem,
what did these numbers look like in the minutes, hours and days prior? That's
the way to establish the levels consistently.
Regards,
Ryan Svihla
On Fri, Aug 26, 2016 at 4:48 AM -0500, "Thomas Julian" <thomasjul...@zoho.com>
wrote:
Hello,
I am working on setting up a monitoring tool to monitor Cassandra Instances.
Are there any wikis which specifies optimum value for each Cassandra KPIs?
For instance, I am not sure,
What value of "Memtable Columns Count" can be considered as "Normal".
What value of the same has to be considered as "Critical".
I knew threshold numbers for few params, for instance any thing more than zero
for timeouts, pending tasks should be considered as unusual. Also, I am aware
that most of the statistics' threshold numbers vary in accordance with Hardware
Specification, Cassandra Environment Setup. But, what I request here is a
general guideline for configuring thresholds for all the metrics.
If this has been already covered, please point me to that resource. If anyone
on their own interest collected these things, please share.
Any help is appreciated.
Best Regards,
Julian.
