Cool down peoples!
http://www.quickmeme.com/meme/35ovcy
Sebastian, don't think Sanne was being rude, he's just blunt and we need his
bluntness :)
Sanne, be nice to Sebastian and get him a beer next time around ;)
Hey, he started it! His email was formatted with HTML !? ;)
But seriously, I didn't mean to be rude or disrespectful; if it comes
across like that I'm sorry. FWIW the answers seemed cool to me too.
Let me actually clarify that I love the attitude of Sebastian to try
the various approaches and get with some measurements to help with
important design decisions. It's good that we spend some time
evaluating the alternatives, and it's equally good that we debate the
trade-offs here.
As warned in my email I'm "nit-picking" on the benchmark methodology,
and probably more than the usual, because I care!
I am highlighting what I believe to be useful advice though: the
absolute metrics of such tests need not be taken as primary
(exclusive?) decision factor. Which doesn't mean that performing such
tests is not useful, they certainly provide a lot to think about.
Yet the interpretation of such results need to not be generalised, and
the interpretation process is more important than the absolute
ballpark figures they provide; for example it's paramount to figure
out which factors of the test could theoretically invert the results.
Using them to identify a binary faster/slow yes/no to proof/disproof a
design decision is a dangerous fallacy .. and I'm not picking on
Sebastian specifically, just reminding about it as we've all been
guilty of it: confirmation bias, etc..
The best advice I've ever had myself in performance analysis is to not
try to figure out which implementation is faster "on my machine", but
to understand why it's producing a specific result, and what is
preventing it to produce an higher figure.
Once you know that, it's very valuable information as it will tell you
either what needs fixing with a benchmark, or what needs to be done to
improve the performance of your implementation ;)
So that's why I personally don't publish figures often, but hey I
still run such tests too and spend a lot of time analysing them, to
eventually share what I figure out in the process...
Thanks,
Sanne
Peace out! :)
--
Galder Zamarreño
Infinispan, Red Hat
> On 31 May 2017, at 09:38, Sebastian Laskawiec <slaskawi(a)redhat.com> wrote:
>
> Hey Sanne,
>
> Comments inlined.
>
> Thanks,
> Sebastian
>
> On Tue, May 30, 2017 at 5:58 PM Sanne Grinovero <sanne(a)infinispan.org> wrote:
> Hi Sebastian,
>
> the "intelligent routing" of Hot Rod being one of - if not the main -
reason to use Hot Rod, I wonder if we shouldn't rather suggest people to stick with
HTTP (REST) in such architectures.
>
> Several people have suggested in the past the need to have an HTTP smart load
balancer which would be able to route the external REST requests to the right node.
Essentially have people use REST over the wider network, up to reaching the Infinispan
cluster where the service endpoint (the load balancer) can convert them to optimised Hot
Rod calls, or just leave them in the same format but routing them with the same
intelligence to the right nodes.
>
> I realise my proposal requires some work on several fronts, at very least we would
need:
> - feature parity Hot Rod / REST so that people can actually use it
> - a REST load balancer
>
> But I think the output of such a direction would be far more reusable, as both these
points are high on the wish list anyway.
>
> Unfortunately I'm not convinced into this idea. Let me elaborate...
>
> It goes without saying that HTTP payload is simply larger and require much more
processing. That alone makes it slower than Hot Rod (I believe Martin could provide you
some numbers on that). The second arguments is that switching/routing inside Kubernetes is
bloody fast (since it's based on iptables) and some cloud vendors optimize it even
further (e.g. Google Andromeda [1][2], I would be surprised if AWS didn't have
anything similar). During the work on this prototype I wrote a simple async binary proxy
[3] and measured GCP load balancer vs my proxy performance. They were twice as fast
[4][5]. You may argue whether I could write a better proxy. Probably I could, but the
bottom line is that another performance hit is inevitable. They are really fast and they
operate on their own infrastructure (load balancers is something that is provided by the
cloud vendor to Kubernetes, not the other way around).
>
> So with all that in mind, are we going to get better results comparing to my proposal
for Hot Rod? I dare to doubt, even with HTTP/2 support (which comes really soon I hope).
The second question is whether this new "REST load balancer" will work better
than a standard load balancer using round robin strategy? Again I dare to doubt, even if
you you're faster at routing request to proper node, you introduce another layer of
latency.
>
> Of course the priority of this is up to Tristan but I definitely wouldn't place
it high on todo list. And before even looking at it I would recommend taking Netty HTTP
Proxy, putting it in the middle between real load balancer and Infinispan app and measure
performance with and without it. Another test could be with 1 and 10 replicas to check the
performance penalty of hitting 100% and 10% requests into proper node.
>
> [1]
https://cloudplatform.googleblog.com/2014/08/containers-vms-kubernetes-an...
> [2]
https://cloudplatform.googleblog.com/2014/04/enter-andromeda-zone-google-...
> [3]
https://github.com/slaskawi/external-ip-proxy/blob/Benchmark_with_proxy/P...
> [4]
https://github.com/slaskawi/external-ip-proxy/blob/master/benchmark/resul...
> [5]
https://github.com/slaskawi/external-ip-proxy/blob/master/benchmark/resul...
>
> Not least having a "REST load balancer" would allow to deploy Infinispan as
an HTTP cache; just honouring the HTTP caching protocols and existing standards would
allow people to use any client to their liking,
>
> Could you please give me an example how this could work? The only way that I know is
to plug a cache into reverse proxy. NGNIX supports pluggable Redis for example [6].
>
> [6]
https://www.nginx.com/resources/wiki/modules/redis/
>
> without us having to maintain Hot Rod clients and support it on many exotic platforms
- we would still have Hot Rod clients but we'd be able to pick a smaller set of
strategical platforms (e.g. Windows doesn't have to be in that list).
>
> As I mentioned before, I really doubts HTTP will be faster then Hot Rod in any
scenario.
>
> Such a load balancer could be written in Java (recent WildFly versions are able to do
this efficiently) or it could be written in another language, all it takes is to integrate
an Hot Rod client - or just the intelligence of it- as an extension into an existing load
balancer of our choice.
>
> As I mentioned before, with custom load balancer you're introducing another layer
of latency. It's not a free ride.
>
> Allow me a bit more nit-picking on your benchmarks ;)
> As you pointed out yourself there are several flaws in your setup: "didn't
tune", "running in a VM", "benchmarked on a mac mini", ...if you
know it's a flawed setup I'd rather not publish figures, especially not suggest to
make decisions based on such results.
>
> Why not? Infinispan is a public project and anyone can benchmark it using JMH and
taking decisions based on figures is always better than on intuition. Even though there
were multiple unknown factors involved in this benchmark (this is why I pointed them out
and asked to take the results with a grain of salt), the test conditions for all scenarios
were the same. For me this is sufficient to give a general recommendation as I did. BTW,
this recommendation fits exactly my expectations (communication inside Kube the fastest,
LB per Pod a bit slower and no advanced routing the slowest). Finally, the recommendation
is based on a POC which by definition means it doesn't fit all scenarios. You should
always measure your system!
>
> So unless you can prove the benchmark results are fundamentally wrong and I have
drawn wrong conclusions (e.g. a simple client is the fastest solution whereas inside
Kubernetes communication is the slowest), please don't use "naaah, that's
wrong" argument. It's rude.
>
> At this level of design need to focus on getting the architecture right; it should be
self-speaking that your proposal of actually using intelligent routing in some way should
be better than not using it.
>
> My benchmark confirmed this. But as always I would be happy to discuss some
alternatives. But before trying to convince me to "REST Router", please prove
that introducing a load balancer (or just a simple async proxy for start) gives similar or
better performance than a simple load balancer with round robin strategy.
>
> Once we'll have an agreement on a sound architecture, then we'll be able to
make the implementation efficient.
>
> Thanks,
> Sanne
>
>
>
>
> On 30 May 2017 at 13:43, Sebastian Laskawiec <slaskawi(a)redhat.com> wrote:
> Hey guys!
>
> Over past few weeks I've been working on accessing Infinispan cluster deployed
inside Kubernetes from the outside world. The POC diagram looks like the following:
>
> <pasted1.png>
>
> As a reminder, the easiest (though not the most effective) way to do it is to expose
a load balancer Service (or a Node Port Service) and access it using a client with basic
intelligence (so that it doesn't try to update server list based on topology
information). As you might expect, this won't give you much performance but at least
you could access the cluster. Another approach is to use TLS/SNI but again, the
performance would be even worse.
>
> During the research I tried to answer this problem and created "External IP
Controller" [1] (and corresponding Pull Request for mapping internal/external
addresses [2]). The main idea is to create a controller deployed inside Kubernetes which
will create (and destroy if not needed) a load balancer per Infinispan Pod. Additionally
the controller exposes mapping between internal and external addresses which allows the
client to properly update server list as well as consistent hash information. A full
working example is located here [3].
>
> The biggest question is whether it's worth it? The short answer is yes. Here are
some benchmark results of performing 10k puts and 10k puts&gets (please take them with
a big grain of salt, I didn't optimize any server settings):
> • Benchmark app deployed inside Kuberenetes and using internal addresses
(baseline):
> • 10k puts: 674.244 ± 16.654
> • 10k puts&gets: 1288.437 ± 136.207
> • Benchamrking app deployed in a VM outside of Kubernetes with basic
intelligence:
> • 10k puts: 1465.567 ± 176.349
> • 10k puts&gets: 2684.984 ± 114.993
> • Benchamrking app deployed in a VM outside of Kubernetes with address mapping
and topology aware hashing:
> • 10k puts: 1052.891 ± 31.218
> • 10k puts&gets: 2465.586 ± 85.034
> Note that benchmarking Infinispan from a VM might be very misleading since it depends
on data center configuration. Benchmarks above definitely contain some delay between
Google Compute Engine VM and a Kubernetes cluster deployed in Google Container Engine. How
big is the delay? Hard to tell. What counts is the difference between client using basic
intelligence and topology aware intelligence. And as you can see it's not that small.
>
> So the bottom line - if you can, deploy your application along with Infinispan
cluster inside Kubernetes. That's the fastest configuration since only iptables are
involved. Otherwise use a load balancer per pod with External IP Controller. If you
don't care about performance, just use basic client intelligence and expose everything
using single load balancer.
>
> Thanks,
> Sebastian
>
> [1]
https://github.com/slaskawi/external-ip-proxy
> [2]
https://github.com/infinispan/infinispan/pull/5164
> [3]
https://github.com/slaskawi/external-ip-proxy/tree/master/benchmark
>
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> --
> SEBASTIAN ŁASKAWIEC
> INFINISPAN DEVELOPER
> Red Hat EMEA
>
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