And to answer one of your questions that I missed...

Achieving 10 gpbs involved consuming across 4 incoming links on the
Napatech device.  On my hardware I used anywhere from 6 to 10 worker
threads for best performance.

I also ensured that all threads and the Napatech device shared the same
NUMA node/domain/id, but I am not sure how important that is.


On Fri, Sep 4, 2015 at 1:58 PM, Alfredo Cardigliano <[email protected]>
wrote:

> Hi Nick
> what is the card model/chipset you are using? What is the traffic rate
> (pps) you need to handle? How many interfaces are you using in the zc
> balancer?
>
> BTW, just a curiosity, you said "I only need to achieve 10 Gbps on a
> single host and then I am going to scale horizontall”, then you said "it
> does not seem capable of handling additional worker threads to scale beyond
> 10-12 Gbps.”, did I miss something?
>
> Alfredo
>
> On 04 Sep 2015, at 19:47, Nick Allen <[email protected]> wrote:
>
> Unless I am misunderstanding you, that is exactly what I am doing.
> Correct me if I am wrong.
>
> I am using the 'pfring_zc_run_balancer' to load balance packets across
> multiple worker threads.  It is the master (aka balancer) thread that is my
> bottleneck.
>
> On Fri, Sep 4, 2015 at 1:50 AM, Luca Deri <[email protected]> wrote:
>
>> Nick,
>> if you want to scale you need to enable RSS (or use the zbalancer) and
>> have a thread per queue.
>>
>> Luca
>>
>> On 03 Sep 2015, at 18:24, Nick Allen <[email protected]> wrote:
>>
>> I have a similar need.  I need to ingest 40+ gpbs into a Hadoop grid.
>> Kafka is acting as my landing zone/front door for the grid.
>>
>> I tried many variations of using tcpdump, Flume, and other concoctions.
>> I ended up building a custom pcap ingest process in C.  The app uses
>> PF_RING ZC to load balance packets across multiple threads.  I then push
>> the packet data into Kafka using librdkafka.  Both the pull from PF_RING
>> and the push to Kafka batch many packets at a time (trading latency for
>> throughput).
>>
>> With the minimal tuning that I have done, it can handle roughly 10-12
>> Gbps.  I only need to achieve 10 Gbps on a single host and then I am going
>> to scale horizontally to manage the aggregate pcap that I need to capture.
>>
>> Right now, the bottleneck is the master thread in PF_RING that dispatches
>> packets off to each worker thread.  That thread pegs a single CPU core (a
>> rather beefy core, I might add).  It does not seem capable of handling
>> additional worker threads to scale beyond 10-12 Gbps.
>>
>> I wish I had access to the source to review and confirm, but that is how
>> it appears with the information that I have.
>>
>>
>>
>>
>>
>>
>>
>>
>>
>> On Thu, Sep 3, 2015 at 11:46 AM, Manny Veloso <[email protected]>
>> wrote:
>>
>>> Also, when you say 1k flows per second is that 1k devices reporting
>>> their flows every second? We’d need a two to three orders of magnitude more
>>> performance.
>>> --
>>> Manny Veloso
>>> Sr. Solutions Engineer
>>> Smartrg.com <http://smartrg.com/>
>>>
>>> From: <[email protected]> on behalf of Luca Deri <
>>> [email protected]>
>>> Reply-To: "[email protected]" <
>>> [email protected]>
>>> Date: Tuesday, September 1, 2015 at 10:52 PM
>>> To: "[email protected]" <[email protected]>
>>> Subject: Re: [Ntop-misc] nprobe and kafka?
>>>
>>> Manny
>>> we have added kafka support on one of our development prototypes so
>>> movign to the official nprobe should not be too difficult. The performance
>>> is similar to the ZMQ or elasticsearch implementation, so considered the
>>> JSON conversion is at least 1k flows/sec
>>>
>>> Luca
>>>
>>> On 01 Sep 2015, at 23:20, Manny Veloso <[email protected]> wrote:
>>>
>>> Hi!
>>>
>>> I’m looking to use nprobe as a bridge into kafka. In the splunk app
>>> nprobe just sends data into splunk. Is that basically the same
>>> configuration as a kafka install?
>>>
>>> Also, what kind of throughput can I expect out of nprobe?
>>> --
>>> Manny Veloso
>>> Sr. Solutions Engineer
>>> Smartrg.com <http://smartrg.com/>
>>> _______________________________________________
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>>>
>>>
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>>
>>
>>
>> --
>> Nick Allen <[email protected]>
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>
>
>
> --
> Nick Allen <[email protected]>
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