Top shows the CPUs pegged at ~100%. Writes are done by a tool built
in-house which is similar in functionality to other object store
benchmarking tools. As I mentioned, there are 256 parallel object
writes (PUTS), each of 256K bytes.
On Thu, Apr 2, 2015 at 9:21 PM, Yogesh Girikumar wrote:
> Also
Also how are you doing the object writes to benchmark it? Are you using dd?
On 3 April 2015 at 09:50, Yogesh Girikumar wrote:
> What does top say?
>
> On 3 April 2015 at 02:34, Shrinand Javadekar
> wrote:
>
>> Hi,
>>
>> I have a single node Swift instance. It has 16 cpus, 8 disks and 64GB
>> me
What does top say?
On 3 April 2015 at 02:34, Shrinand Javadekar
wrote:
> Hi,
>
> I have a single node Swift instance. It has 16 cpus, 8 disks and 64GB
> memory. As part of testing, I am doing 256 object writes in parallel
> for ~10 mins. Each object is also 256K bytes in size.
>
> While my exper
Hi,
I have a single node Swift instance. It has 16 cpus, 8 disks and 64GB
memory. As part of testing, I am doing 256 object writes in parallel
for ~10 mins. Each object is also 256K bytes in size.
While my experiment is running, I see that the CPU utilization of the
box is always ~100%. I am tryi
> I think I am seeing a latency on the order of 10 seconds between (a)
> the time Neutron returns success from that operation and (b) the
> time when the association is actually functioning. Is this sort of
> latency to be expected? I am using Juno, ML2, OVS, and GRE, if it
matters.
Sorry, I
