Customers don't do reservations, we handle that. We scale the size of the
server farm based on the aggregate level of usage.

I'm not understanding the relevance of Prometheus here. We're not looking
for a way to collect and display resource usage - we're looking for a way
to measure it in the first place.

For example, let's say that over a 24-hour period, we rendered 50 frames on
a given machine for 5 different customers. However, the amount of CPU
needed to render a given frame can vary greatly even within a single scene,
and there's no reliable way to predict in advance what that will be.

Instead, I'd like to be able to quantify the amount of CPU / Memory / IO
used for each frame job, calculate the proportion for each customer, and
then pro-rate the machine cost based on that.

I know Kubernetes tracks this information as part of cAdvisor. The question
is getting access to it.

On Tue, May 30, 2017 at 12:21 AM, Matthias Rampke <m...@soundcloud.com> wrote:

> How does actual utilization relate to billing, compared to resource
> reservations? Kubernetes schedules by requests (more or less), what should
> a customer be billed who reserves N cores but only uses a small fraction?
> Or a customer who under-reserves but uses spare capacity? You can also
> forbid the latter using limits, should you choose to.
>
> Billing by reservation would be easier than actual usage, since you can
> basically multiply the reservation (whichever dimensions you choose) by the
> run time. You could do this with Prometheus or simply by collecting the
> data for finished containers from the Kubernetes API.
>
> /MR
>
> On Mon, May 29, 2017, 22:28 Ben Kochie <sup...@gmail.com> wrote:
>
>> This could easily be done with Prometheus.  It's also for real-time
>> monitoring, but it it has a good time-series database and query API for
>> getting the kind of data you need.
>>
>> On Mon, May 29, 2017 at 8:50 PM, <viri...@gmail.com> wrote:
>>
>>> Hi folks, relative newcomer here. :) I'm working on using Kubernetes to
>>> create a render farm for my company. One of the things I need to be able to
>>> do is measure machine utilization so that I can bill our customers. I
>>> looked into the heapster docs, but that doesn't seem to be the correct tool
>>> - it seems to be focused on real-time monitoring, whereas what I need to
>>> know is the total resource usage for a job that may last 10 hours or more.
>>> (More accurately, I want to know how much AWS is going to charge us, but I
>>> need to know it on a per-container basis, since multiple containers for
>>> multiple customers may be running on a single node.)
>>>
>>> The approach I've been looking at is to get the docker stats by talking
>>> to the node directly. That is, given a job, query to find the pod metadata,
>>> then talk to the pod to get the docker stats for the container. I haven't
>>> quite gotten this to work yet.
>>>
>>> Is there a better approach?
>>>
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