Link capacity upgrade threshold
woody at pch.net
Sun Aug 30 13:23:55 CDT 2009
>>> If your 95th percentile utilization is at 80% capacity...
I would suggest that the reason each of you have a different number is
because there's a different best number for each case. Looking for any
single number to fit all cases, rather than understanding the underlying
process, is unlikely to yield good results.
First, different people have different requirements. Some people need
lowest possible cost, some people need lowest cost per volume of bits
delivered, some people need lowest cost per burst capacity, some need
latency, some need low jitter, some want good customer service, some
flexible payment terms, and undoubtedly there are a thousand other
Second, this is a binary digital network. It's never 80% full, it's
60% full, and it's never 40% full. It's always exactly 100% full or
exactly 0% full. If SNMP tells you that you've moved 800 megabits in a
second on a one-gigabit pipe, then, modulo any bad implementations of
SNMP, your pipe was 100% full for eight-tenths of that second. SNMP
not "hide" anything. Applying any percentile function to your data, on
the other hand, does hide data. Specifically, it discards all of your
data except a single point, irreversibly. So if you want to know
anything about your network, you won't be looking at percentiles.
Having your circuit be 100% full is a good thing, presuming you're
for it and the traffic has some value to you. Having it be 100% full as
much of the time as possible is a good thing, because that gives you a
high ratio of value to cost. Dropping packets, on the other hand, is
likely to be a bad thing, both because each packet putatively had value,
and because many dropped packets are likely to be resent, and a resent
packet is one you've paid for twice, and that's precluded the sending of
another new, paid-for packet in that timeframe. The cost of not dropping
packets is not having buffers overflow, and the cost of not having
overflow is either having deep buffers, which means high latency, or
customers with a predictable flow of traffic.
Which brings me to item three. In my experience, the single biggest
contributor to buffer overflow is having in-feeding (or downstream
customer) circuits which are of burst capacity too close to that of the
out-feeding (or upstream transit) circuits. Let's say that your
circuit is a gigabit, you have two inbound circuits that are a gigabit
and run at 100% utilization 10% of the time each, and you have a megabit
of buffer memory allocated to the outbound circuit. 1% of the time,
of the inbound circuits will be at 100% utilization simultaneously.
that's happening, you'll have data flowing in at the rate of two
per second, which will fill the buffer in one twentieth of a second,
persists. And, just like Rosencrantz and Guildenstern flipping coins,
such a run will inevitably persist longer than you'd desire, frequently
enough. On the other hand, if you have twenty inbound circuits of 100
megabits each, which are transmitting at 100% of capacity 10% of the
each, you're looking at exactly the same amount of data, however it
arrives _much more predictably_, since the 2-gigabit inflow would only
occur 0.0000000000000000001% of the time, rather than 1% of the time.
it would also be proportionally unlikely to persist for the longer
of time necessary to overflow the buffer.
Thus Kevin's ESnet customers, who are much more likely to be 10gb or
downstream circuits feeding into his 40gb upstream circuits, are much
likely to overflow buffers, than a consumer Internet provider who's
feeding 1mb circuits into a gigabit circuit, even if the aggregation
of the latter is hundreds of times higher.
So, in summary: Your dropped packet counters are the ones to be
as a measure of goodput, more than your utilization counters. And
size of your aggregation pipes as much bigger than the size of the
aggregate into them as you can afford to.
As always, my apologies to those of you for whom this is unnecessarily
remedial, for using NANOG bandwidth and a portion of your Sunday
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