Servers
Adjusting a Server’s Initial Weight
Equalizer uses a server’s initial weight as the starting point for determining the percentage of
requests to route to that server. As Equalizer gathers information about the actual performance of
a server against client requests, it adjusts the server’s current weight so that servers that are
performing well receive a higher percentage of the cluster load than servers that are performing
at a slower rate.
When you install servers, set each server's initial weight value in proportion to its “horsepower.”
All the initial weights in a cluster do not need to add up to any particular number;
it’s the ratio of
the assigned server weight for a server to the total of all the server weights that determines the
amount of traffic sent to a server
.
For example, you might assign a server with 4 dual-core 64-bit processors operating at 3.40GHz a
value of 100 and a server with 2 dual-core 64-bit processors operating at 1.86GHz a value of 50.
The first server will initially receive approximately 66% (100 divided by 150) of the traffic. The
second server will initially get about 33% (50 divided by 150) of the traffic. It’s important to note
that setting the initial weights of these servers to 100 and 50 is equivalent to setting the initial
weights to 180 and 90.
Values for server weights can be in the range 0-200, with 0 meaning that no new requests will be
routed to the server, essentially disabling the server for subsequent requests. In general, you
should use higher initial weights. When the load balancing policy is
not
set to round robin or static
weight, using higher initial weights will produce finer-grained load balancing. Higher weights
enable Equalizer to adjust server weights more gradually; increasing the weight by 1 produces a
smaller change if the starting weight is 100 than it does if the starting weight is 50.
However you set the initial weights, Equalizer will adjust the weight of servers dynamically as
traffic goes through the cluster. Dynamic server weights might vary from 50-150% of the
statically assigned values. To optimize cluster performance, you might need to adjust the initial
weights of the server instance in a server pool based on their performance.
Note
- Equalizer stops dynamically adjusting server weights if the load on the cluster drops below a certain threshold.
For example, if web traffic slows significantly at 4:00 AM PST, Equalizer will not modify server weights until traffic
increases again. Because a server’s performance characteristics can be very different under low and high loads,
Equalizer optimizes only for the high-load case. Keep this in mind when you configure new Equalizer installations; to
test Equalizer’s ALB performance, you’ll need to simulate expected loads.
Setting Initial Weights for Homogenous Clusters
If all the servers in a cluster have the same hardware and software configurations, you should set
their initial weights to the same value initially. We recommend that you use a initial weight of 100
and set the load-balancing response parameter to
medium
.
As with any new configuration, you will need to monitor the performance of the servers under
load for two to three hours. If you observe that the servers differ in the load they can handle,
adjust their initial weights accordingly and again monitor their performance. You should adjust
server weights by small increments; for example, you might set the initial weight of one server to
110 and the other to 90. Fine-tuning server weights to match each server’s actual capability can
easily improve your cluster’s response time by 5 to 10%.
Note
- A change to a server’s initial weight is reflected in cluster performance only after Equalizer has load balanced a
significant number of new client requests for up to 30 minutes against the cluster in which the servers reside. When
testing initial weights, it is most useful to use a load-generating tool to run typical client requests against the cluster to
determine appropriate server initial weights.
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Copyright © 2014 Coyote Point Systems, A Subsidiary of Fortinet, Inc.
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