Pacemaker decides where to place a resource according to the resource allocation scores on every node. The resource will be allocated to the node where the resource has the highest score.
If the resource allocation scores on all the nodes are equal, by the default placement strategy, Pacemaker will choose a node with the least number of allocated resources for balancing the load. If the number of resources on each node is equal, the first eligible node listed in the CIB will be chosen to run the resource.
Often, in real-world situations, different resources use significantly different proportions of a node’s capacities (memory, I/O, etc.). We cannot balance the load ideally just according to the number of resources allocated to a node. Besides, if resources are placed such that their combined requirements exceed the provided capacity, they may fail to start completely or run with degraded performance.
To take these factors into account, Pacemaker allows you to configure:
To configure the capacity that a node provides or a resource requires, you can use utilization attributes in node and resource objects. You can name utilization attributes according to your preferences and define as many name/value pairs as your configuration needs. However, the attributes’ values must be integers.
Specifying CPU and RAM consumed by several resources
<primitive id="rsc-small" class="ocf" provider="pacemaker" type="Dummy">
<utilization id="rsc-small-utilization">
<nvpair id="rsc-small-utilization-cpu" name="cpu" value="1"/>
<nvpair id="rsc-small-utilization-memory" name="memory" value="1024"/>
</utilization>
</primitive>
<primitive id="rsc-medium" class="ocf" provider="pacemaker" type="Dummy">
<utilization id="rsc-medium-utilization">
<nvpair id="rsc-medium-utilization-cpu" name="cpu" value="2"/>
<nvpair id="rsc-medium-utilization-memory" name="memory" value="2048"/>
</utilization>
</primitive>
<primitive id="rsc-large" class="ocf" provider="pacemaker" type="Dummy">
<utilization id="rsc-large-utilization">
<nvpair id="rsc-large-utilization-cpu" name="cpu" value="3"/>
<nvpair id="rsc-large-utilization-memory" name="memory" value="3072"/>
</utilization>
</primitive>
A node is considered eligible for a resource if it has sufficient free capacity to satisfy the resource’s requirements. The nature of the required or provided capacities is completely irrelevant to Pacemaker – it just makes sure that all capacity requirements of a resource are satisfied before placing a resource to a node.
After you have configured the capacities your nodes provide and the capacities your resources require, you need to set the placement-strategy in the global cluster options, otherwise the capacity configurations have no effect.
Four values are available for the placement-strategy:
default
Utilization values are not taken into account at all. Resources are allocated according to allocation scores. If scores are equal, resources are evenly distributed across nodes.
utilization
Utilization values are taken into account only when deciding whether a node is considered eligible (i.e. whether it has sufficient free capacity to satisfy the resource’s requirements). Load-balancing is still done based on the number of resources allocated to a node.
balanced
Utilization values are taken into account when deciding whether a node is eligible to serve a resource and when load-balancing, so an attempt is made to spread the resources in a way that optimizes resource performance.
minimal
Utilization values are taken into account only when deciding whether a node is eligible to serve a resource. For load-balancing, an attempt is made to concentrate the resources on as few nodes as possible, thereby enabling possible power savings on the remaining nodes.
Set placement-strategy with crm_attribute:
# crm_attribute --name placement-strategy --update balanced
Now Pacemaker will ensure the load from your resources will be distributed evenly throughout the cluster, without the need for convoluted sets of colocation constraints.
- If placement-strategy is default or utilization, the node that has the least number of allocated resources gets consumed first.
- If their numbers of allocated resources are equal, the first eligible node listed in the CIB gets consumed first.
- If placement-strategy is balanced, the node that has the most free capacity gets consumed first.
- If the free capacities of the nodes are equal, the node that has the least number of allocated resources gets consumed first.
- If their numbers of allocated resources are equal, the first eligible node listed in the CIB gets consumed first.
- If placement-strategy is minimal, the first eligible node listed in the CIB gets consumed first.
If only one type of utilization attribute has been defined, free capacity is a simple numeric comparison.
If multiple types of utilization attributes have been defined, then the node that is numerically highest in the the most attribute types has the most free capacity. For example:
The type of problem Pacemaker is dealing with here is known as the knapsack problem [http://en.wikipedia.org/wiki/Knapsack_problem] and falls into the NP-complete [http://en.wikipedia.org/wiki/NP-complete] category of computer science problems – a fancy way of saying “it takes a really long time to solve”.
Clearly in a HA cluster, it’s not acceptable to spend minutes, let alone hours or days, finding an optimal solution while services remain unavailable.
So instead of trying to solve the problem completely, Pacemaker uses a best effort algorithm for determining which node should host a particular service. This means it arrives at a solution much faster than traditional linear programming algorithms, but by doing so at the price of leaving some services stopped.
In the contrived example at the start of this chapter:
Which is not ideal.
There are various approaches to dealing with the limitations of pacemaker’s placement strategy:
Ensure you have sufficient physical capacity.
It might sound obvious, but if the physical capacity of your nodes is (close to) maxed out by the cluster under normal conditions, then failover isn’t going to go well. Even without the utilization feature, you’ll start hitting timeouts and getting secondary failures.
Build some buffer into the capabilities advertised by the nodes.
Advertise slightly more resources than we physically have, on the (usually valid) assumption that a resource will not use 100% of the configured amount of CPU, memory and so forth all the time. This practice is sometimes called overcommit.
Specify resource priorities.
If the cluster is going to sacrifice services, it should be the ones you care about (comparatively) the least. Ensure that resource priorities are properly set so that your most important resources are scheduled first.