watcher/doc/source/strategies/workload-stabilization.rst

Workload Stabilization Strategy

Synopsis

display name: Workload stabilization

goal: workload_balancing

watcher.decision_engine.strategy.strategies.workload_stabilization.WorkloadStabilization

Requirements

Metrics

The workload_stabilization strategy requires the following metrics:

metric	description
instance_ram_usage	ram memory usage in an instance as float in megabytes
instance_cpu_usage	cpu usage in an instance as float ranging between 0 and 100 representing the total cpu usage as percentage
host_ram_usage	ram memory usage in a compute node as float in megabytes
host_cpu_usage	cpu usage in a compute node as float ranging between 0 and 100 representing the total cpu usage as percentage

Cluster data model

Default Watcher's Compute cluster data model:

watcher.decision_engine.model.collector.nova.NovaClusterDataModelCollector

Actions

Default Watcher's actions:

action	description
migration	watcher.applier.actions.migration.Migrate

Planner

Default Watcher's planner:

watcher.decision_engine.planner.weight.WeightPlanner

Configuration

Strategy parameters are:

parameter	type	default Value	description
metrics	array	["instance_cpu_usage", "instance_ram_usage"]	Metrics used as rates of cluster loads.
thresholds	object	{"instance_cpu_usage": 0.2, "instance_ram_usage": 0.2}	Dict where key is a metric and value is a trigger value. The strategy will only will look for an action plan when the standard deviation for the usage of one of the resources included in the metrics, taken as a normalized usage between 0 and 1 among the hosts is higher than the threshold. The value of a perfectly balanced cluster for the standard deviation would be 0, while in a totally unbalanced one would be 0.5, which should be the maximum value.
weights	object	{"instance_cpu_usage_weight": 1.0, "instance_ram_usage_weight": 1.0}	These weights are used to calculate common standard deviation when optimizing the resources usage. Name of weight contains meter name and _weight suffix. Higher values imply the metric will be prioritized when calculating an optimal resulting cluster distribution.
instance_metrics	object	{"instance_cpu_usage": "host_cpu_usage", "instance_ram_usage": "host_ram_usage"}	This parameter represents the compute node metrics representing compute resource usage for the instances resource indicated in the metrics parameter.
host_choice	string	retry	Method of host’s choice when analyzing destination for instances. There are cycle, retry and fullsearch methods. Cycle will iterate hosts in cycle. Retry will get some hosts random (count defined in retry_count option). Fullsearch will return each host from list.
retry_count	number	1	Count of random returned hosts.
periods	object	{"instance": 720, "node": 600}	Time, in seconds, to get statistical values for resources usage for instance and host metrics. Watcher will use the last period to calculate resource usage.
granularity	number	300	NOT RECOMMENDED TO MODIFY: The time between two measures in an aggregated timeseries of a metric.
aggregation_method	object	{"instance": 'mean', "compute_node": 'mean'}	NOT RECOMMENDED TO MODIFY: Function used to aggregate multiple measures into an aggregated value.

Efficacy Indicator

Global efficacy indicator:

watcher.decision_engine.goal.efficacy.specs.WorkloadBalancing.get_global_efficacy_indicator

Other efficacy indicators of the goal are:

• instance_migrations_count: The number of VM migrations to be performed
• instances_count: The total number of audited instances in strategy
• standard_deviation_after_audit: The value of resulted standard deviation
• standard_deviation_before_audit: The value of original standard deviation

Algorithm

You can find description of overload algorithm and role of standard deviation here: https://specs.openstack.org/openstack/watcher-specs/specs/newton/implemented/sd-strategy.html

How to use it ?

$ openstack optimize audittemplate create \
  at1 workload_balancing --strategy workload_stabilization

$ openstack optimize audit create -a at1 \
  -p thresholds='{"instance_ram_usage": 0.05}' \
  -p metrics='["instance_ram_usage"]'

External Links

None