Alarms¶
Alarms provide user-oriented Monitoring-as-a-Service for resources running on OpenStack. This type of monitoring ensures you can automatically scale in or out a group of instances through the Orchestration service, but you can also use alarms for general-purpose awareness of your cloud resources’ health.
These alarms follow a tri-state model:
- ok
- The rule governing the alarm has been evaluated as
False. - alarm
- The rule governing the alarm have been evaluated as
True. - insufficient data
- There are not enough datapoints available in the evaluation periods to meaningfully determine the alarm state.
Alarm definitions¶
The definition of an alarm provides the rules that govern when a state transition should occur, and the actions to be taken thereon. The nature of these rules depend on the alarm type.
Threshold rule alarms¶
For conventional threshold-oriented alarms, state transitions are governed by:
- A static threshold value with a comparison operator such as greater than or less than.
- A statistic selection to aggregate the data.
- A sliding time window to indicate how far back into the recent past you want to look.
Valid threshold alarms are: gnocchi_resources_threshold_rule,
gnocchi_aggregation_by_metrics_threshold_rule, or
gnocchi_aggregation_by_resources_threshold_rule.
Note
As of Ocata, the threshold alarm is deprecated since Ceilometer’s
native storage API is deprecated.
Composite rule alarms¶
Composite alarms enable users to define an alarm with multiple triggering
conditions, using a combination of and and or relations.
Combination rule alarms¶
Note
Combination alarms are deprecated as of Newton for composite alarms. Combination alarm functionality is removed in Pike.
The Telemetry service also supports the concept of a meta-alarm, which
aggregates over the current state of a set of underlying basic alarms
combined via a logical operator (and or or).
Alarm dimensioning¶
A key associated concept is the notion of dimensioning which defines the set of matching meters that feed into an alarm evaluation. Recall that meters are per-resource-instance, so in the simplest case an alarm might be defined over a particular meter applied to all resources visible to a particular user. More useful however would be the option to explicitly select which specific resources you are interested in alarming on.
At one extreme you might have narrowly dimensioned alarms where this selection would have only a single target (identified by resource ID). At the other extreme, you could have widely dimensioned alarms where this selection identifies many resources over which the statistic is aggregated. For example all instances booted from a particular image or all instances with matching user metadata (the latter is how the Orchestration service identifies autoscaling groups).
Alarm evaluation¶
Alarms are evaluated by the alarm-evaluator service on a periodic
basis, defaulting to once every minute.
Alarm actions¶
Any state transition of individual alarm (to ok, alarm, or
insufficient data) may have one or more actions associated with
it. These actions effectively send a signal to a consumer that the
state transition has occurred, and provide some additional context.
This includes the new and previous states, with some reason data
describing the disposition with respect to the threshold, the number
of datapoints involved and most recent of these. State transitions
are detected by the alarm-evaluator, whereas the
alarm-notifier effects the actual notification action.
Webhooks
These are the de facto notification type used by Telemetry alarming and simply involve an HTTP POST request being sent to an endpoint, with a request body containing a description of the state transition encoded as a JSON fragment.
Log actions
These are a lightweight alternative to webhooks, whereby the state
transition is simply logged by the alarm-notifier, and are
intended primarily for testing purposes.
Workload partitioning¶
The alarm evaluation process uses the same mechanism for workload partitioning as the central and compute agents. The Tooz library provides the coordination within the groups of service instances. For further information about this approach, see the high availability guide.
To use this workload partitioning solution set the
evaluation_service option to default. For more
information, see the alarm section in the
OpenStack Configuration Reference.
Using alarms¶
Alarm creation¶
Threshold based alarm¶
An example of creating a Gnocchi threshold-oriented alarm, based on an upper bound on the CPU utilization for a particular instance:
$ aodh alarm create \
--name cpu_hi \
--type gnocchi_resources_threshold \
--description 'instance running hot' \
--metric cpu_util \
--threshold 70.0 \
--comparison-operator gt \
--aggregation-method mean \
--granularity 600 \
--evaluation-periods 3 \
--alarm-action 'log://' \
--resource-id INSTANCE_ID \
--resource-type instance
This creates an alarm that will fire when the average CPU utilization for an individual instance exceeds 70% for three consecutive 10 minute periods. The notification in this case is simply a log message, though it could alternatively be a webhook URL.
Note
Alarm names must be unique for the alarms associated with an
individual project. Administrator can limit the maximum
resulting actions for three different states, and the
ability for a normal user to create log:// and test://
notifiers is disabled. This prevents unintentional
consumption of disk and memory resources by the
Telemetry service.
The sliding time window over which the alarm is evaluated is 30 minutes in this example. This window is not clamped to wall-clock time boundaries, rather it’s anchored on the current time for each evaluation cycle, and continually creeps forward as each evaluation cycle rolls around (by default, this occurs every minute).
Note
The alarm granularity must match the granularities of the metric configured in Gnocchi.
Otherwise the alarm will tend to flit in and out of the
insufficient data state due to the mismatch between the actual
frequency of datapoints in the metering store and the statistics
queries used to compare against the alarm threshold. If a shorter
alarm period is needed, then the corresponding interval should be
adjusted in the pipeline.yaml file.
Other notable alarm attributes that may be set on creation, or via a subsequent update, include:
- state
- The initial alarm state (defaults to
insufficient data). - description
- A free-text description of the alarm (defaults to a synopsis of the alarm rule).
- enabled
- True if evaluation and actioning is to be enabled for this alarm
(defaults to
True). - repeat-actions
- True if actions should be repeatedly notified while the alarm
remains in the target state (defaults to
False). - ok-action
- An action to invoke when the alarm state transitions to
ok. - insufficient-data-action
- An action to invoke when the alarm state transitions to
insufficient data. - time-constraint
- Used to restrict evaluation of the alarm to certain times of the
day or days of the week (expressed as
cronexpression with an optional timezone).
Composite alarm¶
An example of creating a combination alarm, based on the combined state of two underlying alarms:
$ aodh alarm create \
--name meta \
--type composite \
--composite-rule '{"or": [{"threshold": 0.8, "metric": "cpu_util", \
"type": "gnocchi_resources_threshold", "resource_id": INSTANCE_ID1, \
"resource_type": "instance", "aggregation_method": "last"}, \
{"threshold": 0.8, "metric": "cpu_util", \
"type": "gnocchi_resources_threshold", "resource_id": INSTANCE_ID2, \
"resource_type": "instance", "aggregation_method": "last"}]}' \
--alarm-action 'http://example.org/notify'
This creates an alarm that will fire when either one of two underlying
alarms transition into the alarm state. The notification in this case
is a webhook call. Any number of underlying alarms can be combined in
this way, using either and or or. Additionally, combinations
can contain nested conditions:
Note
Observe the underscore in resource_id & resource_type in
composite rule as opposed to --resource-id &
--resource-type CLI arguments.
$ aodh alarm create \
--name meta \
--type composite \
--composite-rule '{"or": [ALARM_1, {"and": [ALARM_2, ALARM_3]}]}' \
--alarm-action 'http://example.org/notify'
Event based alarm¶
An example of creating a event alarm based on power state of instance:
$ aodh alarm create \
--type event \
--name instance_off \
--description 'Instance powered OFF' \
--event-type "compute.instance.power_off.*" \
--enable True \
--query "traits.instance_id=string::INSTANCE_ID" \
--alarm-action 'log://' \
--ok-action 'log://' \
--insufficient-data-action 'log://'
Valid list of event-type and traits can be found in
event_definitions.yaml file . --query may also contain mix of
traits for example to create alarm when instance is powered on but
went into error state:
$ aodh alarm create \
--type event \
--name instance_on_but_in_err_state \
--description 'Instance powered ON but in error state' \
--event-type "compute.instance.power_on.*" \
--enable True \
--query "traits.instance_id=string::INSTANCE_ID;traits.state=string::error" \
--alarm-action 'log://' \
--ok-action 'log://' \
--insufficient-data-action 'log://'
Sample output of alarm type event:
+---------------------------+---------------------------------------------------------------+
| Field | Value |
+---------------------------+---------------------------------------------------------------+
| alarm_actions | [u'log://'] |
| alarm_id | 15c0da26-524d-40ad-8fba-3e55ee0ddc91 |
| description | Instance powered ON but in error state |
| enabled | True |
| event_type | compute.instance.power_on.* |
| insufficient_data_actions | [u'log://'] |
| name | instance_on_state_err |
| ok_actions | [u'log://'] |
| project_id | 9ee200732f4c4d10a6530bac746f1b6e |
| query | traits.instance_id = bb912729-fa51-443b-bac6-bf4c795f081d AND |
| | traits.state = error |
| repeat_actions | False |
| severity | low |
| state | insufficient data |
| state_timestamp | 2017-07-15T02:28:31.114455 |
| time_constraints | [] |
| timestamp | 2017-07-15T02:28:31.114455 |
| type | event |
| user_id | 89b4e48bcbdb4816add7800502bd5122 |
+---------------------------+---------------------------------------------------------------+
Note
To enable event alarms please refer Configuration
Alarm retrieval¶
You can display all your alarms via (some attributes are omitted for brevity):
$ aodh alarm list
+----------+-----------+--------+-------------------+----------+---------+
| alarm_id | type | name | state | severity | enabled |
+----------+-----------+--------+-------------------+----------+---------+
| ALARM_ID | threshold | cpu_hi | insufficient data | high | True |
+----------+-----------+--------+-------------------+----------+---------+
In this case, the state is reported as insufficient data which
could indicate that:
- meters have not yet been gathered about this instance over the evaluation window into the recent past (for example a brand-new instance)
- or, that the identified instance is not visible to the user/project owning the alarm
- or, simply that an alarm evaluation cycle hasn’t kicked off since the alarm was created (by default, alarms are evaluated once per minute).
Note
The visibility of alarms depends on the role and project associated with the user issuing the query:
- admin users see all alarms, regardless of the owner
- non-admin users see only the alarms associated with their project (as per the normal project segregation in OpenStack)
Alarm update¶
Once the state of the alarm has settled down, we might decide that we set that bar too low with 70%, in which case the threshold (or most any other alarm attribute) can be updated thusly:
$ aodh alarm update ALARM_ID --threshold 75
The change will take effect from the next evaluation cycle, which by default occurs every minute.
Most alarm attributes can be changed in this way, but there is also a convenient short-cut for getting and setting the alarm state:
$ openstack alarm state get ALARM_ID
$ openstack alarm state set --state ok ALARM_ID
Over time the state of the alarm may change often, especially if the threshold is chosen to be close to the trending value of the statistic. You can follow the history of an alarm over its lifecycle via the audit API:
$ aodh alarm-history show ALARM_ID
+-----------+------------------+---------------------------------------------------+----------+
| timestamp | type | detail | event_id |
+-----------+------------------+---------------------------------------------------+----------+
| TIME_3 | rule change | {"rule": {"evaluation_periods": 3, "metric": | EVENT_ID |
| | | "cpu_util", "resource_id": RESOURCE_ID, | |
| | | "aggregation_method": "mean", "granularity":600, | |
| | | "threshold": 75.0, "comparison_operator": "gt" | |
| | | "resource_type": "instance"}} | |
| TIME_2 | state transition | {"transition_reason": "Transition to alarm due 3 | EVENT_ID |
| | | samples outside threshold, most recent: | |
| | | 81.4108514719", "state": "alarm"} | |
| TIME_1 | state transition | {"transition_reason": "Transition to ok due to 1 | EVENT_ID |
| | | samples inside threshold, most recent: | |
| | | 67.952938019089", "state": "ok"} | |
| TIME_0 | creation | {"alarm_actions": ["log://"], "user_id": USER_ID, | EVENT_ID |
| | | "name": "cup_hi", "state": "insufficient data", | |
| | | "timestamp": TIME_0, "description": "instance | |
| | | running hot", "enabled": true, "state_timestamp": | |
| | | TIME_0, "rule": {"evaluation_periods": 3, | |
| | | "metric": "cpu_util", "resource_id": RESOURCE_ID, | |
| | | "aggregation_method": "mean", "granularity": 600, | |
| | | "resource_type": "instance"}, "alarm_id": | |
| | | ALARM_ID, "time_constraints": [], | |
| | | "insufficient_data_actions": [], | |
| | | "repeat_actions": false, "ok_actions": [], | |
| | | "project_id": PROJECT_ID, "type": | |
| | | "gnocchi_resources_threshold", "severity": "low"} | |
+-----------+------------------+---------------------------------------------------+----------+
Alarm deletion¶
An alarm that is no longer required can be disabled so that it is no longer actively evaluated:
$ aodh alarm update --enabled False ALARM_ID
or even deleted permanently (an irreversible step):
$ aodh alarm delete ALARM_ID
Debug alarms¶
A good place to start is to add --debug flag when creating or
updating an alarm. For example:
$ aodh --debug alarm create <OTHER_PARAMS>
Look for the state to transition when event is triggered in
/var/log/aodh/listener.log file. For example, the below logs shows
the transition state of alarm with id
85a2942f-a2ec-4310-baea-d58f9db98654 triggered by event id
abe437a3-b75b-40b4-a3cb-26022a919f5e
2017-07-15 07:03:20.149 2866 INFO aodh.evaluator [-] alarm 85a2942f-a2ec-4310-baea-d58f9db98654 transitioning to alarm because Event <id=abe437a3-b75b-40b4-a3cb-26022a919f5e,event_type=compute.instance.power_off.start> hits the query <query=[{"field": "traits.instance_id", "op": "eq", "type": "string", "value": "bb912729-fa51-443b-bac6-bf4c795f081d"}]>.
The below entry in /var/log/aodh/notifier.log also confirms that
event id abe437a3-b75b-40b4-a3cb-26022a919f5e hits the query
matching instance id bb912729-fa51-443b-bac6-bf4c795f081d
2017-07-15 07:03:24.071 2863 INFO aodh.notifier.log [-] Notifying alarm instance_off 85a2942f-a2ec-4310-baea-d58f9db98654 of low priority from insufficient data to alarm with action log: because Event <id=abe437a3-b75b-40b4-a3cb-26022a919f5e,event_type=compute.instance.power_off.start> hits the query <query=[{"field": "traits.instance_id", "op": "eq", "type": "string", "value": "bb912729-fa51-443b-bac6-bf4c795f081d"}]>
aodh alarm-history as mentioned earlier will also display the
transition:
$ aodh alarm-history show 85a2942f-a2ec-4310-baea-d58f9db98654
+----------------------------+------------------+--------------------------------------------------------------------------------------------------------------------------+--------------------------------------+
| timestamp | type | detail | event_id |
+----------------------------+------------------+--------------------------------------------------------------------------------------------------------------------------+--------------------------------------+
| 2017-07-15T01:33:20.390623 | state transition | {"transition_reason": "Event <id=abe437a3-b75b-40b4-a3cb-26022a919f5e,event_type=compute.instance.power_off.start> hits | c5ca92ae-584b-4da6-a12c-b7a00dd39fef |
| | | the query <query=[{\"field\": \"traits.instance_id\", \"op\": \"eq\", \"type\": \"string\", \"value\": \"bb912729-fa51 | |
| | | -443b-bac6-bf4c795f081d\"}]>.", "state": "alarm"} | |
| 2017-07-15T01:31:14.516188 | creation | {"alarm_actions": ["log://"], "user_id": "89b4e48bcbdb4816add7800502bd5122", "name": "instance_off", "state": | fb31f4c2-e357-44c3-9b6a-bd2aaaa4ae68 |
| | | "insufficient data", "timestamp": "2017-07-15T01:31:14.516188", "description": "event_instance_power_off", "enabled": | |
| | | true, "state_timestamp": "2017-07-15T01:31:14.516188", "rule": {"query": [{"field": "traits.instance_id", "type": | |
| | | "string", "value": "bb912729-fa51-443b-bac6-bf4c795f081d", "op": "eq"}], "event_type": "compute.instance.power_off.*"}, | |
| | | "alarm_id": "85a2942f-a2ec-4310-baea-d58f9db98654", "time_constraints": [], "insufficient_data_actions": ["log://"], | |
| | | "repeat_actions": false, "ok_actions": ["log://"], "project_id": "9ee200732f4c4d10a6530bac746f1b6e", "type": "event", | |
| | | "severity": "low"} | |
+----------------------------+------------------+--------------------------------------------------------------------------------------------------------------------------+--------------------------------------+
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