The document discusses the integration of Ceilometer and Heat within the OpenStack ecosystem, focusing on the alarming feature developed by Eoghan Glynn. It details how Ceilometer collects resource usage data and how the Heat orchestration engine automates deployments through declarative configurations. Future directions include expanding metering coverage and improving alarm functionality for better autoscaling mechanisms.

1. ceilometer
Ceilometer
Heat
Alarming
Alarming
Julien Danjou
jd__@Freenode // @juldanjou
julien@danjou.info
Nick Barcet
nijaba@Freenode // @nijaba
nick@enovance.com
Eoghan Glynn
eglynn@Freenode
eglynn@redhat.com

2. Speakers
● Nick Barcet co-founded the Ceilometer project at the
Folsom summit and led the project through incubation
● Julien Danjou has been a core Ceilometer contributor
from the outset, taking over the PTL reins for Havana
● Eoghan Glynn drove the addition of the Alarming
feature to Ceilometer over the Havana cycle

3. Two seemingly disjoint
projects intersect
● Heat is a template-driven orchestration engine
○ automates complex deployments via declarative
configuration
● Ceilometer is a metering infrastructure
○ collects data measuring resource usage and
performance
● Appear on the surface to have minimal commonality ...

4. Ceilometer Workflow
Collect
Transform
Publish
Store
Aggregate
● Collect from OpenStack components
● Transform metering data if necessary
● Publish meters to any destination (including
Ceilometer itself)
● Store received meters
● Aggregate samples via a REST API

5. Heat Workflow
my_stack.template
{ "AWSTemplateFormat" : "2010-09-09",
"Parameters": { "VolumeSize" : { … } }
"Mappings": {
"Flavor2Arch" : { "tiny": {"Arch" : "64" },
... },
"Resources": {
"MyInstance" : {
"Type" : "AWS::EC2::Instance",
"Properties" : { “Volumes” : […] }
} } },
"Outputs": { "DNS" : { "Value" : { … } } } }

6. Heat Workflow
{ "AWSTemplateFormat" : "2010-0909",
"Parameters": { "VolumeSize" : { …
}}
"Mappings": {
"Flavor2Arch" : { "tiny": {"Arch" : "64"
},
... },
"Resources": {
"MyInstance" : {
"Type" : "AWS::EC2::Instance",
"Properties" : { “Volumes” : […] }
} } },
"Outputs": { "DNS" : { "Value" : { … }
}}}
consumed by
Heat Engine

7. Heat Workflow
{ "AWSTemplateFormat" : "2010-0909",
"Parameters": { "VolumeSize" : { …
}}
"Mappings": {
"Flavor2Arch" : { "tiny": {"Arch" : "64"
},
... },
"Resources": {
"MyInstance" : {
"Type" : "AWS::EC2::Instance",
"Properties" : { “Volumes” : […] }
} } },
"Outputs": { "DNS" : { "Value" : { … }
}}}
consumed by
interacts with
Heat Engine

8. Heat Workflow
{ "AWSTemplateFormat" : "2010-0909",
"Parameters": { "VolumeSize" : { …
}}
"Mappings": {
"Flavor2Arch" : { "tiny": {"Arch" : "64"
},
... },
"Resources": {
"MyInstance" : {
"Type" : "AWS::EC2::Instance",
"Properties" : { “Volumes” : […] }
} } },
"Outputs": { "DNS" : { "Value" : { … }
}}}
consumed by
interacts with
Heat Engine
my_stack
Instance
Volume
spins up

9. Heat Autoscaling v1.0
CW-lite
reports
load
my_stack
push-stats

10. Heat Autoscaling v1.0
Heat Engine
reports
load
scales out
stack
my_stack
Instance
Instance
Instance

11. Heat Autoscaling v1.0
Heat Engine
reports
load
scales out
stack
my_stack
Instance
Instance
Instance
Instance

12. Ceilometer to the rescue!
● compute agent already collects most
relevant stats from outside the instance
● API service exposes aggregation over the
evaluation window
● define new API exposing alarm lifecycle
● provide new service to evaluate alarms
against their defined rules
● additional service driving asynchronous
notifications when alarms fire

13. How it all hangs together
{ "AWSTemplateFormat" : "2010-0909",
"Parameters": { "VolumeSize" : { …
}}
"Mappings": {
"Flavor2Arch" : { "tiny": {"Arch" : "64"
},
... },
"Resources": {
"MyInstance" : {
"Type" : "AWS::EC2::Instance",
"Properties" : { “Volumes” : […] }
} } },
"Outputs": { "DNS" : { "Value" : { … }
}}}
added to template
● alarms bounding busy/idleness of
instances
● membership of autoscale group
represented via user metadata
● alarm actions refer to scale
up/down policies
● action URLs are pre-signed
● policies define adjustment step size
& cooldown period

14. How it all hangs together
"CPUAlarmHigh": {
"Type": "OS::Metering::Alarm",
"Properties": {
"meter_name": "cpu_util", threshold: "75"
"evaluation_periods": "5", "period": "60",
"statistic": "avg", "comparison_operator": "gt",
"description": "Scale-up if CPU > 75% for 300s",
"alarm_actions":[…"ScaleUpPolicy", "AlarmUrl"…],
"matching_metadata": {
"metadata.user_metadata.server_group":
"MyWebServerGroup"
}}}

15. How it all hangs together
Heat Engine
injects user
metadata
my_stack
Instance

16. How it all hangs together
Heat Engine
injects user
metadata
my_stack
Instance
API service
Ceilometer
creates
alarms

17. How it all hangs together
API service
Heat Engine
injects user
metadata
my_stack
Instance
monitors
instances
Compute
Agent
Ceilometer
creates
alarms

18. How it all hangs together
API service
Heat Engine
injects user
metadata
my_stack
Instance
triggers
alarm
monitors
instances
Alarm
evaluator
Compute
Agent
Ceilometer
creates
alarms

19. How it all hangs together
alarming
Heat Engine
Alarms
injects user
metadata
my_stack
Instance
Instance
Instance
scales out
stack
Compute
Ceilometer
API

20. How it all hangs together
alarming
Heat Engine
Alarms
injects user
metadata
my_stack
Instance
Instance
Instance
Instance
Instance
scales out
stack
Compute
Ceilometer
API

21. How it all hangs together
API service
my_stack
Meter store
Instance
provides
alarm rules
queries
stats
reports
samples
Compute
Agent
Alarm
evaluator
Ceilometer
Heat Engine

22. Lessons learned
Keys to successful intra-project interactions:
● buy-in from stakeholders on both sides
● early validation and proof-points
● protect consuming project from churn during
the development cycle
● split deliverables into bite-sized separately
consumable chunks

23. Future directions
● expand metering coverage to also capture:
○ memory utilization %
○ LBaaS statistics
○ network & disk I/O rates
● add combination alarm support to Heat
templates
○ allow thresholds over multiple metrics to be modeled
● exclude low-quality datapoints
○ avoid scaling when only outliers have reported metrics

24. Future directions
● monitor baremetal via IPMI or SNMP
○ autoscale groups of hosts managed as Ironic instances
● constrain alarms for time-of-day or day-of-week
○ e.g. set the bar higher on weekends, lower on weekdays
● decouple autoscaling usage from Heat templates
● authenticate webhook calls with keystone trusts
○ avoid ec2-signer use without keystone EC2 tokens ext

25. Further questions?
● Chat on Freenode:
○ #openstack-metering
○ #heat
● Mail the dev list:
○ openstack-dev@lists.openstack.org
● Harangue us via Launchpad:
○ https://launchpad.net/ceilometer/+filebug