Fix the typos in the ceilometer specs

Scan the ceilometer specs repository. Filter the result and fix
the mistakes.

Change-Id: Idfbc41c3b681aa57cd5153dffc2dae600a58efb9
This commit is contained in:
jizilian 2016-02-10 09:18:37 -05:00
parent a4125ab4f3
commit 132f377e85
27 changed files with 37 additions and 37 deletions

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@ -120,7 +120,7 @@ None, we will continue to store a new resource per sample
Performance/Scalability Impacts
-------------------------------
The read performance should improve as we will not have have a giant Sample
The read performance should improve as we will not have a giant Sample
table anymore but smaller, tailored Resource, Meter, and Sample tables.
The write performance is not expected to degrade noticeably.

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@ -45,7 +45,7 @@ types of changes (detailed below): Adding support for Ceilometer queries in
the `javelin code`_ and adding Ceilometer specific entries to the resource
definitions.
The main check that will be facillitated by javelin2 is ensuring the sanity of
The main check that will be facilitated by javelin2 is ensuring the sanity of
api queries with a time range that spans the entire window of time within which
the Grenade test runs (e.g. -+12 hours from now).

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@ -12,7 +12,7 @@ https://blueprints.launchpad.net/ceilometer/+spec/grenade-upgrade-testing
Integrated projects are required to participate in the `grenade`_ upgrade
testing harness. Ceilometer was integrated before these requirements were
added but the requirements apply retroactively. Therefore ceilometer must be
added but the requirements apply retroactively. Therefore, ceilometer must be
added to the harness.
.. _grenade: https://github.com/openstack-dev/grenade

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@ -164,7 +164,7 @@ References
==========
* `Ironic spec`_
* `Review in progress`_ for sending notifcation from Ironic.
* `Review in progress`_ for sending notification from Ironic.
* `Sample data`_
.. _Ironic spec: https://blueprints.launchpad.net/ironic/+spec/send-data-to-ceilometer

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@ -82,7 +82,7 @@ REST API impact
None
No API method is either added or changed. Nevertheless the new error http
No API method is either added or changed. Nevertheless, the new error http
response code (HTTP 403) will be returned when the alarm quotas are exceeded.
Security impact

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@ -70,7 +70,7 @@ Proposed change
We propose to solve the problem by moving access control from calls to the ACL
to applying a decorator to the API methods. Each publicly accessible API
method would have a decorator pointing to a new RBAC module. The RBAC module
decorator would use rules defined in policy.json to determine accesibility of
decorator would use rules defined in policy.json to determine accessibility of
methods by a caller.
This would allow fine-grained, role-dependent, method-specific access control.
@ -135,7 +135,7 @@ manage.
We believe this risk is mitigated by the ability to ship the basic code with
only the current context_is_admin rule enabled. Such configuration would not
allow additional Keystone roles to grant new priviliges unless the system
allow additional Keystone roles to grant new privileges unless the system
operators explicitly added new rules to the policy file.
Pipeline impact
@ -148,7 +148,7 @@ Other end user impact
This will have no direct impact on on python-ceilometerclient as roles and
their associated rules would be established in keystone and interpreted by
Ceilometer API. Nevertheless the python-ceilometerclient will benefit from the
Ceilometer API. Nevertheless, the python-ceilometerclient will benefit from the
increase security provided by the new policy support. For instance, collector
agent (or any other ceilometer service) can have a special role associated
with it disallowing other services (with admin status) to post data in the

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@ -20,7 +20,7 @@ Problem description
Currently, ceilometer doesn't has the capability to get the meters from ceph
object storage, when the ceph is used as a object storage, instead of swift
object storage, when the ceph is used as an object storage, instead of swift
object storage).

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@ -43,7 +43,7 @@ Alternatives
- We can continue to publish via the pipeline but it is far too verbose and
will not solve all dependency issues.
- Have swift own it's own metrics and have it exist swift package. This is
- Have swift own its own metrics and have it exist swift package. This is
dependent on swift accepting something not completely scoped to swift
internal functionality.
- Drop support of swift middleware meters (ie. we won't test it but it'll just

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@ -260,7 +260,7 @@ to be handled.
Dependencies
============
This work is self contained but may add to the libraries required
This work is self-contained but may add to the libraries required
for testing (e.g. wsgi-intercept).
Testing

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@ -18,7 +18,7 @@ Problem description
Currently, metering and event data coexists on the same database. While
related, there's a logical separation in the metering and event models
where the data in each model has it's own unique data and structure; the
where the data in each model has its own unique data and structure; the
metering model can be best described as a time series while the event model is
closer to an entity attribute model. As the models are different in what they
capture, it makes sense that deployers may choose to use different storage
@ -27,8 +27,8 @@ drivers to store each data set.
Proposed change
===============
Similar to the work done to split alarming into it's own database, this
blueprint is to allow for event related data to be stored in it's own database.
Similar to the work done to split alarming into its own database, this
blueprint is to allow for event related data to be stored in its own database.
Alternatives
------------

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@ -109,7 +109,7 @@ Other deployer impact
---------------------
The ElasticSearch storage driver is to have feature parity with the rest of
the currently available event driver backends. It will add a elasticsearch-py
the currently available event driver backends. It will add an elasticsearch-py
client dependency should the driver be selected.
Developer impact

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@ -38,7 +38,7 @@ Add the method 'inspect_disk_iops' in the Inspector and implement it in the
HyperVInspector. The method will return a DiskIOPSStats object.
The metric value will be fetched from Hyper-V VMs, located in the
Msvm_AggregationMetricValue object (further refered to as metric object)
Msvm_AggregationMetricValue object (further referred to as metric object)
associated with the VMs. The metric object's 'MetricDefinitionId' must be
equal to the 'Id' of Msvm_AggregationMetricDefinition object having the
Caption 'Average Normalized Disk Throughput'.

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@ -40,7 +40,7 @@ configure the kafka publisher plugin in pipeline.yaml file like::
- kafka://<broker_ip>?topic=<topic_name>
This way any application that is trying to consume streaming ceilometer
metrics via Kafka, can directly consume the ceilometer samples. For example
metrics via Kafka, can directly consume the ceilometer samples. For example,
projects like monasca - https://github.com/stackforge/monasca-thresh can consume
the ceilometer metrics that are published by the Ceilometer Kafka publisher.
@ -70,7 +70,7 @@ connections are under implementation. More information can be found in the refer
Pipeline impact
---------------
Provide new options to specify kafka publiser as a ceilometer publisher
Provide new options to specify kafka publisher as a ceilometer publisher
Other end user impact
---------------------

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@ -44,7 +44,7 @@ The Neutron event topic names have the following pattern,
* <resource>.delete.end
For this implementation we will track the end events as those give us the most information
with respect to event payload. Also end events are more informative to track the existance
with respect to event payload. Also end events are more informative to track the existence
of a resource and its usage over time.
Alternatives

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@ -89,7 +89,7 @@ Alternatives include:
to implement what are called "SLA checks" via Rally. These allow a
check job which can fail based on a severe degradation in
performance. These are not being done now to first gain experience
with Rally as well as to comparmentalize work in actionable
with Rally as well as to compartmentalize work in actionable
chunks.
Data model impact

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@ -128,7 +128,7 @@ Developer impact
----------------
This change may increase the amount of asynchrony in some tests.
For example the time between posting a sample and being able to
For example, the time between posting a sample and being able to
retrieve that sample may become more unpredictable. As it is already
unpredictable any tests which rely on immediate retrieval are bad
anyway, so we should fix that.

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@ -47,7 +47,7 @@ alarm history.
However their scale might be completely different, so the expiration
frequency shouldn't be the same.
Therefore we will have separate TTL.
Therefore, we will have separate TTL.
Data model impact

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@ -113,7 +113,7 @@ Performance/Scalability Impacts
-------------------------------
Less sample data. Less equivalent data in Events (because of trait filtering).
Events are a bit more scalable in it's design (maybe not the SQL backend).
Events are a bit more scalable in its design (maybe not the SQL backend).
Other deployer impact
---------------------

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@ -29,7 +29,7 @@ work and making user reports.
Proposed change
===============
Add a implementation of method get_meter_statistics via MongoDB
Add an implementation of method get_meter_statistics via MongoDB
aggregation pipeline framework.
From MongoDB docs:
@ -66,7 +66,7 @@ This option allows to write intermediate staging data to temporary files.
So, primary risks of this approach are a necessity of free space
on disk and a slow performance of disk writing and reading.
Accordingly researches and MongoDB docs, the "$sort" command creates
Accordingly, researches and MongoDB docs, the "$sort" command creates
the most amount of intermediate data for follow stages. So, in practice
this stage prepares data whose size is close to new index size.
In same time, the indexed fields sorting (like timestamp

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@ -4,9 +4,9 @@
http://creativecommons.org/licenses/by/3.0/legalcode
=====================
Pollsters No Tranform
=====================
=======================
Pollsters No Transform
=======================
https://blueprints.launchpad.net/ceilometer/+spec/pollsters-no-transform
@ -30,7 +30,7 @@ Proposed change
One way to resolve this complexity is to not do transformations in the
pollsters. Instead when new samples are polled, format them as notifications
and push them onto the notification bus to be retreived by the notification
and push them onto the notification bus to be retrieved by the notification
agent. The pipeline within that agent will then do any required transformations.
Besides clarifying the focus of the polling agents it is likely this change

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@ -93,7 +93,7 @@ Next steps for HA notification agent:
Pros:
Preferred and Easiest approach
Cons:
It doesnt centralize the pipeline definition and runs the risk of agents
It doesn't centralize the pipeline definition and runs the risk of agents
diverging on their pipeline definitions
This means we're allowing any kind of error levels due to the fact file
@ -134,7 +134,7 @@ Alternatives
3. Use automated deployment tools - Puppet, Chef, Ansible to change pipeline
definitions. While this automates changing pipeline definitions across
multiple agents, it doesnt bring the value-add of on-the-fly updates to the
multiple agents, it doesn't bring the value-add of on-the-fly updates to the
agent, without incurring a restart of the daemons.
Pros:

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@ -118,7 +118,7 @@ Ongoing maintainer:
Work Items
----------
* Seperate eventlet and non-eventlet commands into two different module
* Separate eventlet and non-eventlet commands into two different module
directories, starting with the api module.
* Compare and contrast performance of the API server with and without eventlet
paying specific attention to the impact on accessing the storage layer. Mike

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@ -10,7 +10,7 @@ Spliting Ceilometer alarming
https://blueprints.launchpad.net/ceilometer/+spec/split-ceilometer-alarming
Ceilometer evolved from a a simple meter gathering component to a lot of
Ceilometer evolved from a simple meter gathering component to a lot of
different component doing different things. The storage layer has been
abstracted during Juno and Kilo and is going to be handled by Gnocchi. This
spec proposes that the work continues so that the alarming subsystem of

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@ -143,7 +143,7 @@ Data model impact
-----------------
* The "threshold_rules" will be a dict that can be include multiple threshold
rules and the the key of the dict will be "and" or "or". But this has no
rules and the key of the dict will be "and" or "or". But this has no
effect on data model, because the rules is stored as json in db.
REST API impact

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@ -24,7 +24,7 @@ Proposed change
===============
Add a new notifier publisher and use this publisher in event transformer,
when there is a new transformed event from events pipeline
transformers, convert it to notification, send it back to ceilometer notificaton listener,
transformers, convert it to notification, send it back to ceilometer notification listener,
the notification payload is generated from event traits,
then the sample pipeline will convert and publish it into sample.

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@ -114,7 +114,7 @@ Work Items
In current cycle:
* send a email to do a user survey to get feedbacks about this change
* send an email to do a user survey to get feedbacks about this change
* deprecate mongodb and Hbase storage support and log warning messages if
config mongodb or Hbase as storage driver
* add alarm data migration tool for migrating data from mongodb/Hbase to sql

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@ -65,7 +65,7 @@ There are two upgrade paths to handle -- both require no code change:
against same pipeline sets.
4. The new polling agent can be started alongside the old agent only if
no new pollsters were added. If not, new polling agents must start only
in it's own partitioning group and poll only the new pollsters. After
in its own partitioning group and poll only the new pollsters. After
all old agents are upgraded, the polling agents can be changed to poll
both new pollsters AND the old ones.
5. API service management is handled by WSGI so there is only ever one