With this change pre hourly processor which does the
hourly aggregation (second stage) and writes the
final aggregated metrics to metris topic in kafka
now accounts for any early arriving metrics.
This change along with two previous changes
to pre hourly processor that added
1.) configurable late metrics slack time
(https://review.openstack.org/#/c/394497/), and
2.) batch filtering
(https://review.openstack.org/#/c/363100/)
will make sure all late arriving or early
arriving metrics for an hour are aggregated
appropriately.
Also made improvement in MySQL offset to call
delete excess revisions only once.
Change-Id: I919cddf343821fe52ad6a1d4170362311f84c0e4
Changing devstack environment vagrant box and
also rename the devstack VM to 'devstack'
from 'pg-tips'
Also fixing all the tests that were broken when
they were moved from tests/unit to tests/functional
with this review
https://review.openstack.org/#/c/400237/
Update devstack README with a section called
Development workflow for monasca-transform with
steps developers can take to develop and run
tests.
Change-Id: I11678148ba2bcb96eb3e2a522176683dc8bca30a
Add properties to conf file to allow configuration of
SSL for the database connection. Done for both the python
and java connection strings.
Change-Id: I4c3d25c3f8f12eae801a6a818bf4ac7acd93d2dc
Breaking down the aggregation into two stages.
The first stage aggregates raw metrics frequently and is
implemented as a Spark Streaming job which
aggregates metrics at a configurable time interval
(defaults to 10 minutes) and writes the intermediate
aggregated data, or instance usage data
to new "metrics_pre_hourly" kafka topic.
The second stage is implemented
as a batch job using Spark Streaming createRDD
direct stream batch API, which is triggered by the
first stage only when first stage runs at the
top of the hour.
Also enhanced kafka offsets table to keep track
of offsets from two stages along with streaming
batch time, last time version row got updated
and revision number. By default it should keep
last 10 revisions to the offsets for each
application.
Change-Id: Ib2bf7df6b32ca27c89442a23283a89fea802d146
The monasca-transform is a new component in Monasca that
aggregates and transforms metrics.
monasca-transform is a Spark based data driven aggregation
engine which collects, groups and aggregates existing individual
Monasca metrics according to business requirements and publishes
new transformed (derived) metrics to the Monasca Kafka queue.
Since the new transformed metrics are published as any other
metric in Monasca, alarms can be set and triggered on the
transformed metric, just like any other metric.
Co-Authored-By: Flint Calvin <flint.calvin@hp.com>
Co-Authored-By: David Charles Kennedy <david.c.kennedy@hpe.com>
Co-Authored-By: Ashwin Agate <ashwin.agate@hp.com>
Implements: blueprint monasca-transform
Change-Id: I0e67ac7a4c9a5627ddaf698855df086d55a52d26
Witek Bedyk