hawkular monitor agent - inventory
by John Mazzitelli
The Hawkular Monitor Agent (the thing that runs inside of WildFly as a subsystem) can now monitor both its own WildFly instance as well as any remote WildFly instance. It can collect metrics and perform availability checks on any attribute in any subsystem within WildFly and can store that data in Hawkular-Metrics or Hawkular ecosystem. (so if there is any product that runs inside of WildFly, we can now monitor it). I am at a point where I can integrate it into kettle.
I need to now talk to Lukas and gang about the inventory stuff. I have no idea where to start when it comes to integrating with inventory. Lukas - can you setup a call of some sort where you guys can tell me what I have to do and I can ask questions? Hopefully this can help us figure out what we need from inventory from a client perspective.
11 years
metrics explorer UI
by John Mazzitelli
Can someone describe to me what needs to be done to see the Hawkular-Metrics UI (the explorer)? If I store metric and avail data into kettle via the Metrics REST API, I can't use the kettle UI because it is geared to the pinger.
Is there a explorer UI that comes with kettle outside of the main hawkular UI? If not, is there something I have to do to enable that explorer webapp?
11 years
Business app/services representation in Inventory
by Gary Brown
Hi
Before going too far down the BTM road, I just wanted to confirm whether or not we want the business app, their components services, and their relationships to IT resources they use, stored in Hawkular Inventory?
An alternative approach would be to derive the structure and relationships dynamically from the business transaction instance information.
The benefit of storing in Inventory is it enables end users to navigate through the inventory to understand the relationships to the business apps/services, as well as allow other tooling (e.g. impact analysis) to determine the effect of IT resource downtime on business apps.
Thoughts?
Regards
Gary
11 years
RHQ Metrics - 0.2.7 & Hawkular Future
by Stefan Negrea
Hello Everybody,
I want to summarize the latest release of the RHQ Metrics project and the future of the project.
1) RHQ Metrics migrates to Hawkular organization
Release 0.2.7 of the RHQ Metrics is the last one from the current repository. But do not panic! Beyond the mechanics of the transfer and rename, the development will continue with the regular crew.
For the migration, two project repositories (rhq-metrics and rhq-metrics-openshift) will just be transferred to the Hawkular organization. The code from rhqm-charts was already moved to Hawkular, so we will just close the RHQ repository. We will have a follow up communication once all the infrastructure is in place under the new organization.
2) RHQ Metrics 0.2.7 was released today
This release has mainly stability fixes and minor enhancements. The Keycloak integration was delayed and not part of this release (as announced in the planning notes). For more details checkout the Github release notes.
Github Release:
https://github.com/rhq-project/rhq-metrics/releases/tag/0.2.7
JBoss Nexus Maven artifacts:
http://origin-repository.jboss.org/nexus/content/repositories/public/org/...
2) OpenShift Cartridge for RHQ Metrics 0.2.7
The cartridge supports RHQ Metrics 0.2.7, 0.2.6, and 0.2.5. Just a reminder, the cartridge is the simplest and easiest way to get a public facing instance of RHQ Metrics in just a few minutes with a single command. The cartridge configures Cassandra, Wildfly, and RHQ Metrics (REST interface and UI console) to run in a single gear. For more details please visit the Github repository of the project.
Sample command to create a new RHQ Metrics deployment:
rhc app create test_app https://raw.githubusercontent.com/rhq-project/rhq-metrics-openshift/maste...
Github Repository:
https://github.com/rhq-project/rhq-metrics-openshift
A big "Thank you!" goes to John Sanda, Mike Thompson, Heiko Rupp, and Thomas Segismont for their project contributions.
Any discussion, suggestions or contributions are more than welcomed; so feel free to reply to this email or comment directly on the various forum threads.
Thank you,
Stefan Negrea
Software Engineer
_______________________________________________
rhq-devel mailing list
rhq-devel(a)lists.fedorahosted.org
https://lists.fedorahosted.org/mailman/listinfo/rhq-devel
11 years
Stronger typing of metrics
by Michael Burman
Hi,
With our metric definitions, I'd like to see stronger definition of what sort of data we're storing and how it could be processed in the future. And with this I mean the same sort of stuff we had in the RHQ, such as "cumulative / gauge / trendsup / etc", so that we could give better post processing capabilities when fetching the data such as transforming the data between deltas and cumulative (depending on the user needs).
While this could definitely be done with the tags, using such as "units", "type", we don't have any defined names for these options that we could depend on later. I guess this goes to the other tags discussion also, but I assume our tags are designed to work for searching capabilities as well as for definitions?
- Micke
11 years
RfC: Availability
by Heiko W.Rupp
Hey,
there was apparently some watercooler discussion yesterday without any
minutes, so the following
will not be able to refer to it in any way.
Hawkular needs to have a way to store, retrieve and display availability
of a resource or a bunch of them [1].
While we have some short term goals, for the longer run we need to
better identify what needs to be done.
I think we need to separately look at the following concerns:
* availability reporting
* api
*values
* availability computation
* availability storage
* availability retrieval
* alerting on availability
* computed resource state
The basic assumption here is that availability is something relatively
stable. Meaning that usually
the same state (hopefully "UP") is reported each time in a row for a
veeery long period of time (there
are some servers with uptimes >> 1 year).
== reporting
Feeds report availability to Hawkular, where the data may be further
processed and stored.
The reported values are probably in the range of "UP", "DOWN". I can
also imagine that e.g.
an application server that starts shutting down could send a
"GOING_DOWN" value.
On the API side, we need to be able to receive (a list of) tuples
`< resource id, report time, state >`
In case of full Hawkular, the _resource id_ needs to be a valid one from
Inventory.
_Report time_ is the local time on the resource / agent when that state
was retrieved,
represented in ms since the epoch UTC and
then finally the _state_ which would be an Enum of "UP", "DOWN" and
potentially some other
values. While I have described them as string here, the representation
on the wire may be
implemented differently like 1 and 0 or true and false.
== computed availability
In addition to above reporting we may have feeds that either are not
able to deliver availability or
where the availability is delivered as a numeric value - see e.g. the
pinger, where a <rid>.status.code
is delivered as metric value representing the http status codes.
Here we need to be apply a mapping from return code -> availability.
f(code) -> code < 400 ? "UP" : "DOWN"
and then further proceed with that computed availability value.
See also [2] and [3]
=== "Backfill"
As feeds may not report back all the time, we may want to have a
watchdog which adds
a transition into "UNKNOWN" state.
=== Admin-down
A feed may discover resources that report their state as DOWN but where
this is not an issue and rather an
administrative decision. Take a network card as example where the card
as 8 ports, but only 4 of them
are connected. So the other 4 will be reported as DOWN, but in fact they
are DOWN on purpose.
The admin may mark those interfaces as ADMIN_DOWN, which also implies
that further incoming
DOWN-reports (what about UP, UNKNOWN?) reports can be ignored until the
admin re-enables the
interface.
This admin-down probably also needs to be marked in inventory.
=== Maintenance mode
On top of the availability we also have maintenance mode which is
orthogonal to availability and is more meant for alert suppression and
SLA computation. Maintenance mode should not overwrite the recorded or
computed availability.
We still want to record the original state no matter how maintenance
mode is.
== Storage
As I wrote earlier, the base assumption is that availability is supposed
to stay the same for
long periods of time. For that reason run-length encoded storage is
advised
< resource id, state, from , to >
The fields are more or less self-explanatory - to would be "null" if the
current state continues.
This is also sort of what we have done in RHQ, where we have also been
running into some issues,
(especially as we had a very db-bound approach). One issue is that if
you have a transition from UP to DOWN
the DB situation looks like this:
Start:
<rid , UP, from1 , null >
up-> Down at time = from2
find tuple <rid, ??, ??, null > and update to
<rid, UP, from1, from2>
append new tuple
<rid, DOWN, from2, null>
The other issue is to get the current availability (for display in UI
and/or in the previous transition)
find tuple <rid, ??, ??, null>
which are expensive.
The retrieval of the current availability for a resource can be improved
by introducing a cache that stores
as minimal information <rid, last state>.
Another issue that Yak pointed out is that if availability is recorded
infrequently and at random points in time,
just recording when a transition from UP to DOWN or even UNKNOWN
happened may be not enough, as there are scenarios when it is still
important to know when we heard the last UP report.
So above storage (and cache) tuple needs to be extended to contain the
_last heard_ time:
< resource id, state, from , to, last_head >
In this case, as we do not want to update that record for each incoming
availability report, we need to really
cache this information and have either some periodic write back to the
store or at least when a shutdown listener indicates that Hawkular is
going down. In case that we have multiple API endpoints that receive
alert reports , this may need to be a distributed cache.
== Retrieval
Retrieval of availability information may actually a bit more tricky as
returning the current availability state,
as there will be more information to convey:
We have two basic cases
* return current availability / resource state : this can probably be
answered directly from above mentioned cache
* return a timeline between some arbitrary start and end times. Here we
need to go out and return all records
that satisfy something like ( start_time < requested start && end_time >
requested start ) || (start_time > requested start && end_time <=
requested_end )
=== application / group of resources
For applications the situation becomes more complicated as we need to
retrieve the state (records) for each involved resource and then compute
the total state of the application.
Take an app with a load balancer, 3 app servers and a DB then this
computation may go like
avail ( app ) :=
UP if all resources are UP
MIXED if one app server is not UP
DOWN otherwise
Actually this may even contain a time component
avail ( app , time of day ) :=
if (business_hours (time of day) )
UP if all resources are UP
MIXED if one app server is not UP
DOWN otherwise
else
UP if all resources are UP
MIXED if two app servers are not UP
DOWN otherwise
It may be a good idea to not compute that on the fly at retrieval time,
but to add the result as synthetic availability records for the
computation into the normal availability processing stream as indicated
earlier in the "computed availability" section. This way, the computed
information is also available for alerting as input
== Alerting on availability
Alerting will need to see the (computed) availability data and also the
maintenance mode information to be able to
alert on
* is UP/DOWN/... ( for X time )
* goes UP/DOWN/...
With the above I think that alerting should not need to do complex
availability calculations on its own, but rather
work on the stream of incoming (compute
[1] https://issues.jboss.org/browse/HWKMETRICS-35
[2] http://lists.jboss.org/pipermail/hawkular-dev/2015-March/000413.html
[3] http://lists.jboss.org/pipermail/hawkular-dev/2015-March/000402.html
11 years
Jira work log
by John Sanda
I see that there is a work log tab for tickets. Is there a way to set it up so that when commits are pushed, the ticket can automatically be updated? I am pushing commits to my personal repo, and it would be nice for the ticket to indicate this so that it is easy to see where work is being done. I could just add a comment with the info, but I figured it would be worth checking to see if there is an automagic way for the ticket to be updated with that info.
- John
11 years
migration to the new inventory
by Jiri Kremser
Hi,
we've merged all the pull requests so the new inventory is there. There are still some minor issues though. In UI you may see couple of errors, but the pinger seems to be working after all. Everything should be buildable of course.
Hopefully I'll resolve the rest of the issues tomorrow,
jk
11 years
