Hawkular Metrics Openshift Containers
by Matt Wringe
I have a new subproject in Hawkular Metrics which sets up creating
components for Openshift/Fabric8
(https://github.com/hawkular/hawkular-metrics/pull/200).
There are 3 main parts
Cassandra: creates a custom seed provider to support
ReplicationControllers in Kubernetes, creates a folder/zip archive which
can be used to generate a Docker image. It may make sense to move the
Cassandra parts out to a separate project.
Hawkular Metrics: creates a folder/zip archive which can be used to
generate a Docker image
Kubernetes: pulls everything together into a single kubernetes
application. Can be used to deploy an application zip into fabric8 (via
drag and drop in the web console or via the maven plugin) or deploy all
the components into Openshift via the kubernetes.json configuration file.
The docker images are not created and deployed to a docker registry as
part of the build, it will just create a folder where you can run the
docker build from. None of the maven docker plugins I looked at seemed
to really work properly, so its still a manual process to do the build
(and push to a registry). Its something which needs to be improved.
The Cassandra service currently only supports adding new nodes to a
cluster and not removing them via the ReplicationController. This is due
to the replication factor being set to be 1 by default (which means when
a node is removed, so is the data it contained).
I believe the docker subproject of hawkular metrics is obsolete and can
be removed
(https://github.com/hawkular/hawkular-metrics/tree/master/docker), but
someone please correct me if I am wrong. It's scripts are referring to
the console which no longer exists as part of the project.
- Matt
1 year, 3 months
Tenant Id - Not Part of URL
by Stefan Negrea
Hello Everybody,
I've been working on a PR for the upcoming Hawkular Metrics release that will remove the tenant id from the end-point URLs. The tenant id will be moved to either a header parameter or a query parameter. The query parameter is in place for cases (such as curl) where setting a header is not possible, difficult, or inconvenient.
Here is an example of the change:
Existing URL:
/{tenantId}/gauge/{metricId}/data
New URL:
/gauge/{metricId}/data
Tenant id set via:
1) header - tenantId
2) query parameter - tenantId
There are two exceptions to this rule, /tenants and /db/{tenantid}/series. The /tenants end-point will be changed into something different in the upcoming releases since it is mostly a management type API that does not belong in the same place with the regular metrics endpoint. And /db/{tenantid}/series end-point is needed in this exact format for compatibility with Influxdb compatible services.
Now, to the merits of this change. The tenant id is volatile, can change any time, and changes to it should be expected; but the rest of the URL is fixed. The second issue is that the tenant id is a security concern. So we were limited in design choices since a security concern was leaking as part of the URL.
So removing the tenant id from the URL will give us permanent & consistent addresses for resources (metrics and metric data points). And we will gain a lot of flexibility on the security side. In the future, users could authenticate with a user/pass combo and the backend would transform that into a tenant id to be used on the request. If the same user later decides to use a tenant id to pass along the request, the URL of the resources would not change. Another expectation is that tenant id is not sufficient, it is typically a combo of id + secret; so we would have resorted to a header or query param for the second piece of information (the secret).
This change will give us the flexibility to adjust the security model (the meaning of tenant ids and ways to validate them) without compromising the URL structure. This will help Hawkular Metrics as it gets integrated into more and more projects and products.
Here are the links to the JIRA and the PR for this change:
https://github.com/hawkular/hawkular-metrics/pull/202
https://issues.jboss.org/browse/HWKMETRICS-68
Thank you,
Stefan Negrea
Software Engineer
1 year, 3 months
New and noteworthy in hawkular-parent 25
by Peter Palaga
Hi *,
hawkular-parent 25 brings the following:
* srcdeps-maven-plugin 0.0.5
* meets the promisses falsely done for 0.0.4:
* less console output
* built without tests
* wildfly-maven-plugin 1.1.0.Alpha4
I have sent PRs to all components repos.
Thanks,
Peter
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1 year, 3 months
Availability metrics: aggregate stats series
by Joel Takvorian
Hello all,
I'm still aiming to add some features to the grafana plugin. I've started
to integrate availabilities, but now I'm facing a problem when it comes to
show aggregated availabilities ; for example think about an OpenShift pod
that is scaled up to several instances.
Since availability is basically "up" or "down" (or, to simplify with the
other states such as "unknown", say it's either "up" or "non-up"), I
propose to add this new feature: availability stats with aggregation. The
call would be parameterized with an aggregation method, which would be
either "all of" or "any of": with "all of" we consider that the aggregated
series is UP when all its parts are UP.
It would require a new endpoint since the AvailabilityHandler currently
only expose stats queries with metric id as query parameter - not suitable
for multiple metrics.
Any objection or remark for this feature?
Joel
9 years, 5 months
[Inventory] Performance of Tinkerpop3 backends
by Lukas Krejci
Hi all,
to move inventory forward, we need to port it to Tinkerpop3 - a new(ish) and
actively maintained version of the Tinkerpop graph API.
Apart from the huge improvement in the API expressiveness and capabilities,
the important thing is that it comes with a variety of backends, 2 of which
are of particular interest to us ATM. The Titan backend (with Titan in version
1.0) and SQL backend (using the sqlg library).
The SQL backend is a much improved (yet still unfinished in terms of
optimizations and some corner case features) version of the toy SQL backend
for Tinkerpop2.
Back in March I ran performance comparisons for SQL/postgres and Titan (0.5.4)
on Tinkerpop2 and concluded that Titan was the best choice then.
After completing a simplistic port of inventory to Tinkerpop3 (not taking
advantage of any new features or opportunities to simplify inventory
codebase), I've run the performance tests again for the 2 new backends - Titan
1.0 and Sqlg (on postgres).
This time the results are not so clear as the last time.
>From the charts [1] you can see that Postgres is actually quite a bit faster
on reads and can better handle concurrent read access while Titan shines in
writes (arguably thanks to Cassandra as its storage).
Of course, I can imagine that the read performance advantage of Postgres would
decrease with the growing amount of data stored (the tests ran with the
inventory size of ~10k entities) but I am quite positive we'd get competitive
read performance from both solutions up to the sizes of inventory we
anticipate (100k-1M entities).
Now the question is whether the insert performance is something we should be
worried about in Postgres too much. IMHO, there should be some room for
improvement in Sqlg and also our move to /sync for agent synchronization would
make this less of a problem (because there would be not that many initial
imports that would create vast amounts of entities).
Nevertheless I currently cannot say who is the "winner" here. Each backend has
its pros and cons:
Titan:
Pros:
- high write throughput
- backed by cassandra
Cons:
- slower reads
- project virtually dead
- complex codebase (self-made fixes unlikely)
Sqlg:
Pros:
- small codebase
- everybody knows SQL
- faster reads
- faster concurrent reads
Cons:
- slow writes
- another backend needed (Postgres)
Therefore my intention here is to go forward with a "proper" port to
Tinkerpop3 with Titan still enabled but focus primarily on Sqlg to see if we
can do anything with the write performance.
IMHO, any choice we make is "workable" as it is even today but we need to
weigh in the productization requirements. For those Sqlg with its small dep
footprint and postgres backend seems preferable to the huge dependency mess of
Titan.
[1] https://dashboards.ly/ua-TtqrpCXcQ3fnjezP5phKhc
--
Lukas Krejci
9 years, 5 months
Hawkular APM version 0.10.0.Final released with Zipkin integration
by Gary Brown
We are pleased to announce the release of version 0.10.0 of the Hawkular APM project.
The release notes can be found here: https://github.com/hawkular/hawkular-apm/releases/tag/0.10.0.Final
The highlights for this release are:
* In addition to the existing aggregated view of service invocations, it is now possible to view the list of trace instances for that (potentially filtered) aggregated view, and then select an individual instance to display the end to end call trace for that instance. (Screenshots available in the release notes).
* Zipkin integration. It is now possible to point applications, instrumented using zipkin compliant libraries, to the Hawkular APM server and have their information processed and visually represented in the UI.
Feedback on the new features would be very welcome!
Regards
Hawkular APM Team
9 years, 6 months
metrics on the bus
by Jay Shaughnessy
Lucas and I were talking over jira [1] which has to do with
metrics/alerting scale. This was discussed a bit on IRC recently as
well. Today, metrics publishes all datapoints to the bus (metrics and
avail go to different topics). The only consumer of that data is
alerting, and it consumes a small fraction of the total data (actually
it consumes none of it OOB at the moment, but that will hopefully change
as Lucas's alerting work comes on line in MIQ).
Although in its purest form this publish-it-all is the essence of bus
publishing, we both feel it's an unnecessary waste of resources, as
metrics can reach very high volume. There are a few approaches to
reducing the publishing/filtering that we're currently doing. The
options we discussed boil down to:
* No Publishing
o Just query metrics for the data needed for alerting (or whatever
other external use we may have for the data)
o This is essentially a polling approach with frequent polling
* Demand Publishing
o The "just tell me what movie you want to see" approach
o Let clients request the metric ids it wants published to the bus
I'm purposefully not going into much detail at this point. I'd rather
we talk out a preferred approach between these two, or something not
presented. But we'd like to move away from the current publish-it-all
approach.
[1] https://issues.jboss.org/browse/HWKALERTS-118.
9 years, 6 months
