On 13 Feb 2015, at 13:39, Randall Hauch <rhauch(a)redhat.com>
wrote:
Just posted today: Parse.ly <
http://parse.ly/>’s time series backend is
log-oriented and uses the same technology I discussed earlier. But they have details about
data volumes and how they aggregate/window data. Might be useful.
http://blog.parsely.com/post/1633/mage/ <
http://blog.parsely.com/post/1633/mage/>
> On Feb 13, 2015, at 12:01 PM, Randall Hauch <rhauch(a)redhat.com
<mailto:rhauch@redhat.com>> wrote:
>
> Oh, one more thing:
>
>>> On Feb 13, 2015, at 10:49 AM, Thomas Segismont <tsegismo(a)redhat.com
<mailto:tsegismo@redhat.com>> wrote:
>>> ...
>>> Hawkular metrics comes in two forms:
>>
>>> * a Java library (metrics-core)
>>> * a Java EE web application (built on top of the library)
>>>
>>> metrics-core can be embedded in any sort of JVM application but it
>>> expects to find a Cassandra cluster somewhere.
>
>
> I understand that the collectors will be libraries; you’ll probably eventually want
these in multiple languages. But it sure seems strange to have the Hawkular engine (for
lack of a better term) be a library. Not only is that more complicated to set up, but if
you design it to be embeddable then it will be harder to also make it scale.
>
> It sure seems easier to focus on only installing Hawkular as a separate (potentially
distributed) system that is set up and used. Sure, config it to point to the Cassandra
cluster. But that can be easily wrapped up in a Docker image that people download and
simply start, pointing via ENV variables to a Cassandra instance/cluster (perhaps also
started from a Docker image). Better still is that these Docker images can be wrapped in a
Kubernetes pod (that uses a Cassandra pod) and deployed on OpenShift. Now you have
Hawkular as a service, but still easily installed on a customer’s network.
>
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