On 13 Feb 2015, at 13:39, Randall Hauch <rhauch@redhat.com> wrote:

Just posted today: 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/

We had a conversation about the Pasre.ly tweet this morning on #hawkular.




On Feb 13, 2015, at 12:01 PM, Randall Hauch <rhauch@redhat.com> wrote:

Oh, one more thing:

On Feb 13, 2015, at 10:49 AM, Thomas Segismont <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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