We’ll probably start with some graphs, then bulk up time sampling, time-series 
analysis, and convolutional analysis (for integrating other data streams). 
There are some elegant-ish approaches for generating models of content 
preference that we can play with, too. Here is one that I’ve been interested in 
looking into with our data stream: 
https://pdfs.semanticscholar.org/e7b4/e019df2a07395753b5de173f57d62c690172.pdf 
<https://pdfs.semanticscholar.org/e7b4/e019df2a07395753b5de173f57d62c690172.pdf>

One question I have is whether you’d be willing to gather some data that we can 
use for development purposes. That would be super helpful. 

Eventually, I’d like to publish some data (on dataVerse), which would be 
something like me doing a lit search on Google Scholar for publications related 
to behavioral log analysis… Maybe we can see what our webExtension logs look 
like on eBay or similar.

Is there a public front-end (eBay, Amazon, Netflix, Prime Video, etc., etc.) 
that resembles your use case, Austin?



> On Jan 26, 2020, at 11:58 PM, Austin Bennett <whatwouldausti...@gmail.com> 
> wrote:
> 
> That's what I am hoping to understand -- making full use of the data :-)
> 
> It certainly goes beyond business analytics, funnels, heatmaps.  
> 
> 
> 
> On Sun, Jan 26, 2020, 8:47 PM Joshua Poore <poor...@me.com.invalid> wrote:
> RE Elastic
> 
> Historically, we chose it for two reasons:
> 
> 1. We wanted to discriminate ourselves with very rich data (also verbose). 
> Lucene back-ends made sense in supporting a query language that would allow 
> making full use of that data.
> 
> 2. Kibana is great and greatly reduces the overhead in supporting front-end 
> dashboard. It has a great feel to it, its highly customizable, and a plugin 
> culture is growing.
> 
> At the end of the day, absolutely nothing is stopping anyone from shipping 
> logs to another back-end. I did get a ticket the other day to support a DAL…
> 
> Best,
> 
> Josh
> 
> > On Jan 25, 2020, at 8:58 PM, Austin Bennett <whatwouldausti...@gmail.com 
> > <mailto:whatwouldausti...@gmail.com>> wrote:
> > 
> > Great, thanks, Josh!  (no worries on timing).
> > 
> > A longer term nagging question, that still seems relevant -- Are there
> > any specific reasons that you've anchored on (what seems to only be)
> > Elastic as a backend?  Naively, it seems could view Flagon as a way to
> > produce data, that then could go through a message queue and to one or
> > many different backends depending on desired consumption patterns.  Is
> > this more a matter of convenience - Elastic suffices and therefore
> > devote attention elsewhere -- or because Elastic does something
> > particularly unique given the context of Flagon.
> > 
> > Cheers,
> > Austin
> > 
> > On Sat, Jan 25, 2020 at 5:15 PM Joshua Poore <poor...@apache.org 
> > <mailto:poor...@apache.org>> wrote:
> >> 
> >> Austin—good to hear from you.
> >> 
> >> Apologies for the delay. Have been working with users last few days and 
> >> wanted to give your email the appropriate attention—some good questions.
> >> 
> >> Replies inline
> >> 
> >>> On Jan 22, 2020, at 4:31 PM, Austin Bennett <whatwouldausti...@gmail.com 
> >>> <mailto:whatwouldausti...@gmail.com>> wrote:
> >>> 
> >>> Hi Flagon,
> >>> 
> >>> Looking for info:
> >>> 
> >>> * I don't see much on analysing the data that gets collected.  Very
> >>> interested in understanding the types of insights that people are
> >>> deriving.  Pointers very welcome (esp. to specific use cases).
> >>> Apologies if missing something obvious…
> >> 
> >> Most of our users are interested purely in business analytics. Mostly we 
> >> get requests for guidance on Funnel’s and Heatmaps. We have a crude funnel 
> >> mocked in a Kibana dashboard which you can find in our Business Analytics 
> >> Dashboard here: 
> >> https://github.com/apache/incubator-flagon/tree/master/docker/kibana/6.8.2/Saved%20Objects
> >>  
> >> <https://github.com/apache/incubator-flagon/tree/master/docker/kibana/6.8.2/Saved%20Objects>
> >>  
> >> <https://github.com/apache/incubator-flagon/tree/master/docker/kibana/6.8.2/Saved%20Objects
> >>  
> >> <https://github.com/apache/incubator-flagon/tree/master/docker/kibana/6.8.2/Saved%20Objects>>
> >> 
> >> Of course you’ll need to set up an Elastic instance to use it. You can 
> >> find a sandbox ELK project in the parent directory: 
> >> https://github.com/apache/incubator-flagon/tree/master/docker 
> >> <https://github.com/apache/incubator-flagon/tree/master/docker> 
> >> <https://github.com/apache/incubator-flagon/tree/master/docker 
> >> <https://github.com/apache/incubator-flagon/tree/master/docker>>
> >> 
> >> In the Kibana visualizations and dashboards you’ll find a number of other 
> >> viz elements that derive directly from user asks. You’ll need to customize 
> >> a little bit given you’ll have different values from your logs, but there 
> >> is a LOT of content there.
> >> 
> >> We are working on a python package, too, for more advanced behavioral 
> >> analytics. We haven’t been able to devote much time to it as we’ve been 
> >> working on tightening up UserALE, but we’ve done some WIP experiments with 
> >> an analytic pipeline (seriously, very much a WIP): 
> >> https://github.com/apache/incubator-flagon-distill/tree/distill_toolkit_refactor/WIP-distill_examples
> >>  
> >> <https://github.com/apache/incubator-flagon-distill/tree/distill_toolkit_refactor/WIP-distill_examples>
> >>  
> >> <https://github.com/apache/incubator-flagon-distill/tree/distill_toolkit_refactor/WIP-distill_examples
> >>  
> >> <https://github.com/apache/incubator-flagon-distill/tree/distill_toolkit_refactor/WIP-distill_examples>>
> >>> 
> >>> * Additionally, is JIRA the best place to understand pinpoints and
> >>> areas for improvement?  Esp. upon recognizing value of using the data,
> >>> would be very interested in using my backend/data-eng experience to
> >>> help develop and increase the stability of system for high-scale
> >>> production use (sounds like successfully used places already).
> >> 
> >> For now, yes, JIRA is the best place. We really do keep track of things 
> >> well in JIRA. Most of the tickets in there are backlog ideas, wishes, 
> >> task. We pull from the backlog into releases and track that way. In the 
> >> very near term, we’ll be ditching JIRA and moving to Git Projects. JIRA 
> >> seems to be a wall for our users. For now, feel free to jump in and add 
> >> tickets labeled by component:
> >> 
> >> For UserALE and log pipeline add tickets to: 
> >> https://issues.apache.org/jira/browse/FLAGON-483?jql=project%20%3D%20FLAGON%20AND%20component%20%3D%20UserALE.js
> >>  
> >> <https://issues.apache.org/jira/browse/FLAGON-483?jql=project%20%3D%20FLAGON%20AND%20component%20%3D%20UserALE.js>
> >>  
> >> <https://issues.apache.org/jira/browse/FLAGON-483?jql=project%20=%20FLAGON%20AND%20component%20=%20UserALE.js
> >>  
> >> <https://issues.apache.org/jira/browse/FLAGON-483?jql=project%20=%20FLAGON%20AND%20component%20=%20UserALE.js>>
> >> 
> >> For Analytical asks, add tickets to: 
> >> https://issues.apache.org/jira/browse/FLAGON-464?jql=project%20%3D%20FLAGON%20AND%20component%20%3D%20Distill
> >>  
> >> <https://issues.apache.org/jira/browse/FLAGON-464?jql=project%20%3D%20FLAGON%20AND%20component%20%3D%20Distill>
> >>  
> >> <https://issues.apache.org/jira/browse/FLAGON-464?jql=project%20=%20FLAGON%20AND%20component%20=%20Distill
> >>  
> >> <https://issues.apache.org/jira/browse/FLAGON-464?jql=project%20=%20FLAGON%20AND%20component%20=%20Distill>>
> >> 
> >> For Stack/back-end (ELK) improvements, add tickets to: 
> >> https://issues.apache.org/jira/browse/FLAGON-466?jql=project%20%3D%20FLAGON%20AND%20component%20%3D%20stack
> >>  
> >> <https://issues.apache.org/jira/browse/FLAGON-466?jql=project%20%3D%20FLAGON%20AND%20component%20%3D%20stack>
> >>  
> >> <https://issues.apache.org/jira/browse/FLAGON-466?jql=project%20=%20FLAGON%20AND%20component%20=%20stack
> >>  
> >> <https://issues.apache.org/jira/browse/FLAGON-466?jql=project%20=%20FLAGON%20AND%20component%20=%20stack>>
> >> 
> >> Every commit we make, traces to a ticket. However, JIRA feels unwieldy for 
> >> a lot of users. Feel free to add to JIRA, I will migrate to GIt Projects, 
> >> when we make our move.
> >>> 
> >>> * Lastly, how would y'all characterize the docs vs state of the code
> >>> (is it believed things are well documented and not much drift -- docs
> >>> tend to lag behind).  The repository is not changing rapidly, so seems
> >>> like would be a slow drift if it has occurred.
> >> 
> >> Lately, we’ve been burning down adoption issues for UserALE.js. We’re 
> >> actually in the final throes of testing and documenting for UserALE.js v 
> >> 2.1.0. This is actually a largish release:
> >> 
> >> 1. Webpack/Module Bundler support
> >> 2. SessionStorage Support
> >> 3. custom auth headers
> >> 4. comprehensive custom log support
> >> 5. other things
> >> 
> >> We’ve been pretty active there: 
> >> https://github.com/apache/incubator-flagon-useralejs/tree/FLAGON-469 
> >> <https://github.com/apache/incubator-flagon-useralejs/tree/FLAGON-469> 
> >> <https://github.com/apache/incubator-flagon-useralejs/tree/FLAGON-469 
> >> <https://github.com/apache/incubator-flagon-useralejs/tree/FLAGON-469>>
> >> 
> >> As per docs, our workflow generally follows a pattern such that all 
> >> READMEs are updated prior to pushing new release candidates. Once 
> >> released, we update docs on the website at the same time that we update 
> >> our website to reflect new release links, etc.
> >> 
> >> Currently, docs on UserALE.js — 
> >> http://flagon.incubator.apache.org/docs/useralejs/ 
> >> <http://flagon.incubator.apache.org/docs/useralejs/> 
> >> <http://flagon.incubator.apache.org/docs/useralejs/ 
> >> <http://flagon.incubator.apache.org/docs/useralejs/>> — and the stack — 
> >> http://flagon.incubator.apache.org/docs/stack/ 
> >> <http://flagon.incubator.apache.org/docs/stack/> 
> >> <http://flagon.incubator.apache.org/docs/stack/ 
> >> <http://flagon.incubator.apache.org/docs/stack/>> — are about up to date, 
> >> or lag by a patch release. The website is generally a good source for 
> >> guides and considerations, but our readmes are pretty solid. We’re always 
> >> willing to field asks for more specific documentation.
> >> 
> >> We would love some help on our back-end. We’re lagging a bit as we’ve not 
> >> yet moved our examples up from ELK 6.8—>7.0. That’s on the near term 
> >> slate, as well as more documentation on clustering and indexing options. 
> >> But, we’d love PRs.
> >> 
> >>> 
> >>> Thanks,
> >>> Austin
> >> 
> >> Thank You, Austin! I hope this is helpful!
> >> 
> 

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