I was wondering how different workplaces track user actions/events from a backend perspective. Popular options include segment, mparticle but they seem to be quite expensive for small/medium level enterprises
Ask HN: How do you manage event tracking at your workplace
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Re: Ask HN: How do you manage event tracking at your workplace
#2Most product analytics companies offer a free startup account for a year, so check on that.
If you just need web server log processing, AWStats is free and pretty good: https://awstats.sourceforge.io/
Re: Ask HN: How do you manage event tracking at your workplace
#3Re: Ask HN: How do you manage event tracking at your workplace
#4[deleted]
Re: Ask HN: How do you manage event tracking at your workplace
#5Is there a good solution for event/usage tracking for intranet apps without access to Internet? Or is the only option to roll out everything by yourself?
Re: Ask HN: How do you manage event tracking at your workplace
#6We use https://snowplowanalytics.com/
How did you set it up? In-house?
Re: Ask HN: How do you manage event tracking at your workplace
#7We're using Snowplow and it's quite great. There's a complicated setup process and you have to declare event schema before starting tracking, but it's quite cost effective if that's your priority.
We have millions of rows coming from unique users in realtime at $600/mo, with Segment this would at least be $5000/mo.
We then use Redash to prepare charts, tables, etc for analysis.
Re: Ask HN: How do you manage event tracking at your workplace
#8Logfiles.
Re: Ask HN: How do you manage event tracking at your workplace
#9Logfiles.
but that doesn't look good on my resume!
Re: Ask HN: How do you manage event tracking at your workplace
#10Google Cloud Function streaming inserts to BigQuery. Then analysis is carried out with the BigQuery UI (ad hoc analyses or scheduled queries for pipelines), DataStudio (visualizations -- we use this infrequently, it's really not great) or Google Colab (statistical analyses, complex visualizations).
The pros are:
* full SQL access to the data via BigQuery
* simple to set up (yes, you have to write custom code; but a basic implementation is on the order of a couple dozen of lines of code)
* we have full ownership of the data across the pipeline (better for user privacy than using another 3rd party)
Prior to this we used Google Analytics, but their paid solution is too expensive for us and their analytics/aggregation API (though quite powerful) samples a subset of the data which was not acceptable for some of our use cases.