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When was this? ~70 events per second doesn't sound like much to capture and aggregate. How much of this parsing did you need to perform in real time? Creating

When was this? ~70 events per second doesn't sound like much to capture and aggregate. How much of this parsing did you need to perform in real time? Creating a unique token to pair requests/responses shouldn't add much overhead at all.

DougWebb 13y ago
Development started around 2000, and stabilized around 2008. As far as I know the reporting scripts are still being run every day. During this period we had purchased a 1TB storage rack from EMC for a million dollars, to give you some perspective on the differences between then and now. - No real-time parsing; it's all nightly batch processing after devops rotates the Apache server logs to a storage volume. The logs sit there for a while then get compressed and moved to offline tape archives. - No DB storage of the logs; space was too expensive and the Oracle database we had couldn't have kept up. It was already heavily burdened with a completely separate usage statistics system that fed into user-facing reporting and billing, which had a much higher event rate, about 100x higher, than the http logs. - We had unique tokens, but they identified a particular user session that tied together all of the user's http requests from login to logoff/abandonment, and which also tied into the Oracle-based statistics for that user, that user's organization, and the customer responsible for the user (often multi-organization). My reports had breakdowns for individual user experiences, session-level metrics, and user type/organization/customer/region/etc metrics. - I don't recall how long the analysis took; it was between half an hour to two hours I think. A lot of that time was spent on disk I/O reading the logs. I had optimized the parsing, analysis, and results recording about as much as I could. - This stuff was written in Perl, and ran on Solaris servers from that time era... probably not a lot more powerful than a handful of smartphones today, though they did have lots of cpus. I don't think traffic has grown much since I left the company (we had pretty full market penetration already) so it's likely those servers haven't been upgraded.
- dvanduzer 13y ago
  I suspected it would have to be a system of that era. I think I have a good idea of how businesses (at a high level) have failed to understand Moore's law from 2000-present. I'm curious what those failures of understanding were like from 1985-2000. We all know that technology has been advancing rapidly, but these specific anecdotes of organizations paying a million dollars just for the backing storage of a system that you can essentially get for free from Google now...
  - DougWebb 13y ago
    Yeah, it's pretty amazing how much things have changed. That raw log data was about 250GB/year which is nothing today but when we started collecting it we were paying $1000/GB. Actually, they're probably still paying over $100/GB. The whole datacenter was outsourced to Perot Systems in the mid-2000s, and the storage fees were astronomical. We calculated that Perot must pay a separate tech to stare at each individual hard drive with a replacement in-hand in case any errors were reported. At least, they could afford to do that with what we were paying them for storage.

DougWebb 13y ago

Development started around 2000, and stabilized around 2008. As far as I know the reporting scripts are still being run every day. During this period we had purchased a 1TB storage rack from EMC for a million dollars, to give you some perspective on the differences between then and now. - No real-time parsing; it's all nightly batch processing after devops rotates the Apache server logs to a storage volume. The logs sit there for a while then get compressed and moved to offline tape archives. - No DB storage of the logs; space was too expensive and the Oracle database we had couldn't have kept up. It was already heavily burdened with a completely separate usage statistics system that fed into user-facing reporting and billing, which had a much higher event rate, about 100x higher, than the http logs. - We had unique tokens, but they identified a particular user session that tied together all of the user's http requests from login to logoff/abandonment, and which also tied into the Oracle-based statistics for that user, that user's organization, and the customer responsible for the user (often multi-organization). My reports had breakdowns for individual user experiences, session-level metrics, and user type/organization/customer/region/etc metrics. - I don't recall how long the analysis took; it was between half an hour to two hours I think. A lot of that time was spent on disk I/O reading the logs. I had optimized the parsing, analysis, and results recording about as much as I could. - This stuff was written in Perl, and ran on Solaris servers from that time era... probably not a lot more powerful than a handful of smartphones today, though they did have lots of cpus. I don't think traffic has grown much since I left the company (we had pretty full market penetration already) so it's likely those servers haven't been upgraded.

dvanduzer 13y ago
I suspected it would have to be a system of that era. I think I have a good idea of how businesses (at a high level) have failed to understand Moore's law from 2000-present. I'm curious what those failures of understanding were like from 1985-2000. We all know that technology has been advancing rapidly, but these specific anecdotes of organizations paying a million dollars just for the backing storage of a system that you can essentially get for free from Google now...
- DougWebb 13y ago
  Yeah, it's pretty amazing how much things have changed. That raw log data was about 250GB/year which is nothing today but when we started collecting it we were paying $1000/GB. Actually, they're probably still paying over $100/GB. The whole datacenter was outsourced to Perot Systems in the mid-2000s, and the storage fees were astronomical. We calculated that Perot must pay a separate tech to stare at each individual hard drive with a replacement in-hand in case any errors were reported. At least, they could afford to do that with what we were paying them for storage.