At Splunk Live in Zurich this week an interesting discussion erupted about human and machine languages. Before I continue with the story, I want to thank everyone that attended the event. Despite the fact that Raffy Marty is a resident celebrity, this was our first formal customer and partner event in Switzerland. We had more than 50 people attend for several hours to talk about Splunk and data center management challenges. The event was co-hosted by T-Systems.

Thank you Meno Schnapauff for your great presentation on how T-Systems and the Swiss National Railway are using Splunk!

Other attendees included folks from Swisscom, Unicom Consulting, Rothschild Bank, Genossenschaft Migros, LeShop, Netcetera, Cablecom GmbH, TBK-Patent Munich, On Line Video 46, Skyguide, PostFinance and the Univestity of Fribourg. Brian Haynes, Tim Thorpe, Julie Duncan and Hash Basu-Choudhuri from our London office participated too.

Now part of the reason I mention all these names (in addition to thanking folks) is to the point of this post. In the room we had an American (me), several native English speakers from different areas of England, Swiss German speakers from Switzerland and German speakers from Germany. What I noticed is how two people think they speak the same language but can’t always understand each other. It turns out there are a lot of American (some West Coast) colloquialisms I use that my “queens English” counterparts don’t understand. And of course most of the time I try to make a joke the Swiss and Germans just look at me like I’m from outer space even though if you asked them they’d say they speak fluent English. During the event the Swiss Germans had trouble understanding the Germans and the Germans had trouble understanding the Swiss Germans. The folks from the UK who spoke German didn’t understand either the Swiss German or the German German although they all claim to speak German.

What does all this have to do with IT you ask? Well it turns out that mashing up languages and attempting to understand each other even though we don’t speak exactly the same language is one of the biggest problems we have in trying to understand our IT systems as well.

“One of the questions posed at the event was how can I modify my system and application logging to some standard in order to follow what my systems are doing? Do we need a logging standard?”

I have long been telling people that logging standards are a waste of time. IBM’s Common Base Events (CBE) has been around for decades and has very little traction in the real world. Data Center Mark-up Language (DCML) was pushed by Opsware and lots of smart people. It got nowhere. Logs exist. Instrumentation exists. Our IT systems already have tremendous amounts of data. Trying to retrofit that data to some standard is impossible. Attempting to organize a multi-vendor logging standard will never happen. Getting developers to log consistently sounds great but I’ve never seen it done before.

What we need is a mashup of machine languages and logging formats. That’s exactly what IT Search is!

Humans need to stop thinking about how we can format data to make it easier for machines to work with it. There is too much data. The real value is being about to work with massive amounts of data without any human intervention. This is exactly what Google does for the web. Sure you can reformat your HTML to get better search results. But even if you do nothing Google will index your site. You don’t even have to tell Google to do it!

I’m going to start sharing more of our experiences helping people see the connections that already exist in their logging data. While the connections are not always obvious to the naked eye and human linear thinking, machines are great at teasing out non-obvious relationships. This is perhaps the most compelling thing we work on at Splunk and continue to push the bleeding edge of what’s possible.