In my previous blog post I covered how I used InfluxDB and Grafana to do analytics on my podcast backlog reaching the depressing conclusion that I wasn’t in fact making progress on my backlog. Oh my. If you look carefully though you’ll also note that the time series used ranged from the 15th February 2016 to the 22nd September 2016. One might have also noticed that in the graph close ups there were these unusually straight lines which whilst not visible to you were actually gaps in the data where Grafana was connecting the dots. There were actually a couple of these points and they were periods where InfluxDB for what ever reason hadn’t started. The final reason it ends in September was that InfluxDB at the time was refusing to start and until I got around to writing the blog post had been dead. Instead in late November 2016 I decided to try something different: to use MySQL as a time series database instead!

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I have a lot of podcasts in my backlog. Over 2000 podcasts remain behind in my history and I’ve got more than enough audio to go on for years. However the problem I had was that I wasn’t sure if I was making any progress on my podcasts or if I was slowly trending backwards (which I had been for years). Before I started at LinkedIn, my commute to work was generally a 15 minute train ride from downtown San Jose straight up North First Street. With the walking time (~10 minutes to/from stations), that landed me with less than 50 minutes of audio time each day. The problem with that was of course the one podcast I was most behind on, Radio National’s Late Night Live, is 50 minutes long and at the time aired five nights a week (now it’s four nights a week, they dropped the Friday night “classic” show which were episodes from their archive). At the time I think I was delayed to around 2009, maybe even as far back to 2007. But I didn’t have the data to see that. Now with a couple of years of LinkedIn, it felt like I was making progress but show me the data!

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For a few years now I’ve had a Cacti instance set up to monitor my inbox. It started ages ago when I realised I had a massive email backlog (over 9000 emails!) and I wanted to track my progress on getting back on track. To do this I turned to a Cacti install I had set up to monitor an Airport Extreme that was my network gateway.

Here’s what that looks like for my unread email for the last day. You can see that email slowly creeps up overnight and then around 8am I woke up and read the email. This gives you an interesting insight into when you get email and when it gets read. So let’s get this set up!

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