The newbie cloud architect diary

This initial phase of a small Mobile App project presents motivations and goals for a new application, and  gives directions around tooling selection. The weekly mood As already mentioned some time ago, I sometimes spend my freetime riding a roadbike. And as it belongs to, I feel both the need to have pleasure and to perform. At first I enjoy good weather, beautiful landscapes and spontaneous break-aways with mates. From time to time, I also expect to make or smash the numbers, simply by pushing it to technical and mental limits where applicable. A few months ago I wrote a blog post  about recording rides using a GPS / Running watch, and analysing calculated power data from Strava segment efforts. Now, I feel the need for something to show me how I perform while riding. Since the watch doesn't show more than speed and time like a cheap bike computer, I do need some extra. However, I want to achieve this with parsimony, that is without purchasing a  Cycling power meter ...

Digital mobility comes with GPS navigation and tracking. We'll use Apache Spark for processing and analysing GPX files generated by a running watch. The daily mood Beside riding, I also like running in my free-time. Well, because of my actual life-style and health, a category of time investment that sits somewhere in between  leisure  and duty . As part of my running activities, I recently started with interval training on a 400m tartan track. I run 8x 1000m fast + 600m slow , for a total of about 1 hour workout plus 15 min warm-up and 15 min cool down. This is rather a traditional training method as compared to modern  High-intensity-interval-training  (HIIT), but I actually needed a convenient plan for improving my racing pace, without being too much concerned of potential pain and injury. I am equiped with a second-hand  Garmin Forerunner  watch, probably one of the most popular devices for capturing passable GPS/HR measures at an affordable price range...

Python project working around Strava API rate limitation in order to extract and analyse full segment effort power data from multiple ride activities. The daily mood It's been such a hard week of work and I needed kind of a distractive weekend. First I helped my son build the Lego ISS  (consisting of 864 pieces). Then we had neighbourhood discussions about the recent announcement of a huge construction project which will start next year, take place just in front of our apartment doors, get incredibly noisy and finally reduce our green area into a urban "wasteland".  Beside that I was able to join an outdoor training of my runner club for the first time since three month of pandemic. A good transition to the little Python programming initiative around riding power analytics that I started last week. In my  previous post , we were able to collect Strava segment power data from a single ride, and visualise it. Still there is potential for improvement and I am now looking fo...

Python project that extracts and analyzes a data sample from Strava API. The records are effort power values calculated for given segments of a ride. The daily mood Today is a bank holiday. I didn't work on duty, but I did "kind of" work for fun.  As a roadbike enthusiast I am riding once a week in the summer. I usually record my  activities using a Garmin watch, then track and share them with friends on  Strava  which is the most popular social-media platform (mainly) dedicated to endurance sports. Strava offers a free account and a commercial subscription with additional features. I used to pay for premium for a couple of months but I personally didn't find it worth. The fascination of cycling Cycling is addictive. First, it catches you with outdoor experience, in which you are escaping duty routine, tanking natural oxygen, discovering new places. Second, it treats your body well through carefull and efficient  biomechanics . It is (almost) fre...