I am 6 years late to the party. The first edition of The Phoenix Project came out in 2013, and I only got it now.
I don’t remember the last time I picked up a book, and could absolutely not put it down until I was done with it.
If you haven’t yet read The Phoenix Project, I highly recommend you get yourself a copy and start.
In my opinion this is a book that every struggling developeri, IT department, or business leader, should pick up.
I am very aware that I am not the first to say any of these things, but bear with me. I write my findings to make sure I don’t forget them.
The Phoenix Project explores the life of Bill Palmer after a sudden promotion from Director of Midrange Technology Operations to VP of IT Operations.
Coaxed by his CEO into accepting the position, Bill now has to save the company’s failing project, whilst firefighting IT issues to keep the company moving.
Bill faces many issues during his first few days, but reacts accordingly. He sets up a team, tries to understand how he can better manage the reocurring issues,
and tries to reorganise work.
Things get worse before they get better, but with the help of Erik he finds his footing and comes out the other side victorious.
Erik has some lessons for Bill throughout the whole book, which I will try to list, and explore. Keep on reading.
I love working with Python + Pandas, but sometimes working with lots of data or even loading
that data into memory can be a problem.
It can be better to have a database to perform DB operations, like merges and filters, and then
do the final operations in Pandas, when the data is more manageable. For that I use Postgres + Python,
psycopg2 before loading the data into Pandas. Lets get to work!
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I finally tracked down my problem…
When I first started this blog, I found it quite tricky to have Jekyll up and running properly.
I followed the guide in Github and the guide in jekyll’s own website, but kept having problems.
These problems were related to dependencies, the gems ruby uses, and installing them wasn’t an easy task.
When you solve a problem, or get something working, do you ever feel “dirty”? Like the solution you
found wasn’t ideal, and your environment is polluted? Or that strange feeling you get, when something works but you don’t exactly know why?
I absolutely hate that feeling… And I felt that way, until I found Docker.
If you have checked my LinkedIn, you know I am a Data Engineer at Cytora.
Part of my job is to work in our product, the API that serves our AI models to our clients.
Part of a good product is to be able to provide the users with a good experience while they use it,
or develop tools that interact with it. To do so, you need to be able to tell them exaclty what is going wrong.
A simple 400 Bad Request won’t work, you need to be able produce custom error messages and codes.
However, what should be an easy task, isn’t.