So this just happened…

-
 ruc
/via http://www.commitstrip.com/en/2016/05/30/very-very-old-projects/
‘It’s not like the “fun” we had when we swapped out Angular for React, but this pretty much holds for any/all breaking changes.
Turnover in the core-services team leads to swapping out SaltStack for Ansible but only for the new environments, because we’ll deprecate the old environments, right?
We should keep up with django updates, except for that one high revenue client’s environment, because “high revenue” right?
I could go on, but there is always a reason to not update. What’s worse, the reason might actually be a good one 😟

Comments

Post a Comment

Popular posts from this blog

Erlang, Binaries, and Garbage Collection (Sigh)

-
Image
The nice thing about garbage-collection is that it is makes memory management absolutely transparent to you Of course, the above is true right up to the point when it stops being transparent, at which point it does a phase change from nice to clusterf**k of biblical proportions .  There are entire posts, books, and suicide notes that have been written about this, and I have no great desire to add to them, save with the minor comment that paranoia about garbage-collection is still justified , albeit only in the edge-cases for most people. That said, I'll give you that Erlang GC is in many ways much, much better positioned in this regard than, oh, Java, but it still rears up and bites you in the butt when you least expect it. ( More information about Erlang's GC vis-a-vis Java here , and Jesper's truly excellent description of Erlang's GC here ).  A story from the past should serve to illustrate this. Once upon a time, in a magical land far far away - well, Her...
Read more

Spot The Difference — Deep Learning Edition

-
Image
You’ve played  Spot The Difference  at some point, right? (Of course you did. We  all  did  ). Think about what you actually did when you were trying to Spot The Difference — in fact, just do it again with SpongeBob juggling above. You’re probably doing something like 1. Quick glance to the left. 2. Quick glance to the right 3. “ Spatula on the left. Wonder if there is one on the right? ” 4. “ Yup, there is. Sriracha on the right. Is that on the left? ” 5. “ Nope! It’s a ketchup bottle on the left! And there is nothing on the plate below it! ” etc. To summarize, what you’re basically doing is looking at each image alternately, identifying objects in each image, and trying to find the same object in the other image. As it turns out, what most Deep Learning systems do is something quite different. They basically do something like this 1. Figure out everything in the first image (“ ketchup bottle at 1 o-clock, empty plate at 3 o-clock, spatula at 1...
Read more