This is not a post about Brexit; this is about conversations. Storytelling rose in the 80’s as a key marketing tool – phenomena like the Nescafe “Gold Blend” adverts demonstrated how the ability to tell a story could convincingly engage consumers en masse. Truth be told, this was nothing new – the “soap opera” is so-called because those ongoing serial dramas used to be sponsored by soap manufacturers. But, the key insight by the storytellers was that creating a story around a message you wanted to communicate (rather than simply being associated to or referenced by the story) was very powerful.
Having droned on a little the other day about duplication in Stackanetes (in hindsight, I had intended to make a “it’s turtles all the way down” type jibe), I’ve been delighted to read lots of other people spouting the same opinion – nothing quite so gratifying as confirmation bias.
Massimo has it absolutely right when he describes container scheduling as an incestuous orgy (actually, he didn’t, I just did, but I think that was roughly his point). What is most specifically obvious is the fact that while there is a lot of duplication, there isn’t much agreement about the hierarchy of abstraction: a number of projects have started laying claim to be the lowest level above containers.
There’s a great demo from the recent OpenStack Summit (wish I had been there):
OpenStack is a known massive pain to get up and running, and having it in a reasonable set of containers that might be used to deploy it by default is really interesting to see. This is available in Quay as Stackanetes, which is a pretty awful name (as is Stackenetes, and Stackernetes, both of which were googlewhacks earlier today) for some great work.
Over the past couple of days I’ve been engaged in a Twitter discussion about serverless. The trigger for this was Paul Johnston‘s rather excellent series of posts on his experiences with serverless, wrapped up in this decent overview.
First, what is serverless? You can go over and read Paul’s explanation; my take is that there isn’t really a great definition for this yet. Amazon’s Lambda is the canonical implementation, and as the name kind of gives away, it’s very much a function-oriented environment: there are no EC2 instances to manage or anything like that, you upload some code and that code is executed on reception of an event – then you just pay for the compute time used.
“Passion burns most fiercely when fuelled by success”
The various videos of the speakers from Tech2020 – including yours truly – are up and available for Skillsmatter members. Going back to my previous blog post, I can heartily recommend the speakers who I was excited about, but have to say, I was blown away by the overall quality of the conference. Even those topics I didn’t think would hold much interest or news for me turned out to be incredibly interesting, and I daresay the next editing of this conference will be something to watch out for.
For a while now, I have been waxing lyrical (to those who will listen) about the variety of new tools and analyses available to people who want to prognosticate. If nothing else, the current craze for data within most businesses has resulted in people almost literally swimming around in the stuff without an awful lot of an idea about what to do with it, and while this has lead to some unspeakably shambolic practices (those who know me will likely have heard me on my hobby horse about proving models with actual experimentation) it has also opened up new horizons for people like me.
Not that long ago, I did a switch on my Android phone: against all the promises I made to myself beforehand, I switched on the Google account and allowed it to sync up to GCHQ/NSA the cloud. I did this for one main reason: I had just got an Android tablet, and I despised having to do the same stuff on each device, particularly since they weren’t running the same versions of Android, and one was a Nexus – so not all the UI was the same. The benefits, I have to say, were pretty much worth it: I don’t have too much sensitive data on there, but the ease of use is incredible. What was particularly good was that when I broke my phone, and had to have a new one, once the new one was linked up everything was basically back how it was. That’s tremendously powerful.
In my previous post about virtualenv, I took a look at a way of making python environments a little bit more generic so that they could be moved around and redeployed at ease. I mentioned docker.io as a new tool that uses a general concept of “containers” to do similar things, but more broadly. I’ve dug a bit into docker, and these are my initial thoughts. Unfortunately, it seems relatively Fedora un-friendly right now.
