Peter Alvaro: What not where: Why a blue sky OS? BuzzConf 2020 (Video)

A world of distributed, persistent memory is on its way. Our programming models traditionally operate on short-lived data representations tied to ephemeral contexts such as processes or computers. In the limit, however, data lifetime is infinite compared to these transient actors. We discuss the implications for programming models raised by a world of large and potentially persistent distributed memories, including the need for explicit, context-free, invariant data references. We present a novel operating system that uses wisdom from both storage and distributed systems to center the programming model around data as the primary citizen, and reflect on the transformative potential of this change for infrastructure and applications of the future.


Wow. Thanks for surfacing this talk. This is better and more relevant to what I am interested in then what any AI could bring me.
I stopped wasting time in doing my own technology scouting. Instead just follow what you are writing and organizing. I struggle to keep up and learn from them.

Haha. Thanks @TrailMarks. I need to go through this video again and take some notes. And blog! We can all learn and organize together.

I thought with all that IPLD wizardy you are doing the similar to what I work towards:
A Blue Sky Web Native OS (I call kernel) which operates on the same principle of
data as a first class citizen.
I am adding to that the notion that all data is a graph and all you need to do is to retrieve in one operation immediate neighbourhood of a node of interest and propagate updates.
You had some really nice phrase about IPFS being a common shared data layer or something along the lines.

Brooke is slowly being comfortable with me talking about a “web operating system”. It’s not quite the right layer, as we think about a persistent data layer and identity, apps, and compute, you see there are some pieces coming together.

IPFS is an example of a “commons infrastructure”.

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to toggle the date locale using a graphQL query

I read it as toggle data “locale” using graphQL query

Transparent switching between storage systems and universal interoperability layer across them

Completing the natural progression from SQL, to No SQL, No API, no Database

“What not where”

hat would have been stating the “secret sauce” behind MindGraph, TrailMarks the works