trumpeta

I live in a place with 30% humidity inside for about 1/2 of the year. I had real issues with my eyes getting dry. I’ve tried drops, went to the doctor, etc. In the end the issue was that I was not sufficiently hydrated. When I started drinking 2-3 liters of water per day, all my eye issues went away.

sure but so is social media and ultra processed food. Both with much greater impact, why not start there?

Have a look at https://github.com/hannobraun/fornjot

The reason I chose Synology over others was their SHR "filesystem", where you can continue adding heterogeneously sized disks after constructing the FS and it will make the most use possible out of the extra capacity in the new disks. When I researched it ZFS did not yet have the resizing feature merged, now it does, though I think it is still not able to use this extra space.

I'm wondering if anybody has any better recommendations given the requirement of being able to add storage capacity without having to completely recreate the FS.

angry Python noises

I think it's great advice, but the "finish rarely" part is maybe understated. The goal is to try as many things as possible, as quickly as possible in order to find your true calling. You'll stick with it once found.

It's meant to imply that it's as performant as, but safer than c/c++.

no it says it includes “human review”

You can choose a different game engine or write your own. You can not write an app for iOS without Apple SDK

Interesting article. I wonder if the FS abstraction is not too large, maybe it could be split into various layers, such as the Physical layer (block KV store), intermediate with building files from blocks and last UI layer with FS or Object Store type access. Kind of similar to what's happening in the database space with Query Engines like DataFusion.

Great! Now do trilingual!

I'd still rather stare at a blank screen for 20s than view the ads.

What do they do when GitHub is down?

I think the self-hosted bit is just for syncing, as long as you have multiple devices its not likely to lose data even if you don't follow the 3-2-1 backups.

They were making austerity jokes in Yes Minister!

I hope Apple loses and is forced to change their logo i to something like a bitten iPhone. The other company make actual apples and for longer than Apple, so they should have the right of way.

also much less likely to get shot there than at school!

Another way of doing this is assign Hyper key to Caps Lock with Karabiner and then use that to set up hyper+X shortcuts to different or macros using Hammerspoon.

So e.g. I have hyper+a for Alacritty, hyper+b for Browser etc.

The battery won't spin and lose all charge, it has a breaker mechanism that will stop it similar to how seatbelts work, it gets stuck if it pulls too hard. This is to prevent damaging a circuit if you forget resistors.

Of course this is a model of how electricity should work, but it is still useful and they document the differences from "real" electricity decently in the books.

In any case its a super fun toy and I highly recommend getting it!

At what scale have you decided you’ve outgrown it?

ELT approach means you copy raw data from transactional sources, events, external APIs and dump it in the first “layer” of your data warehouse.

Then you progressively clean it and model it into some format that is easily usable for dashboards or self service analytics.

To do that you build a DAG of SQL scripts and dbt makes that easy through templating, macros and automatically generated docs.

You still have to execute the DAG somehow and here you either use their OSS version and schedule it with anything from Github Actions to Airflow, OR you buy their Cloud offering

what makes Ante low level? Just from a cursory look over the website seems pretty high level to me.

We operate a (small?) Airflow instance with ~20 DAGs but, one of those dags has ~1k tasks. It runs on k8s/aws setup with a MySQL backing it.

We package all the code in 1-2 different Docker images and then create the DAG. We've faced many issues (logs out of order, missing, random race conditions, random task failures, etc.)

But what annoys me the most is that for that 1 big DAG, the UI is completely useless, tree view has insane dupplication, graph view is super slow and hard to navigate through and answering basic questions like, what exactly failed and what nodes are around it are not easy.

Torvalds (I think):

> Bad programmers worry about the code. Good programmers worry about data structures and their relationships.

The problem with dogmatic OOP is that it mixes data structures and code into one. This leads to hard to modify code, unexpected side effects, poor parallelism. Imperative or FP code does the minimum to define what the data should be shaped like and then has a bunch of functions that either modify it or do some IO with it.

That's a lot easier to trace through and reason about. That in turn leads to more malleable code, which lets you evolve it faster as your understanding of the problem domain evolves.

ddg has the same issue though

Maybe I can offer an answer to your question, I have worked at a couple of companies where we ran "small" scale k8s clusters (1-100 nodes as you say).

We have chosen k8s and I would again, because its nice to use. Its not necessarily easier, as you point out, the complexity of managing the cluster is considerable. But if you use a managed cluster like EKS or DO's k8s offering, you don't have to worry too much about the nodes and the unit of worry is the k8s config and then for deployment you can use Docker.

I like Docker, because its nice. Its nice to have the same setup locally as you have remotely.

In my experience the tooling around k8s is nice to manage declaratively, I never liked working with machines directly because even tools like Chef or Ansible feel very flimsy.

The other thing you can do is run on ECS or similar, but there the flexibility is a lot lower. So k8s for me offers the sweet spot of being able to do a lot quickly with a nice declarative interface.

I'd be interested to hear your take on how to best run a small cluster though.

You’re making a great point there about procedural mindset being applied to array programming. But the thing is, I feel like array based programming should lend itself naturally to functional approaches. And Pandas does do this to an extent.

My problem is that this is super inconsistent. Some things are done as a method call on an object, others by passing the object to a pandas function and others yet by passing a function to a method on an object. This is the major source of frustration for me.

Maybe there is some logic to that, but I haven’t found it yet and I think that is a sign of bad API design. Its like PHP to me. All nice and documented but useless without Googling everything

Do you have an opinion on MSK?

> I got here by taking no risk at all. > This is the most European thing I've ever heard. Most people would not like to take risks and would not even think about stepping outside of their comfort zone.

In some sense this is true, but lets not get carried away. The American Startupism is all about the flash, big growth, big impact, big IPO. In EU you have companies slowly grinding a hard problem for 20 years that also have huge impact but no flashy news. Look at things like vertical farming, ASLR, fintech. Thats all thanks to low risk and stability.

correct, but the tuition is peanuts compared to US or in some cases places like India.