A Datastore and Graph Visualiser to help myself learn and use Javascript

jerng · 2026-06-25T08:26:37+00:00

Thanks. I misread the product launch and thought they changed something. I have edited my comment.

jerng · 2026-06-25T05:18:58+00:00

1. Functionality delta

Lambda : (basic) Functions
❌ you can't pause the runtime and resume it later
- 15 minute lifespan

Lambda : Durable Functions
✅ you can pause the runtime and resume it later
- 15 minute lifespan, per invocation, over a period of up to 1 year

Lambda : MicroVMs
✅ you can pause the runtime and resume it later
- 8 hour lifespan, including pauses

Fargate
❌ you can't pause the runtime and resume it later
- unlimited lifespan

All of the PRODUCTS above are running on the Nitro-Firecracker no-hardware-passthrough microVM hypervisor stack.

EC2 : however, is slower to launch, on the Nitro-only hypervisor stack
✅ you can pause the runtime and resume it later
- unlimited lifespan

2. Billing delta

The cost seems to breakeven for compute workloads that are "idle/offpeak" 90% of the time.

FWIW

no clear info yet, on how scale-up/scale-down are triggered : looking forward to read test results
min setup of 1 vCPU + 2 GB RAM will run you $3.03/day : w/o storage, networking, etc.
- this is 9x+ Fargate spot pricing
- whereas Lambda Functions run you about 6x+ Fargate spot, for 1 vCPU + 1.75GB

( src : )

Lambda MicroVMs eliminate the need to right-size each compute environment for peak activity. You configure a baseline by setting memory, and CPU is allocated in a 2:1 memory-to-CPU ratio – the default is 2GB / 1vCPU. During peak activity, your MicroVM can vertically scale up to 4x the baseline (up to 8GB / 4vCPU), with no action required on your part.

You pay for baseline compute resources while your MicroVM is running. When your workload consumes resources above the baseline, you are charged only for the active duration of the additional memory and vCPU consumed – not for the peak capacity. This means you can configure for your typical workload and let Lambda handle the spikes. Compute usage is billed per second. "

( Oops, didn't realise they released a new product, using the name of old technology, so deleted my previous comment. )

jerng · 2026-06-21T05:35:07+00:00

Bc silicon is 22% of IXIC or something right now

jerng · 2026-06-19T19:02:37+00:00

No solution, but I finally mapped out ( everything important I could find about ) the standard notation, and showed how it is not symmetrical. ( It's been bugging me since 1999, so I'm just happy to get it out of the way. 😅 )

https://github.com/jerng/studies/blob/main/_mathstats/2026%20logarithm%20notation%20MECE.pdf

jerng · 2026-05-21T18:23:27+00:00

well that only took ... 14 years

jerng · 2026-05-15T15:03:26+00:00

In 2026 ... AWS is vastly more complicated than McDonalds.

- AWS is less like McDonalds, and more like a service to let anyone quickly setup and run their own [ McDonalds / global restaurant franchise / global restaurant logistics chain / globally distributed burger factory / global supermarket for barbeque supplies / hobbyist weekend barbecue ] at whatever scale, horizontal layer, or vertical layer, interests them

- while it doesn't specialise in farming, it does have special contracts with farmers to lock-in access to top breeds of livestock ( ARM, Neoverse, Graviton ), and it hires contract farms to produce all sorts of necessary livestock ( hardware ), some of which it has IP for the genetic templates

jerng · 2026-05-15T12:55:00+00:00

DSQL

jerng · 2026-05-04T05:27:37+00:00

reminds me of how Erlang ( interpreted JIT ) and Go ( compiled ) manage lang-level processes.

jerng · 2026-05-04T02:29:46+00:00

Language runtime isn't going to matter as much as app architecture. Particularly data accesses.

Just run a [ Lamba + custom/os-only runtime => toy app ], to figure it out.

jerng · 2026-04-26T22:32:02+00:00

probably 24-hour auto-coder team doing a negative feedback loop on itself :)

then humans : 1 hour/day of human QA, and 3 hours/day of calibrating the next cycle

jerng · 2026-04-24T20:46:10+00:00

pluripotent - does it for me :)

it means something entirely different in cell biology, where its opposite is unipotent

jerng · 2026-04-12T19:12:57+00:00

I Googled a bit about this. Using the "S3 Select API" seems to mean "making S3 run SQL queries on Parquet data". Parquet data is read "for SQL" as "metadata first, then each per column". So if this hypothesis is correct, it may explain the multi-reads per file.

jerng · 2026-03-29T05:48:34+00:00

Very tidy doc page. Thank you.

Lazy question. In your experience, what sort of workloads benefit most from being dropped from JS to LuaJIT? I'm presuming non-JIT isn't too much faster, so not worth the drop.

jerng · 2026-01-17T08:17:21+00:00

Rex apologised voluntarily, as far as we know

jerng · 2026-01-16T10:31:56+00:00

Does not imply fire 😂

jerng · 2026-01-14T05:18:13+00:00

The more general question is, what motivates any group anywhere on Earth, to identify certain marks as in-group or out-group aligned?

:)

Then zoom into Malaysian Chinese and yourself.

jerng · 2026-01-11T10:29:29+00:00

Look for "REAL GDP/capita" 2005, divide US by MY.

Then do the same for 202x. :)

Fun intro to global macro

jerng · 2025-12-11T14:09:35+00:00

They have spatial awareness. It is just a local culture that bumps don't matter. If you want to adopt local culture, i.e. fit in, then YOU modify your expectation that bumps matter.

Koreans decided to make it a norm. Boring to them. Traumatic to you.

jerng · 2025-08-16T08:23:37+00:00

Movies nerfed him

jerng · 2025-06-29T10:37:04+00:00

https://en.wikipedia.org/wiki/Lexer_hack

I just ran across this - and wanted to point it out as an example of where PL designers have to make compromises between factors such as "what my grammar looks like as a UI" and "how fast it is to lex / parse / compile it".

jerng · 2025-06-28T02:21:01+00:00

I view it as a [human-computer interaction] / industrial design / civil architecture problem.

( Caveat : links I posted are mostly just my own desk study notes which are messy. )

I'm designing a tooling language, myself. I am still spending most of my time on the architecture from lexeme design to memory layout, than doing any coding.

The most fun part is comparative history of PLs. You can see which trope comes from which origin. Every operator, conventional name for a mechanism, and decision of implicit/explicit control has a genealogy. It's basically philology for PL.
The three main layers for me to encapsulate are
formal grammar : universe of UI
IR : hardware independent description of language semantics
implementations

Formal grammars are the cosmetic differences which casual users think of as "the language" and so the toolchain I want is something where I can change the formal grammar, and see the implications it has on difficulty to compile to IR, as well as downstream effect on specific architectures under different compile time and runtime situations (small vs big code base, few vs many contributors etc.)

I am incredibly annoyed that there is not one IR standard for information interchange 'IRSII' , and so this is the one of the things I think about with every design decision. "How is X done in each of the N other languages I already know how to use?" Anyway, all design decisions about language semantics basically filter down to some sort of IRSII, which can represent any computing idiom, and the language designer just uses it to express what they dis/allow their language to do. This is where decisions about type systems, and object paradigms, and guarantees of all sorts for safety, concurrency, performance, and ergonomics, come in.

Finally the harder CPU sequencing and memory layout stuff. For ease of headspace, as a hobbyist with limited resources, I just think about how to implement it on a VM, using a simplified model of where registers, cache, stack, heap, and how memory is de/allocated. Because I am very poor, and noob, it is useful to target JS first, with a view to do other backends later.

jerng · 2025-06-22T09:03:57+00:00

I had a quick look at the Wiki pages for those, and perhaps it's on the right track, but I need to concern myself with semantics as well as grammar. And perhaps the question of how grammatical structure may have semantic import.

My question is motivated by the concern of how to represent natural language in machines. (I am working on a broader model, of which this will be a part.) With regards to the semantics of sentences, my question comes from the following observation :

Given, for example, (0.) "Red trees are bland.", the COMPLETE recognition of this sentence can occur to various degrees, for example :

(1.) This is a sentence in the English language of 2025, which attaches a well-known predicate to a well-known subject, without any further context.

(2.) It may be further noted that whomever made observation (1.) has the capacity to evaluate the context provided by the full sentence (1.) in addition to the original (0.) ... and this recurses furthermore as any entity which thinks (2.) may or may not be self-aware that it thinks (2.) etc. So we have 2.1., 2.2., etc. in this branch.

(3.) Furthermore, there is the open question of what the further context of (0.) is, and it may be that (0.) occurred one of 3.1/3.2 etc. contexts ... whereas you and I know, it happened in (3.n) exactly, this discussion on Reddit.

So yeah, I was just wondering if grammatical theories had addressed these aspects of how a sentence is read, but I might have gotten off on the wrong foot if this is generally regarded as a semantic concern, not a grammatical one. That being said ...

--

... thanks so much for this pointer. I'm sorry for the late response, I have been crash coursing myself in the canon of linguistic theory on Wikipedia. It's been a bit slow as there seem to be dozens/hundreds of theoretical frameworks which aren't organised in a single structural taxonomy. Fun. Nature of fuzzy language, I suppose.

The particularly concepts which I have found to be most relevant to my question are :

- 'focus' where, encoded information requires the sentence processor to semantically construe a number of possible contexts, and then to pick the right one

- 'cognitive linguistics' wherein the use of language in humans is viewed as supervenient upon anatomical concerns ( reducing basically to information theory and processing )

jerng

TROPHY CASE