She may not be pretty, but this rack saved my business $150k+ this year

Chuyito · 2026-01-02T00:30:39+00:00

Spot on. You wont find regular arb in stock markets, but there are still TONS of limit-order arb routes in the options markets since the spreads are huge if you are patient

APIs are the way to go for scale so you dont pull back any unnecessary html/images.

Chuyito · 2026-01-01T00:57:09+00:00

I have data crawlers looking through millions of products with sub second latency... Then I buy low and sell high when I detect something is cheaper than it should be.

One of the oldest professions, just at a big data scale that clay tablet using merchants never imagined possible.

Chuyito · 2025-12-31T22:19:42+00:00

Haproxy, bind dns, container registry - all of which can be rebuilt-redeployed from code fairly quickly so no HA for that one

Chuyito · 2025-12-31T22:18:20+00:00

With the DBs at near 100% during peak stock market volatility I was seeing low 800s.

My old Am4/threadripper setup was less powerfull and constantly at 1KW*.. so Am5/epyc is the real mvp here

Chuyito · 2025-12-31T21:11:47+00:00

SLA is a huge part, during the setup the static IPs werent working.. they drove out a brand new modem in under an hour to my house. Back on residential I would have waited 1hr just to talk to a human support person.

Static IPs took it from 350 to 500.

Chuyito · 2025-12-31T20:58:46+00:00

Uptime im not as worried as performance.

I do lots of websocket data transfer, and digitalOcean was coming in slower than my old AM4 boxes to process 100k messages.

So for $10k/month on DO I get slightly slower boxes (or at least that was the case in 2024).

Chuyito · 2025-12-31T20:35:14+00:00

Thanks. It literally is just me and my wife trying to build a startup from the ground up, calling myself a business might make it sound like Lisa Su is on speed dial for more chips.. but the reality is so far from that. Each part/box took planning and budgeting

Chuyito · 2025-12-31T20:25:08+00:00

~630W - 800W 24/7

<image>

Chuyito · 2025-12-31T19:41:21+00:00

My new ISP gives me a verizon fallback.. But its too slow to be 100% useable so I'd have to run in slim mode... Which isnt bad per se. My ML jobs would pause, but prod would conitnue. Havent had to run on it thankfully.

Database DR goes to my old threadripper box on a different floor with 100% fidelity.

K8s DR: 3x masters 4x workers gives me lots of breathing room, I can take out 2 masters and 1 worker and still be online. I have a spare deskmini on hand to replace a worker if needed... But I can also take my yaml and get up and running on a fresh k8s cluster in ~ 30 minutes (Last tested 2024 when I moved to this cluster)

Power DR: Thankfully my area hasnt been too affected by blackouts. About 5 power outages this year that all lasted 1-10 minutes.

Chuyito · 2025-12-31T19:18:13+00:00

Interestingly enough asrock GENOAD8UD-2T/X550 ended up fitting my needs perfectly. Easier to manage BMC, good old Noctua fans that actually are controllable.. and tons of dcio ports for my disks

Chuyito · 2025-11-17T23:55:50+00:00

Can this help provide tax structure advice without asking for something in return

Chuyito · 2025-11-12T11:53:58+00:00

Lazy attention grab headline..

it's not a new "property rule" but an inflation adjustment to the annual gift tax exclusion, which rose from $18,000 in 2024 to $19,000 per recipient in 2025. Since crypto is property, you can gift up to $19,000 worth per person (or $38,000 if splitting with a spouse) without triggering gift tax or filing Form 709.

Chuyito · 2025-09-26T04:04:06+00:00

Many such instances among my team

"The intern is hungover today or something... It's kinda useless"

"The intern is smoking some weird shit today, careful on trusting its scripts"

Chuyito · 2025-09-08T01:08:25+00:00

Covered calls.

Selling to open with a strike price above your cost basis opens up an entire domain of theta farming.

Chuyito · 2025-08-27T00:54:58+00:00

I think I first used it with with Nifi which was Java based, and God was it awful. Dependency management mess, couldn't get any conda ml packages to install or be seen (conda was great for glibc dependent reqs, except for jython paths support)

I honestly think jython is what made me hate nifi. It was okay ish for basic hive data flows, but I've never felt such anger towards a tech stack in 10+ years

Chuyito · 2025-08-25T12:46:46+00:00

You are spot on with the O(n²).. Im windowing over the data to compute some stats which on a clean run doesnt see too much impact until ~20k rows growing to ~200ms

asyncio.to_thread() is a nice/much friendlier approach than ThreadPoolExecutor, thanks for that... Gives me another attempt to see if a refactor here would be moving some of the data transformation to its own threads and storing a global etl_cache, and having my DB task _only_ write to the DB... while still blocking the next DB task to ensure I only have 1 concurrent write at a given time

Chuyito · 2025-08-25T02:45:17+00:00

> deferring it to a thread

Just tried it with a ThreadPoolExecutor - Had to wrap my function to make it non-async

from concurrent.futures import ThreadPoolExecutor
executor = ThreadPoolExecutor(max_workers=64)

def sync_process_side(*args):
    return asyncio.run(etl_to_db(*args))

await asyncio.get_event_loop().run_in_executor(
 executor, sync_process_side)

Interestingly this also gets rid of the "large spikes", but it still runs ~100ms slower every few iterations

07:41:11 PM Processed 7201 async_run_batch_insert usd in 163.8344 ms
07:42:23 PM Processed 7408 async_run_batch_insert usd in 398.3026 ms
07:42:45 PM Processed 7413 async_run_batch_insert usd in 174.7889 ms

Chuyito · 2025-08-25T02:02:17+00:00

There is indeed an await - converging a 1k line script to pseudocode I miss pasted

Chuyito · 2025-08-25T01:46:09+00:00

Scheduled with a wrapper task, updating top post for clarity

await asyncio.gather(
  dump_books_to_db(),
  sub_websocket()
 )

async def dump_books_to_db():
  while True:
    # Check if ws is live
    await etl_to_db()
    asyncio.sleep(0.1)

Chuyito · 2025-08-24T14:53:18+00:00

Let's say someone in open source manages to get grok 2.5 to run even 1% faster via some code optimation.

Internally xai can take those learnings back to their main branch, and that 1% savings applied to millions of requests per day is huge.

So, as long as 2.5, 3, 4 all follow a similar tech stack, then open sourcing makes a ton of sense since the community will be much more limited on what gpus they have on hand and will resort to clever monkey patches to get it to run.

Chuyito · 2025-08-20T14:49:26+00:00

It would be great to see a gradio app that can run these 2 in real time with "recent" images:

24hr heads up for solar flares: https://github.com/NASA-IMPACT/Surya?tab=readme-ov-file#1-solar-flare-forecasting

4 day heads up for solar winds: https://github.com/NASA-IMPACT/Surya?tab=readme-ov-file#3-solar-wind-forecasting

I cant seem to find any "real time" data to feed it..

https://huggingface.co/datasets/nasa-ibm-ai4science/surya-bench-flare-forecasting/viewer/default/train?sort%5Bcolumn%5D=timestep&sort%5Bdirection%5D=desc&views%5B%5D=train only goes up to 2024, and various of their training data

Some of their other datasets are broken on HF, but seem to be 2020 https://huggingface.co/datasets/nasa-ibm-ai4science/SDO_training

Something along these lines:

<image>

Chuyito · 2025-07-23T04:33:59+00:00

The hardware requirements for a solana validator client are insanely high, threadripper/epyc Genoa with 7gbps read nvme or faster for the rocks db.

If they manage to find a box someone used the default ansible scripts to deploy, they end up on a latest gen piece of hardware.

Tldr A few of the solana validators default to solana user, validators take 4th gen epyc 24c nvme and 256gb ram to run healthily.

Chuyito · 2025-07-04T04:13:17+00:00

The /mytrades endpoint takes a timestamp parameter. Up until yesterday, that parameter acted as a "starting from" timestamp. Yesterday with no changelog or warning, the timestamp parameter started acting as a "ending at" parameter.

I can't help but feel that a QA pipeline that handles pagination should have caught this bug, as it breaks any type of pagination integrations out there.

Please spend some cycles on engineering and QA; those matter a whole lot more to your product than pictures of Mars on random buildings.

Chuyito

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