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AWS emulator

https://github.com/aws/aws-emulator
571•super_linear•5h ago•193 comments

Tim Peters has died

https://discuss.python.org/t/in-memoriam-tim-peters-1952-2026/110028
752•ayhanfuat•16h ago•75 comments

United Airlines bans AI agents from booking flights on behalf of travelers

https://www.cbsnews.com/news/united-airlines-bans-ai-agents-booking-flights/
236•herpderperator•2h ago•224 comments

93% of Paint Splatters Are Valid Perl Programs (2019)

https://www.mcmillen.dev/sigbovik/
36•zenincognito•58m ago•7 comments

A false smoke alarm almost drowned Jane Street's only NYC datacenter

https://michael.bacarella.com/2026/11/10/false-smoke-alarm-jane-street-datacenter/
372•mbac32768•6h ago•185 comments

Lock Your GitHub Actions

https://hugovk.dev/blog/2026/lock-github-actions/
49•gslin•1h ago•12 comments

Gemini Decisions API

https://blog.google/innovation-and-ai/technology/developers-tools/gemini-decisions-api/
197•iamdelirium•4h ago•67 comments

Emacs in the Age of Magic

https://commandlinesystems.com/magic.txt
108•ggcr•3h ago•40 comments

Show HN: I recreated Papers Please but you're deciding which YC startups to fund

https://termsheetplease.com/
144•bolau•4h ago•63 comments

Huawei releases MACaQ, its internal quantizer for local inference

https://github.com/huawei-csl/MACaQ
40•thefox96•3h ago•17 comments

The Utah Teapot

https://graphics.cs.utah.edu/teapot/
44•cobbal•3h ago•11 comments

Faster Retrieval for Better, More Efficient RAG

https://machinelearning.apple.com/research/faster-retrieval
130•zerop•6h ago•23 comments

Flying on Green: Why Farmers Are Turning to Drones for Cover Crop Seeding

https://www.agweb.com/news/machinery/flying-green-why-farmers-are-turning-drones-cover-crop-seeding
28•rmason•2d ago•17 comments

My AI agents found an unmapped Maya site

https://pietromiotti.com/latest/maya-site
903•eyvindn•11h ago•332 comments

A Brief History of Sierra Online (2017)

https://retrofreakreviews.com/2017/01/30/sierra-retrospective/
6•freshtake•1d ago•0 comments

Nvidia prepares to fire CEO Jensen Huang, WSJ reports

https://twitter.com/watcherguru/status/2120645607866188008
41•alexmolas•55m ago•2 comments

Hyper-Realistic Sand with WebGL2

https://av.github.io/safe-sand/
280•everlier•9h ago•59 comments

Show HN: Yogurt – Free, private, open-source alternative to Granola

https://github.com/FrigadeHQ/yogurt
148•brownrout•7h ago•68 comments

Optimizing Reference Deletions in Git

https://nayak.im/posts/optimizing-reference-deletion/
12•nayak•3d ago•0 comments

Launch HN: Pomerado (YC F26) – Turn any website into an MCP for agents

41•alanjm23•6h ago•35 comments

The hardest notes to find on the guitar

https://www.gitori.com/blog/articles/hardest-notes-on-the-guitar-fretboard
43•udit99•7h ago•56 comments

Atuin Threads: All your agent sessions on every machine

https://blog.atuin.sh/threads-agent-sessions/
180•linsomniac•9h ago•65 comments

IBM Quantum Nighthawk Demonstrates New Levels of Speed and Quality

https://newsroom.ibm.com/2026-11-11-ibm-quantum-nighthawk-demonstrates-new-levels-of-speed-and-qu...
41•gok•3h ago•22 comments

Nvidia Is Preparing to Oust Nvidia CEO Jensen Huang

https://www.wsj.com/business/nvidia-is-preparing-to-oust-nvidia-ceo-jensen-huang-30f421ad
241•jbredeche•1h ago•206 comments

The Apple Support Community will permanently close on November 20, 2026

https://discussions.apple.com/welcome
97•tech234a•20h ago•198 comments

Can a Linear Program Do Weight-Space Programming?

https://nathan.rs/posts/weight-space-lp/
230•emschwartz•11h ago•34 comments

Using voltage glitching to unleash the A100 in my mining card

https://blog.kate.land/posts/using-voltage-glitching-to-unlock-the-a100/
252•lae•12h ago•101 comments

Tools for exploring the souls of large language models

https://oshea00.github.io/posts/tinygpt-visualizer/
24•r00tanon•2h ago•8 comments

Tinfoil (YC P25) is hiring an applied AI security engineer in San Francisco

1•FrasiertheLion•11h ago

We need more goat sacrifices

https://www.experimental-history.com/p/we-need-more-goat-sacrifices
180•iamnothere•11h ago•104 comments
Open in hackernews

Garbage collection of object storage at scale

https://www.warpstream.com/blog/taking-out-the-trash-garbage-collection-of-object-storage-at-massive-scale
96•ko_pivot•1y ago

Comments

juancn•1y ago
Another possible mechanism for doing GC at scale (a variation on Asynchronous Reconciliation in the article) in some file/object store, is doing a probabilistic mark and sweep using bloom filters.

The mark phase can be done in parallel building many bloom filters for the files/objects found.

Then the bloom filters are merged (or'ed together essentially) and then a parallel sweep phase can use the bloom filter to answer the question: is this file/object live?

The bloom filter then answers either "No" with 100% certainty or "Maybe" with some probability p that depends on the parameters used for the bitset and the hash function family.

cogman10•1y ago
What does the bloom filter solve?

The expensive portion of the mark and sweep for the object store is the mark phase, not the storage of what's been marked. 100s, 1000s, or even millions of live objects wouldn't hardly take any space to keep in a remembered set.

On the other hand, querying the S3 bucket to list those 1M objects would be expensive no matter how you store the results.

But this does tickle my brain. Perhaps something akin to the generational hypotheses can be applied? Maybe it's the case that very old, very young, or very untouched objects are more likely to be garbage than not. If there's some way to divide the objects up and only look at objects whose are in "probably need to be collected" regions, then you could do minor fast sweeps semi frequently and schedule more expensive "really delete untracked stuff" infrequently.

Cicero22•1y ago
I was thinking they could use something like cloudwatch events, or something, to trigger sweeps and significantly reduce scheduled sweeps.

They could even use cost allocation tags to predict if a bucket or group of buckets should be scanned if it's growing unexpectedly. Cost isn't a perfect metric but there's definitely signal there.

juancn•1y ago
Building the set of used files or objects (which is what mark does in a mark/sweep).

Sometimes it's too expensive to mark in place, even if it's a bit that you need to write to disk and keeping a set of references may be prohibitive (or the structure holding the references is mostly/effectively immutable).

If it's all memory and mutable it doesn't (normally) really matter, but when it's not, you ideally would have some mechanism to move the code to where the data is, rather than stream the data to where the compute is (it is really wasteful for large scale data processing).

In any case, you would not be moving/scanning the files themselves, but the metadata is what you want to read for the mark phase.

The article if I understood correctly implies that the files and the metadata of the files (Kafka queues and so on) are separate, so presumably, the metadata is much much smaller than the data itself, but still potentially large.

For example if you had a large scale content addressed store (think a massive version of git's blob storage), you typically add to something like that and keep a few mutable root references to start your GC from to seed a mark/sweep.

Following the git example, the roots would be the branches, tags and reflogs, and the metadata you scan the transitive closur of the trees that are reachable from those (simplifying a bit) but not the file blobs themselves.

I use git as an example because a a CAS lends itself very well to large scale distributed systems because you can reason about it as an immutable data structure, but you can still change it effectively with sane semantics.

donavanm•1y ago
If you like big beautiful storage and probabilistic structures check out https://www.usenix.org/conference/osdi14/technical-sessions/.... The coho data folks ended up in AWS S3 a few years later.
juancn•1y ago
Thanks! I hadn't seen it and it may come handy!
deathanatos•1y ago
> Why Not Just Use a Bucket Policy?

I've heard these words so many times, it's refreshing to see someone dig into why bucket policies aren't a cure-all.

As for "Why not use synchronous deletion?" — regarding the pitfall there, what about a WAL? I.e., you WAL the deletions you want to perform into an object in the object store, perform the deletions, and then delete the WAL. If you crash and find a WAL file, you repeat the delete commands contained in the WAL.

(I've used this to handle this problem where some of the deletions are mixed: i.e., some in an object store, some in a SQL DB, etc. The object store is essentially being used as strongly consistent storage.)

(Perhaps this is essentially the same as your "delayed queue"? All I've got is an object store though, not a queue, and it's pretty useful hammer.)

telotortium•1y ago
> HN Disclaimer: WarpStream sells a drop-in replacement for Apache Kafka built directly on-top of object storage.

First time I’ve seen one of these. That’s actually a better way to advertise your product than putting it at the end.

hencq•1y ago
Yes, though I think they meant to say disclosure instead of disclaimer.
siscia•1y ago
What I see working extremely well, arguably in a setting where cost was not really an issue was a much simpler approach.

Keep compacting files at some regular cadence `t` and keep a bucket policy to delete files older than `t+delta+buffer`.

Then have an alarm for files older than `t+buffer`