FLflippant·Aug 23, 2024Submission
FLAME – Auto scale parts of your existing app
1 points · Open discussionphoenixframework
flame
Elixir2023–2024
phoenixframework / flame
flame
Fleeting Lambda Application for Modular Execution: auto scale parts of your existing app with a single function call
4Distinct people
4Mentions
0Explicit recommenders
1.2KGitHub stars
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What it is
Fleeting Lambda Application for Modular Execution: auto scale parts of your existing app with a single function call
GitHub
Where it is used
No documented product use has been verified yet.
What people are saying
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This week on Hacker News
Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 12:24:10 PM UTC.
No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.
Mentions over time
HN mentions by month4 dated mentions
Observed mentions: 2023-12-06 18:28:04 UTC to 2024-08-23 14:00:41 UTC.
Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.
View mention counts and date ranges
| Period | Start (UTC) | End (exclusive, UTC) | Mentions | Submissions | Comments |
|---|---|---|---|---|---|
| Dec 2023 | 2023-12-01 00:00:00 UTC | 2024-01-01 00:00:00 UTC | 2 | 1 | 1 |
| Jan 2024 | 2024-01-01 00:00:00 UTC | 2024-02-01 00:00:00 UTC | 0 | 0 | 0 |
| Feb 2024 | 2024-02-01 00:00:00 UTC | 2024-03-01 00:00:00 UTC | 0 | 0 | 0 |
| Mar 2024 | 2024-03-01 00:00:00 UTC | 2024-04-01 00:00:00 UTC | 0 | 0 | 0 |
| Apr 2024 | 2024-04-01 00:00:00 UTC | 2024-05-01 00:00:00 UTC | 0 | 0 | 0 |
| May 2024 | 2024-05-01 00:00:00 UTC | 2024-06-01 00:00:00 UTC | 1 | 0 | 1 |
| Jun 2024 | 2024-06-01 00:00:00 UTC | 2024-07-01 00:00:00 UTC | 0 | 0 | 0 |
| Jul 2024 | 2024-07-01 00:00:00 UTC | 2024-08-01 00:00:00 UTC | 0 | 0 | 0 |
| Aug 2024 | 2024-08-01 00:00:00 UTC | 2024-09-01 00:00:00 UTC | 1 | 1 | 0 |
What Hacker News says
4 sourcesIMO the big win for Elixir/Nx/Bumblebee/etc is that you can do batched distributed inference out of the box without deploying anything separate to your app or hitting an API. Massive complexity reduction and you can more easily scale up or down. https://hexdocs.pm/nx/Nx.Serving.html#content
And there's also a scale to 0 story for when you're not using that GPU at all: https://github.com/phoenixframework/flame
1 language/toolchain. 1 deployable app. Real time and distributed machine learning baked in. 1 dev can go really far.
In Elixir and Machine Learning in 2024 so far: MLIR, Arrow, structured LLM, etc.Probably not too much to say that’s specific to FLAME. Closures are serializable and can be sent as messages to actors on the BEAM with a few caveats.
From a quick look at the code, this looks the magic line: https://github.com/phoenixframework/flame/blob/main/lib/flam...
In Rethinking serverless with FLAMEFlame: Treat your entire application as a lambda
3 points · Open discussion