Back to Home11/17/2025, 3:34:38 PM

Show HN: Bsub.io – zero-setup batch execution for command-line tools

1 points
0 comments

Mood

thoughtful

Sentiment

positive

Category

tech

Key topics

cloud computing

command-line tools

batch processing

I built bsub because I was tired of wiring up Docker images, Python environments, GPUs, sandboxing, and resource limits every time I needed to run heavy command-line tools from web apps. I wanted: send files -> run job in the cloud -> get output -> done.

https://www.bsub.io

bsub lets you execute tools like Whisper, Typst, Pandoc, Docling, and FFmpeg as remote batch jobs with no environment setup. You can try them locally via the CLI or integrate via a simple REST API.

Example (PDF extraction):

bsubio submit -w pdf/extract *.pdf

Works like running the tool locally, but the compute and isolation happen in the cloud.

### Technical details

- Each job runs in an isolated container with defined CPU/GPU/RAM limits. - Files are stored ephemerally for the duration of the job and deleted after completion. - REST API returns job status, logs, and results. - Cold start for light processors (Typst, Pandoc) is low; Whisper/FFmpeg take longer due to model load/encoding time. - Backend scales horizontally; more workers can be added during load spikes.

### Current processors

- SST/Whisper -- (speech-to-text) - Typography -- (Typst, Pandoc) - PDF extraction -- (Docling) - Video transcoding -- (FFmpeg)

More coming; suggestions welcome for tools that are painful to set up locally.

### Looking for testers - CLI is open source: https://github.com/bsubio/cli - Installers available for Linux/macOS; Windows testing is in progress. If you’re on Windows, feedback is especially helpful: contact@bsub.io - Free during early testing; pricing TBD.

If you try it, I’d appreciate feedback on API design, latency, missing processors, or anything rough around the edges.

The author introduces Bsub.io, a platform for executing command-line tools in the cloud without setup, and seeks feedback from the community.

Snapshot generated from the HN discussion

Discussion Activity

Light discussion

First comment

4h

Peak period

4

Hour 5

Avg / period

2.3

Comment distribution9 data points

Based on 9 loaded comments

Key moments

  1. 01Story posted

    11/17/2025, 3:34:38 PM

    1d ago

    Step 01
  2. 02First comment

    11/17/2025, 7:52:45 PM

    4h after posting

    Step 02
  3. 03Peak activity

    4 comments in Hour 5

    Hottest window of the conversation

    Step 03
  4. 04Latest activity

    11/19/2025, 1:30:49 AM

    8h ago

    Step 04

Generating AI Summary...

Analyzing up to 500 comments to identify key contributors and discussion patterns

Discussion (0 comments)

Discussion hasn't started yet.

ID: 45954472Type: storyLast synced: 11/17/2025, 3:36:05 PM

Want the full context?

Jump to the original sources

Read the primary article or dive into the live Hacker News thread when you're ready.