Instructions for setting up local cpu + gpu visibility
Nobody has claimed this yet.
Assessment
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Newbie friendliness
- 38/100
- Issue type
- Documentation
- Clarity
- Mostly clear
- Activity status
- Stale
- Tech stack
- django, docker, shell
- Domain
- devops, documentation, observability, security
Research direction
Start by reading the repository’s admin documentation and the referenced comment on pull request #39 to find the existing local setup instructions and decide what is in scope. Document how to launch containers for OpenTelemetry logs, metrics, and traces, whether GPU metrics need special setup, and how to configure Caddy for secure access to Django admin or staff accounts. Done means the install and launch flow covers those topics; the issue names no files or tests.
Written by the indexing model from the issue text.
Description
Show install & launch flow:
- show how to launch local containers for visualizing otel: logs, metrics, traces
- show how to include GPU metrics as part of that if anything special
- for secure web use, show how to configure Caddyfile for web forward for django admin or staff level accounts
A separate issue can be for documenting how to use
Split off from comment https://github.com/graphistry/graphistry-cli/pull/39#issuecomment-2125981596
- Dominant language
- Shell
- Stars
- 31
- Forks
- 6
- PR merge metrics
- No merged PRs in 30d
Getting set up
This project ships no dev container, Dockerfile or contributing guide, so setting up is up to you: start from its README, and see our first-contribution guide for the general steps.
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
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