Show HN: Devbox – Containers for clean dev environments
Show HN (score: 5)Description
- Instant setup: `devbox init my-project` and you're in a fresh env with `devbox shell`.
- Configurable via JSON: Define packages, services, and more in a `devbox.json` file. Share it in your repo for reproducible setups—teammates just run `devbox up`.
- Docker-in-Docker by default: Build and run containers inside your env without extra config.
- Host-friendly: Edit code directly on your machine; the container handles the runtime.
- Templates for quick starts: Built-ins for Python, Node.js, Go, web dev, etc.
- Advanced options: Port mapping, env vars, resource limits, and even mounting your dotfiles.
It's FOSS (MIT license), Linux-focused (Debian/Ubuntu, or WSL2 on Windows), and super easy to install: `curl -fsSL https://devbox.ar0.eu/install.sh | bash`.
Check out the launch page and docs at https://devbox.ar0.eu, or the repo at https://github.com/itzCozi/devbox. I'd love some feedback, stars, or contributions to help grow this into a solid community tool!
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Show HN: KeyEnv – CLI-first secrets manager for dev teams (Rust) Hi HN,<p>I built KeyEnv because I was tired of the "can you Slack me the Stripe key?" workflow.<p><pre><code> The problem: My team's secrets lived in a mix of Slack DMs, shared Google Docs, and .env files that definitely weren't in .gitignore at some point. Enterprise tools like Vault required more DevOps time than we had. Doppler was close but felt heavier than we needed. What KeyEnv does: keyenv init # link project keyenv pull # sync secrets to local .env keyenv run -- npm start # inject secrets, run command That's basically it. Secrets are encrypted client-side (AES-256-GCM) before leaving your machine. Zero-knowledge architecture—we can't read your secrets even if we wanted to. Technical details: - Single Rust binary, no runtime dependencies - Works offline (cached secrets) - RBAC for teams (owner/admin/member/viewer) - Service tokens for CI/CD - Full audit trail Honest tradeoffs: - SaaS only, no self-hosted option - Fewer integrations than Doppler - If you need dynamic secrets or PKI, use Vault Pricing: Free tier (3 projects, 100 secrets), $12/user/month for teams. Would love feedback on the CLI UX and any rough edges. Happy to answer questions about the architecture. </code></pre> <a href="https://www.keyenv.dev" rel="nofollow">https://www.keyenv.dev</a>
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Show HN: On the edge of Apple Silicon memory speeds
Show HN: On the edge of Apple Silicon memory speeds I have developed open source CLI-tool for Apple Silicon macOS. It measures memory speeds in different ways and also latency. It can achieve up to 96-97% efficiency on read speed on M4 base what is advertised as 120GB/s. All memory operations are in assembly.<p>I would really appreciate for results on different CPU's how benchmark works on those. I have been able to test this on M1 and M4.<p>command : 'memory_benchmark -non-cacheable -count 5 -output results.JSON' (close all applications before running)<p>This will generate JSON file where you find sections copy_gb_s, read_gb_s and write_gb_s statics.<p>Example M4 with 10 loops: "copy_gb_s": { "statistics": { "average": 106.65421233311835, "max": 106.70240696071005, "median": 106.65069297260811, "min": 106.6336774994254, "p90": 106.66606919223108, "p95": 106.68423807647056, "p99": 106.69877318386216, "stddev": 0.01930653530818627 }, "values": [ 106.70240696071005, 106.66203166240008, 106.64410802226159, 106.65831409449595, 106.64148106986977, 106.6482935780762, 106.63974821679058, 106.65896986001393, 106.6336774994254, 106.65309236714002 ] }, "read_gb_s": { "statistics": { "average": 115.83111228356601, "max": 116.11098114619033, "median": 115.84480882265643, "min": 115.56959026587722, "p90": 115.99667266786554, "p95": 116.05382690702793, "p99": 116.09955029835784, "stddev": 0.1768243167963439 }, "values": [ 115.79154681380165, 115.56959026587722, 115.60574235736468, 115.72112860271632, 115.72147129262802, 115.89807083151123, 115.95527337086908, 115.95334642887214, 115.98397172582945, 116.11098114619033 ] }, "write_gb_s": { "statistics": { "average": 65.55966046805113, "max": 65.59040040480241, "median": 65.55933583741347, "min": 65.50911885624045, "p90": 65.5840272860955, "p95": 65.58721384544896, "p99": 65.58976309293172, "stddev": 0.02388146120866979 },<p>Patterns benchmark also shows bit more of memory speeds. command: 'memory_benchmark -patterns -non-cacheable -count 5 -output patterns.JSON'<p>Example M4 from 100 loops: "sequential_forward": { "bandwidth": { "read_gb_s": { "statistics": { "average": 116.38363691482549, "max": 116.61212708384109, "median": 116.41264548721367, "min": 115.449510036971, "p90": 116.54143114134801, "p95": 116.57314206456576, "p99": 116.60095068065866, "stddev": 0.17026641589059727 } } } }<p>"strided_4096": { "bandwidth": { "read_gb_s": { "statistics": { "average": 26.460392735220456, "max": 27.7722419653915, "median": 26.457051473208285, "min": 25.519925729459107, "p90": 27.105171215736604, "p95": 27.190715938337473, "p99": 27.360449534513144, "stddev": 0.4730857335572576 } } } }<p>"random": { "bandwidth": { "read_gb_s": { "statistics": { "average": 26.71367836895143, "max": 26.966820487564327, "median": 26.69907406197067, "min": 26.49374804466308, "p90": 26.845236287807374, "p95": 26.882004355057887, "p99": 26.95742242818151, "stddev": 0.09600564296001704 } } } }<p>Thank you for reading :)
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