Skip to content

v0.3.1

Choose a tag to compare

@oren-openteams oren-openteams released this 19 Jun 14:48
· 11 commits to main since this release

v0.3.1

Opt-in organization CA bundle injection and automatic GPU scheduling tolerations. Both are no-ops for existing deployments — upgrading from v0.3.0 requires no changes to your values.

Highlights

🔐 Organization CA bundle injection (#16)

For clusters behind a TLS-inspecting proxy (Netskope, Zscaler, BlueCoat, internal corporate CAs), the chart can now inject an organization CA into the Ray head and worker pods so outbound HTTPS succeeds. Opt in by pointing orgCABundle.configMapName at a ConfigMap containing your root CA:

orgCABundle:
  configMapName: org-ca-bundle

When enabled, an initContainer builds a combined bundle (system trust + org CA) and the pods get SSL_CERT_FILE, REQUESTS_CA_BUNDLE, CURL_CA_BUNDLE, and GIT_SSL_CAINFO pointed at it — covering requests, urllib3, curl, pip, torch.hub, and git (incl. pip install git+https://…). When unset (the default), zero CA-related output is rendered — byte-identical to v0.3.0.

  • ⚠️ ArgoCD users: the README's example sync policy ignores /spec/rayClusterConfig, which silently drops the CA injection under server-side apply. See the "ArgoCD footgun" note in the README before enabling orgCABundle.
  • httpx caveat: httpx's default verify=True ignores SSL_CERT_FILE; app code must use verify=ssl.create_default_context(). Documented in the README.

🎮 Automatic GPU tolerations (#18)

GPU workloads (pods requesting nvidia.com/gpu) now get an nvidia.com/gpu toleration injected automatically, so they schedule onto tainted GPU nodes (e.g. NIC's auto-tainted AWS GPU node groups) without manual configuration. A user-supplied toleration for the same key is respected as an intentional override and not duplicated. Non-GPU pods are unaffected.

📚 Documentation site (#12)

Added a Docusaurus-based landing page / docs site for the pack, published to GitHub Pages.

Upgrade notes

No action required. All changes are opt-in or fire only for GPU workloads; existing values produce the same Ray deployment as v0.3.0.

Versioning

This is the first release under EffVer (effort-based versioning). Per EffVer's pre-1.0 guidance (0.MACRO.MICRO), a release that's a no-op for existing users is a micro bump → 0.3.0 → 0.3.1. The chart appVersion stays 2.43.0 (tracks Ray, not the pack).

What's changed

Full changelog: v0.3.0...v0.3.1