olares-chart

DevOps & Security

Use when deploying a repo, docker-compose, or generic Helm chart to your own Olares, packaging an Olares app image, authoring or validating an OlaresManifest, wiring storage / system middleware / entrances / env / GPU, or fixing a failed install (ImagePullBackOff, permission denied / EACCES, app won't start or won't reach running). Publishing to the public Olares Market is the olares-publish skill.

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How to use this skill

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Source SKILL.md: https://github.com/beclab/Olares/blob/HEAD/cli/skills/olares-chart/SKILL.md

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Deploy your code or any project to your Olares

Source of truth for flags is always olares-cli chart <verb> --help. This file only carries what --help cannot: the two coupled axes of a port, where to start on each, the per-axis concerns to get right, and the gotchas lint won't catch.

Porting baseline: Olares >= 1.12.6. Check the target with olares-cli profile list (VERSION column). Full version rules — apiVersion: v3, the chart version fields, the olares type: system dependency — are in references/olares-chart-versioning.md.

Platform model (read once, no login needed for authoring). Porting decisions rely on the Olares storage model, uid-1000 run identity, app/namespace & networking, system middleware, and version model — all defined once in ../olares-shared/references/olares-platform.md. Packaging an image and authoring/validating the chart need no login; only deploy to your Olares (market upload + install) does.

When to use

Turn a repo / docker-compose / generic Helm chart into an Olares app, or validate an OlaresManifest; package its image; wire storage / middleware / entrances / env / GPU
Deploy / run the app on your own Olares (market upload + install), or fix a failed install (ImagePullBackOff, EACCES, app won't start)
Serve a specific LLM / embedding model (HF or Ollama) with no chart authoring — clone an llm-init base app and fill env (llm-models.md); capability/context tuning + day-2 ops in llm-ops.md

Anything outside this scope -> see the Skill suite map in ../olares-shared/SKILL.md (already loaded as the suite prerequisite).

Mental model: this skill authors, validates, and deploys your own chart to your own Olares, and owns the fixes that mean editing your chart. Diagnosing a runtime failure (won't install / start, crashes, running but unreachable, image won't pull) is ../olares-doctor/SKILL.md — it finds the root cause and points back here for the chart edit. Listing / selling it on the public Olares Market is ../olares-publish/SKILL.md; installing or managing an already-published catalog app is ../olares-market/SKILL.md; inspecting pods/logs of an unrelated running app is ../olares-cluster/SKILL.md.

The shape of the work — two axes

Porting an app is not a fixed from-compose → lint → deploy pipeline — it is driving two orthogonal but coupled axes each to its own ready state, looping back as constraints surface (an image's baked-in uid/paths constrain the chart's mounts/permissions; a deploy constraint can send you back to rebuild the image). Start wherever your app already stands, not at a fixed step 1. Once both axes are ready, deploy to the current Olares — an automatic upload + install + diagnose loop.

Packaging — the image: the app built into a pullable, arch-correct artifact. Olares only pulls, never builds.
Deployment — the chart: a lint-passing OlaresManifest + templates. from-compose is only one way in.

First move (not a pipeline): locate where the app already sits on the packaging and deployment state tables → drive the concerns to ready, looping as constraints surface → deploy to your Olares.

Axis 1 — Packaging (the image)

Olares pulls images from a registry and never builds from source, so every workload must reference a publicly pullable, node-arch-correct image. Image work is agent-driven: ask which registry the developer uses (Docker Hub / ghcr), check docker is usable and logged in, then build + push yourself — only docker login stays manual, and only when not already authenticated (references/olares-chart-image.md). No Olares login needed. Build for this node's arch (single-arch); multi-arch is only for publishing.

Packaging state	Do this	Ready when
No Dockerfile (just source)	author a Dockerfile, then build+push	—
Dockerfile, but no pullable image	build+push (Docker Hub or ghcr)	—
A pullable image exists	check its arch; rebuild if it doesn't match this node (`olares-cli cluster node list`)	every workload has a pullable, arch-correct image

Axis 2 — Deployment (the chart)

The target is a lint-passing Olares chart. from-compose (kompose) is just one entry method — a bare repo, a generic Helm chart, or an already-Olares chart each begin elsewhere (see the state table below). Local authoring (from-compose / lint / package) needs no login.

Deployment state	Do this	Ready when
Source only (no compose)	author a docker-compose from the code (compose.md)	—
A docker-compose	`chart from-compose` then refine (from-compose.md)	—
A generic Helm chart (no OlaresManifest)	hand-author `OlaresManifest.yaml` + refine (skip `from-compose`)	—
Already an Olares chart	go straight to validation	a chart that passes `chart lint`

Deploy to your Olares (the done step)

Both axes ready → deploy to the current Olares automatically. lint proves the chart is structurally valid; it does not prove the app pulls its images, wires its middleware, and reaches running — the deploy loop does. After lint passes, proceed without asking: check login → package → market upload → market install -s upload --watch → on failure fetch logs → diagnose → fix chart + re-lint → retry. Only stop to ask when the profile fails olares-shared's auth-readiness gate (invalidated / never) — logged-in / expired both proceed. Full procedure: references/olares-chart-deploy.md.

For deploying to your own Olares, metadata can stay a stub as long as lint passes; functional refinement (storage / middleware / entrances) is still required.

The concerns to get right (reflect on these per axis)

from-compose produces a chart that lints but is not yet a good Olares app. These are the same concerns viewed two ways — what triggers them, what they let you do, and when they're done — collapsed into one row each. Drive each to "get this right", and loop back here when its trigger reappears.

Axis	Concern	Get this right	Loop back when	Reference
packaging	Image	pullable, pinned to a version tag (never `:latest`), arch-correct for this node	`ImagePullBackOff` / wrong arch, or a deploy constraint forces a rebuild	image.md
packaging+deployment	Run identity	uid 1000; `spec.runAsUser: true`; initContainer `chown` for root-owned volumes; no root main on non-trusted images (OPA)	EACCES on appData/appCache/userData; admission denies a root third-party image	run-as-user.md
deployment	Storage	every compose volume → the right userspace area (Data/Cache/Home/Common/External), matching `permission`, leftover kompose PVCs deleted	a volume isn't persisting or lands in the wrong area	manifest.md §2
deployment	Middleware & deps	no bundled `postgres`/`redis`/`mongo`/…; wire to system middleware; SQLite→Postgres where supported; companion apps as `type: application` deps	a bundled db/queue remains, or a companion should be a dependency	middleware.md
deployment	Env	app config in `envs[]` (v3 `valueFrom`, no inline `OLARES_USER`); install-time `required` prompts; middleware/system/user vars via `.Values.olaresEnv`; platform context via `.Values.*`	install fails on `appenv` 422, or config must be user-supplied	env.md, env-defaults.md, system-values.md
deployment	Entrances & ports	≥1 `entrances[]`; HTTP via entrances, non-HTTP via `ports[]`; internal-only services `invisible: true`	a service is unreachable, or an internal port is exposed as a desktop entrance	manifest.md §4
packaging+deployment	GPU / models	build a CUDA image without a local GPU; download model weights via initContainer into the shared `appCommon` Hugging Face cache	AI app needs a CUDA build, model provisioning, or a shared model cache	gpu.md
deployment	LLM model serving	serve any HF/Ollama model without authoring — pick an engine by format, fill env, clone an `llm-init` base app (llama.cpp / Ollama / vLLM / SGLang); set `MODEL_SUPPORTS` from the model card	user wants to run/serve a specific LLM or embedding model, not author a new app	llm-models.md + llm-ops.md
deployment	Accelerator	GPU/accelerator apps only: declare `spec.accelerator` modes per repo support; set `requiredGPUMemory`. A non-accelerator app needs no `mode` — use the flat `spec.requiredCpu/limitedCpu/requiredMemory/limitedMemory/requiredDisk` envelope (mutually exclusive with `spec.accelerator`)	app targets a GPU/accelerator device, or `lint` flags `spec.resources`	accelerator.md
packaging+deployment	DinD	a privileged `beclab/docker` daemon sidecar (`ENABLE_DIND`, `DOCKER_HOST`); main container stays non-privileged	a terminal/agent app must run `docker` / `docker compose`	dind.md
deployment	Shared backend	`options.shared: true` (on a v3 app) ⇒ admin-only install into `<app>-shared`; consumers reach it via cross-namespace Service DNS; flag the admin-install	a heavy/accelerator backend serves many users over shared data	shared.md
deployment	Version & deps fields	fixed values every chart writes: `apiVersion: v3`; `olaresManifest.version: '0.12.0'`; `metadata.version` == `Chart.yaml` `version`; `options.dependencies` includes `olares >=1.12.6-0` (`type: system`) — authored by you; bump `metadata.version` (= `Chart.yaml` `version`) on every (re)upload	every manifest edit — confirm these fields + the `olares` system dep (`lint` rejects a missing system dep); every (re)upload — bump the version first	versioning.md
deployment	Workloads / replicas	`workloadReplicas` lists every Deployment/StatefulSet → count (authored by you); each `spec.replicas` wired to `{{ .Values.workloads.<name>.replicaCount }}` + matching `values.yaml`	every time you author/add/rename a workload — run the three-point self-check; a hardcoded `replicas` silently no-ops suspend/resume / staged install	manifest.md Workloads & replicas
deployment	Metadata	stub OK for local deploy (`Utilities`, default icon) while `lint` passes; full `metadata.*` + listing images only when publishing	`lint` flags missing metadata, or you want a public listing	manifest.md §1
deployment	Validate-local	`olares-cli chart lint ./<app>` passes, then `chart package`	a refinement changed the manifest/templates	lint.md
deploy	Deploy	`market upload` + `market install`, then diagnose from logs — automatic after `lint` passes (login required)	proving the chart actually runs on the developer's Olares	deploy.md

Deploy leans on sibling skills: olares-shared (login check), olares-market (upload / install / cleanup), olares-cluster (logs), and olares-doctor (runtime root-cause diagnosis when a deploy fails or the app won't start). After lint passes, drive the deploy loop automatically without asking (proceed unless olares-shared's auth-readiness gate says stop); never log in on the developer's behalf without asking. One way to sequence the whole assembly (and the file tree from-compose emits) lives in references/olares-chart-workflow.md — a reference, not a required order.

CLI verbs

The only olares-cli chart subcommands (source of truth: --help). Everything else above is docker or sibling skills.

Verb	What it does	Reference
`from-compose` (alias `init`)	kompose-convert compose file(s) into an Olares chart skeleton	from-compose.md
`lint`	validate a chart dir / `.tgz` with the Market ingest pipeline	lint.md
`package`	package a chart dir into a `<name>-<version>.tgz` for upload (mirrors `helm package`, no helm binary needed)	workflow.md (D4)

Special porting patterns & official ports (beclab/apps)

Most of this skill assumes a web app with an HTTP entrance. When the upstream doesn't fit, match a known pattern first; if still unsure, see how the official ports solved it.

Headless CLI / service (no web UI) — no GUI to point an entrance at: add a web-terminal sidecar as a visible entrance + expose the API/MCP port as an invisible internal entrance. → archetype-headless.md
GUI desktop app (browser-streamed) — a native Linux desktop app with no web UI: wrap it in a web-desktop base image (Selkies default, or KasmVNC for old hardware/static UIs), point one visible window entrance at HTTP :3000, and device-gate optional iGPU/VAAPI acceleration on .Values.deviceName. → archetype-gui.md
Still no idea? look at how the official ports wire it (manifest fields, entrance shapes, middleware/app dependencies, GPU specs) in beclab/apps before guessing:

gh search code --repo beclab/apps <keyword>      # find charts using a pattern (e.g. type: application, accelerator, appCommon)
# then browse https://github.com/beclab/apps/tree/main/<app> — its OlaresManifest.yaml + templates/

This is the canonical source for cross-app wiring this skill intentionally does not hardcode.

When picking a reference app, skip these — they mislead more than they help:

Apps with a .suspend (or .remove) control file in the OAC root — suspended / no longer distributed; not a current, reliable pattern.
Shared / cluster-scoped charts that express sharing with spec.subCharts[].shared: true + options.appScope.clusterScoped: true + appRef (the ollamaserver/ollamav2 shape). Copy the shared-app pattern from an apiVersion: v3 app, not from these. See shared.md.

Gotchas (what `lint` won't catch)

lint validates structure, not Olares correctness. Beyond the concerns table above, these blind spots bite and are entirely on you:

metadata.name must match the chart folder and Chart.yaml name, and be ^[a-z][a-z0-9]{0,29}$. Keep metadata.appid equal to metadata.name (from-compose sets it; it backs the entrance domain <appid>.<zone>). Rename all four together. lint does NOT require metadata.appid — an empty value passes (the loader normalizes it to md5(metadata.name)[:8]), but market upload rejects a missing appid, so set it explicitly or a lint-clean chart still fails to upload.
Declared .Values.userspace.appData/appCache/userData mounts MUST have the matching permission field, or the app-data cross-check fails.
hostPath volumes + rolling updates are incompatible — replace host mounts with the userspace volumes above.
The entrance proxy caps every request at options.apiTimeout seconds (default 15s) — long LLM streams / big uploads / slow reports get cut at the entrance (504 / closed connection) even when the pod is healthy. Set options.apiTimeout: 0 to disable, or a large bounded value; a negative value is not "unlimited" (it falls back to 15s). See the Manifest refinement areas.