https://blog.cloudflare.com/vertical-microfrontends/ analyze
Cloudflare’s post describes a “vertical microfrontends” (VMFE) pattern implemented on Workers: independent frontends per URL segment, stitched into a single, SPA‑like UX using an edge router plus HTML rewriting, view transitions, and speculation rules.1
Core idea
- Each path (or path prefix) like
/,/docs,/dash,/dash/product-ais a fully independent frontend: its own repo, framework, CI/CD, and Cloudflare Worker.1 - A dedicated “Router Worker” is bound to the domain and routes requests to the correct Worker using service bindings based on path prefix rules.1
- The router also post‑processes HTML responses (via
HTMLRewriter) and injects cross‑VMFE UX enhancements (CSS view transitions, speculation prefetch).1
Routing and isolation model
wrangler.toml(for the Router Worker) definesservices(service bindings) that point to each vertical microfrontend Worker, e.g.HOME,DOCS,DASH.1- A
ROUTESvariable (JSON) maps path prefixes to those bindings, e.g./→HOME,/docs→DOCS,/dash→DASH; the Router strips the prefix before forwarding to preserve each Worker’s own standalone URL semantics.1 - Each team owns its entire stack for that route: framework choice, deployment pipeline, dependencies, and release cadence, avoiding cross‑team regressions in a monolithic front‑end.1
UX unification techniques
- CSS View Transitions: the router can inject CSS so that specific DOM elements (notably
nav) persist and animate between full page loads, making cross‑Worker navigation feel SPA‑like instead of showing white flashes.1 - Speculation Rules API: the router can inject a
<script type="speculationrules">block to prefetch other VMFE URLs into in‑memory cache, making subsequent navigations nearly instant in Chromium‑based browsers.1 - These features can be toggled via
ROUTESconfig:smoothTransitions: trueat the root to enable transitions globally, andpreload: trueper route to emit speculation rules for that path.1
HTML rewriting and asset paths
- Because the
/docsor/dashprefixes exist only at the Router level, raw HTML from a child Worker that uses relative or root‑based paths would break when proxied.1 - The Router uses
HTMLRewriterto adjust asset URLs and links, e.g. rewriting./logo.pngto./docs/logo.pngwhen serving under/docs, ensuring assets and navigation work both via the Router and via the service’s own direct URL.1 - The same HTML rewriting pass is used to inject the view transition CSS and speculation rules without requiring each team to manually add them.1
Architectural implications and usage
- This is a vertical microfrontend pattern (split by URL slice, not page fragment) contrasting with “horizontal” MFEs where components within a page come from different services.1
- It targets scenarios where multiple teams (marketing, docs, dashboard, per‑product dashboards) need high autonomy while still presenting a cohesive app under one domain.1
- Cloudflare ships a ready‑made “Vertical Microfrontend” Worker template: from the dashboard, you choose “Workers & Pages → Create application → Select a template → Create microfrontend”, then map existing Workers and enable view transitions via configuration.1
If you tell me your target stack (e.g. React dashboard on /dash, Astro marketing on /, Docs on /docs) and how you deploy today, I can draft a focused Router Worker skeleton and a migration plan prompt you can reuse.
r2 sandboxes explain
Cloudflare “R2 sandboxes” is essentially the pattern of using the Sandbox SDK with R2 (or other S3‑compatible storage) mounted into each sandbox’s filesystem for persistent state per isolated compute environment.23
What a sandbox is
- A sandbox is an isolated execution environment (VM‑backed container) created and managed via the Sandbox SDK (
getSandbox(id)), with its own filesystem, processes, network stack, and enforced CPU/mem/disk quotas.45 - Sandboxes are identified by a sandbox ID; using the same ID across requests reuses the same environment until it is destroyed or times out, which is how you get “sticky” compute per user/session/tenant.46
How R2 fits in
- The SDK exposes
mountBucket()to mount any S3‑compatible bucket (R2, S3, GCS, etc.) into the sandbox filesystem at a path like/dataor/storage.37 - With R2 as provider (
provider: 'r2'), you get provider‑specific optimizations (e.g. flags likenomixupload) and zero‑egress when used inside Cloudflare, which makes it the recommended persistent backing store for sandboxes.37
Persistence model
- Data written to the sandbox’s local filesystem (unmounted paths) is ephemeral and disappears when the sandbox is destroyed; data written under a mounted R2 path persists because it actually lives in R2.23
- Typical pattern: mount a bucket (optionally with a
prefixlike/sessions/user123) and treat it as a per‑sandbox or per‑tenant home directory, using standard file operations (open,cat, etc.) while R2 handles durability.23
Isolation and tenancy
- Each sandbox runs in a separate VM, so sandboxes cannot see each other’s files, processes, or network, giving strong tenant isolation at the compute layer.5
- Within R2, isolation is usually done by bucket‑per‑tenant or by prefixes (
prefix: '/sessions/user123'), so that even if multiple sandboxes share a bucket, you still have per‑tenant logical separation.3 - Best‑practice guidance: use separate sandboxes per user/tenant for strong isolation and mount R2 in read‑only mode where possible, elevating to read‑write only where needed.57
Typical architecture for “R2 sandboxes”
- A Worker or platform backend calls
getSandbox(userId)(or similar key) to spin up/attach to a sandbox and then mounts an R2 bucket under/datausing Worker secrets for credentials.423 - Your app then executes untrusted code or tools in that sandbox (
sandbox.exec,sandbox.writeFile,sandbox.readFile) while relying on R2‑backed paths for any state that must outlive the sandbox lifecycle.423
If you describe your target model (per‑user code execution, per‑project notebooks, multi‑tenant SaaS, etc.), I can draft a concrete “R2‑backed sandbox” design and a minimal Worker + Sandbox SDK + R2 config you can paste into your stack.
explain how ephemeral containers with r2 gcs and git could provide a fast start to an llm cloud based ide and act persistent?
You can treat the container as disposable “compute cache” and use R2/GCS + git as the persistent substrate so the IDE feels instant while all real state lives outside the container.171819
High-level pattern
- Ephemeral containers (or sandboxes) start quickly with a thin base image and no baked-in project state; they’re cheap to destroy and recreate.1720
- Persistent resources live in:
- On startup, the container mounts or syncs from these stores, so the environment appears stateful even though the container itself is not.1819
Startup sequence for a “fast” LLM IDE
For a per-user or per-project ephemeral container:
- Resolve session: map user/session →
sandboxIdor similar key. - Mount persistent storage:
- Bootstrap workspace:
- If
/persist/projects/$projectId/.gitexists,git fetch/git pullinto a working dir in the ephemeral FS (e.g./workspace). - If not,
git clonetemplate repo into/workspace, then rsync (or copy) to/persist/projects/$projectIdto seed persistent state.
- If
- Warm LLM tooling:
- Restore cached models, embeddings, indexes, and tool metadata from
/persist/cache/...so the agent starts “warm” instead of recomputing.18
- Restore cached models, embeddings, indexes, and tool metadata from
- Attach IDE front-end:
- Cloud IDE (WebSocket) connects to the container’s
/workspace, but writes are periodically or continuously synced back to/persist(or directly operate on the mounted path if performance is sufficient).
- Cloud IDE (WebSocket) connects to the container’s
The perceived effect: user hits “Open in cloud IDE”, and a new pod/sandbox comes up with code, history, and LSP/LLM context already there.
How persistence actually works
- Container filesystem:
- Fast, local, but ephemeral. Destroying the pod/sandbox wipes it.
- Mounted object storage:
- Git:
- Holds the versioned code; typically you don’t mount git, you clone/fetch into the ephemeral FS, then persist the working tree in R2/GCS to avoid full clones on every cold start.
A concrete pattern is: “R2 as home directory”, “git as upstream”, “ephemeral container as compute”.
Acting “persistent” across sessions
- Identity mapping:
- Use a stable key (user, org, project) to choose the R2/GCS prefix and git remote; every new container for that key mounts the same bucket prefix.19
- Rehydration:
- On container start, sync
/persist→/workspace, restore terminals, install dependencies from cachednode_modules/venvin/persist/cache, and re-open last files from a JSON state file.
- On container start, sync
- Garbage collection:
How this benefits an LLM‑first IDE
- Fast “project open”: no cold pull from remote git and no model re-index; those live in R2/GCS and are just re-mounted.1718
- Safer multi-tenant story: each user/org gets its own bucket or strict prefix; each request gets its own ephemeral container/sandbox, with R2/GCS as the only shared infra boundary.2119
- LLM tooling can treat
/workspaceas durable: logs, prompts, vector indexes, and diagnostics get synced to/persist, so agents can reconstruct context even when the backing container has been replaced.
If you want, I can draft a minimal spec/prompt for “ephemeral sandbox LLM IDE” with: API surface (openProject, resumeSession), storage layout in R2/GCS, and git fetch strategy tuned for your target languages.
could I run a Linux micro kernel in a cloudflare ephemeral instance with Claude code?
You cannot boot and manage your own Linux microkernel inside a Cloudflare Worker/Sandbox in the sense of “run a nested kernel,” but you can run arbitrary Linux user‑space binaries (including a microkernel-like userspace OS or a minimal shell environment) in an isolated VM/container that you control from a Worker, and then drive it with Claude Code. 333435
What Cloudflare actually gives you
- Workers: JavaScript/TypeScript runtime on top of V8; no raw containers or kernels, only user‑space code within Cloudflare’s sandboxed engine. 36
- Sandbox SDK: an API from a Worker to spin up “sandboxes,” each of which is an isolated Linux container running in its own VM, where you can run commands, manage files, and expose HTTP services. 333437
- Containers: the newer “Cloudflare Containers” product lets you deploy Docker‑style images and control them via Workers/Durable Objects; each container is a Linux userspace environment managed by Cloudflare’s orchestration. 3835
In all of these, the host Linux kernel is provided by Cloudflare; you don’t boot your own kernel image.
What you can do with a “micro kernel” idea
- Build a minimal Linux userspace image (e.g., BusyBox + your toolchain) and deploy it as a Cloudflare Container; from a Worker, you use
env.MY_CONTAINER.get(id)or a Sandbox SDK binding to start/stop containers per user/session. 3839 - Within that container, you can run a very small “micro‑OS” process tree (shell, editors, LSP, language runtimes) and expose an HTTP or TCP endpoint that the IDE/Claude Code talks to for compilation, tests, tools, etc. 333735
- For untrusted code execution, you rely on Cloudflare’s VM‑per‑sandbox isolation and syscall restrictions (seccomp‑style) rather than running your own microkernel for isolation. 3440
So your “micro kernel” in practice is a tiny Linux userspace plus your supervisor process, not an actual guest kernel image.
How Claude Code would interact
- Claude Code (or your own LLM agent) calls a Worker endpoint like
POST /sessions/:id/exec, which: - The VM/container filesystem can be wired to persistent storage (R2/S3/GCS via Sandbox SDK
mountBucket()or container volume mounts) so user projects survive container restarts, giving the illusion of a long‑lived dev machine. 41424335
From Claude Code’s perspective, it’s “a remote Linux box per session with a filesystem and tools,” even though it’s ephemeral under the hood.
Direct answer to your “micro kernel” question
- No: you cannot boot a custom Linux microkernel (e.g., your own
bzImage) inside a Worker or Sandbox; the kernel is Cloudflare’s and not under your control. 333635 - Yes: you can deploy a minimal Linux container image that behaves like a micro‑kernel-ish environment (very small userspace, single supervising process), run it as an ephemeral sandbox/container per session, and have Claude Code orchestrate it via Workers/Durable Objects. 33393835
If you tell me your target constraints (languages, max RAM/CPU per session, need for Docker‑in‑Docker or not), I can draft a precise “Claude‑driven Cloudflare container sandbox” spec and a Worker skeleton you can plug into your IDE backend.
could the users home directory be r2/gcs?
Yes. You can make a user’s “home directory” effectively live in R2 or GCS by mounting a bucket (or prefix) into the sandbox/container filesystem at /home/$USER or similar and treating that as the canonical home. 515253
In Cloudflare sandboxes
- Sandbox SDK exposes
mountBucket(bucket, mountPath, options)to mount any S3‑compatible storage (R2, GCS via S3 API, S3, B2) as a local directory. 5152 - You can mount per‑user prefixes, for example:
bucket = "ide-home",mountPath = "/home/user",options.prefix = "users/${userId}", so/home/userbecomes the user’s persistent home. 515254 - Files written there survive sandbox destruction and are accessible from any future sandbox that mounts the same bucket+prefix. 5455
In Cloudflare Containers
- Containers support mounting R2 buckets via FUSE (e.g., tigrisfs, s3fs) so the bucket appears as a filesystem path. 5356
- The recommended pattern is to mount the bucket at a path like
/mnt/r2and then either:- set
$HOME=/mnt/r2/users/$USER, or - bind‑mount
/mnt/r2/users/$USERto/home/$USERinside the container’s startup script. 53
- set
- R2 credentials are passed as env vars or Worker secrets, and you can mount read‑only or read‑write depending on whether the “home” is mutable. 5357
GCS variant
- For GCS, you can either use its S3‑compatible endpoint with
mountBucket()in sandboxes, or usegcsfusein a container similarly to the R2 FUSE example. 515258 - Same idea: per‑user prefixes in a single bucket, or bucket‑per‑tenant, mapped to
/home/$USER. 58
Practical implication for your LLM IDE
- Every ephemeral IDE container/sandbox mounts
homefrom R2/GCS, so shells, editors, history, and config files (dotfiles, tool state, agent caches) all live in object storage and persist across sessions. 54515953 - You keep images extremely thin (no baked user state) and still get a stable, POSIX‑looking
$HOMEper user or per project. 605161
If you want a concrete snippet, I can draft: “Worker + Sandbox SDK: per‑user /home as R2 prefix” or “Containers Dockerfile + entrypoint with R2 FUSE mount and $HOME override.”
draft: “Worker + Sandbox SDK: per‑user /home as R2 prefix” or “Containers Dockerfile + entrypoint with R2 FUSE mount and $HOME override.”
Below are two focused drafts you can paste and iterate on: one for a Worker + Sandbox SDK using per‑user /home on R2, and one for Containers using a Dockerfile + entrypoint with an R2 FUSE mount and $HOME override.6667686970
1) Worker + Sandbox SDK: per‑user /home as R2 prefix
Goal: From a Worker, create/reuse a sandbox per user, mount an R2 bucket prefix as /home/user, and run commands that see this as $HOME.
// wrangler.toml (or wrangler.jsonc)
name = "ide-backend"
main = "src/worker.ts"
compatibility_date = "2026-01-31"
[vars]
R2_ENDPOINT = "https://<ACCOUNT_ID>.r2.cloudflarestorage.com"
R2_BUCKET = "ide-home"
[env.production.vars]
# Optional: different bucket/prefix per env
[secrets]
// R2_ACCESS_KEY_ID
// R2_SECRET_ACCESS_KEY
// SANDBOX_API_TOKEN (if required by Sandbox SDK)
// src/worker.ts
import { SandboxClient } from "@cloudflare/sandbox-sdk"; // placeholder name
// Check actual import in docs. [web:2][web:5]
export interface Env {
R2_ENDPOINT: string;
R2_BUCKET: string;
R2_ACCESS_KEY_ID: string;
R2_SECRET_ACCESS_KEY: string;
// Any Sandbox-related bindings/tokens
}
export default {
async fetch(req: Request, env: Env, ctx: ExecutionContext): Promise<Response> {
const url = new URL(req.url);
if (url.pathname === "/exec") {
const userId = url.searchParams.get("user") ?? "anon";
const cmd = url.searchParams.get("cmd") ?? "ls -la";
const sandboxId = `user-${userId}`; // stable id → persistent home [web:4]
const client = new SandboxClient({
// config from env / binding
});
// Create or reuse sandbox for this user/session
const sandbox = await client.getSandbox(sandboxId);
// Mount R2 prefix as /home/user
await sandbox.mountBucket(env.R2_BUCKET, "/home/user", {
endpoint: env.R2_ENDPOINT,
accessKeyId: env.R2_ACCESS_KEY_ID,
secretAccessKey: env.R2_SECRET_ACCESS_KEY,
// optional: per-user prefix in a shared bucket
prefix: `users/${userId}/`,
// example flags: cache, read-only, etc. [web:9]
flags: ["use_cache=/tmp/cache"],
});
// Set HOME for this command
const result = await sandbox.exec({
cmd: ["/bin/bash", "-lc", cmd],
env: {
HOME: "/home/user",
},
timeoutMs: 30_000,
});
return new Response(result.stdout + result.stderr, {
status: 200,
headers: { "content-type": "text/plain" },
});
}
return new Response("Not found", { status: 404 });
},
};
Key behaviors:
sandboxIdis stable per user so the same sandbox can be reused; the R2 mount gives a persistent home that survives sandbox destruction anyway.6871mountBucket()exposes a specific R2 bucket/prefix as/home/user, and$HOMEis set accordingly. 6667- You can add
prewarmcommands to install tools or sync git into/home/useron first use.
Prompt you can reuse:
“Given this Worker + Sandbox SDK skeleton that mounts an R2 prefix as
/home/user, extend it to: (1) support multiple projects per user under/home/user/projects/:id, (2) run language servers and attach over WebSocket, and (3) implement a simpleopenProject/execHTTP API for an LLM IDE backend.”
2) Containers: Dockerfile + entrypoint with R2 FUSE mount and $HOME override
Goal: Build a Cloudflare Container image that mounts an R2 bucket with FUSE (tigrisfs/s3fs) at /mnt/r2, binds /mnt/r2/users/$USER to /home/$USER, and starts your IDE agent or shell.6970
# Dockerfile
FROM debian:stable-slim
RUN apt-get update && \
apt-get install -y ca-certificates fuse3 curl && \
rm -rf /var/lib/apt/lists/*
# Install tigrisfs (S3-compatible FUSE adapter) or s3fs; see docs. [web:43]
RUN curl -L https://github.com/tigrisdata/tigrisfs/releases/download/v0.5.0/tigrisfs-x86_64 \
-o /usr/local/bin/tigrisfs && \
chmod +x /usr/local/bin/tigrisfs
# Create non-root user
RUN useradd -m -s /bin/bash dev
# Copy entrypoint
COPY entrypoint.sh /entrypoint.sh
RUN chmod +x /entrypoint.sh
USER root
ENTRYPOINT ["/entrypoint.sh"]
CMD ["bash"]
# entrypoint.sh
#!/usr/bin/env bash
set -euo pipefail
: "${R2_ACCOUNT_ID:?R2_ACCOUNT_ID is required}"
: "${R2_BUCKET_NAME:?R2_BUCKET_NAME is required}"
: "${AWS_ACCESS_KEY_ID:?AWS_ACCESS_KEY_ID is required}"
: "${AWS_SECRET_ACCESS_KEY:?AWS_SECRET_ACCESS_KEY is required}"
: "${CF_USER_ID:=anon}" # passed from Worker / DO for per-user home
MOUNT_POINT="/mnt/r2"
USER_NAME="dev"
USER_HOME="/home/${USER_NAME}"
USER_PREFIX="users/${CF_USER_ID}"
mkdir -p "${MOUNT_POINT}"
# Mount R2 bucket with FUSE (tigrisfs example) [web:43]
tigrisfs \
--endpoint "https://${R2_ACCOUNT_ID}.r2.cloudflarestorage.com" \
--bucket "${R2_BUCKET_NAME}" \
--mount-point "${MOUNT_POINT}" \
--access-key "${AWS_ACCESS_KEY_ID}" \
--secret-key "${AWS_SECRET_ACCESS_KEY}" \
--foreground=false &
# Wait briefly for mount to come up (you may want a proper health check)
sleep 2
# Prepare per-user home in the mounted bucket
mkdir -p "${MOUNT_POINT}/${USER_PREFIX}"
# Bind-mount user prefix to /home/dev if allowed in environment
# (Cloudflare Containers expose FUSE and allow bind mounts per docs.) [web:43][web:47]
mount --bind "${MOUNT_POINT}/${USER_PREFIX}" "${USER_HOME}"
# Switch to dev user with HOME pointing at the mounted path
export HOME="${USER_HOME}"
chown -R "${USER_NAME}:${USER_NAME}" "${USER_HOME}"
echo "Mounted R2 bucket ${R2_BUCKET_NAME}/${USER_PREFIX} as ${HOME}"
# Exec the requested command as dev (e.g., shell, IDE agent)
exec su - "${USER_NAME}" -c "$*"
Worker/DO side (sketch):
- Configure Container with env vars:
R2_ACCOUNT_ID,R2_BUCKET_NAME, and pass per‑userCF_USER_IDviaenvVarswhen you start the container instance. 6970 - Your Worker handles
POST /sessions→ starts/reuses a container withCF_USER_ID, then proxies IDE/Claude traffic (WS/HTTP) to it.
Prompt you can reuse:
“Given this Dockerfile and entrypoint for mounting an R2 bucket as
/home/devinside a Cloudflare Container, extend it to: (1) support both R2 and GCS (switchable via env), (2) mount a per-project prefix under the same user, and (3) run an LSP + code-execution sidecar for an LLM IDE, exposing a simple HTTP API.”
If you specify your preferred FUSE adapter (tigrisfs vs s3fs vs gcsfuse) and languages (Node, Python, Go, etc.), I can tighten these drafts to exactly match your toolchain.
gcsfuse and languages (Node, rust python venv
Yes, you can use GCS via gcsfuse and still have a good DX for Node, Rust, and Python (venv) as long as you treat GCS as the backing store for $HOME or /workspace and keep language‑specific caches there.828384
Below is a focused draft integrating gcsfuse with those runtimes.
Dockerfile with gcsfuse + Node + Rust + Python
FROM debian:stable-slim
# Base deps
RUN apt-get update && \
apt-get install -y \
ca-certificates curl gnupg lsb-release fuse3 \
build-essential git python3 python3-venv python3-pip \
nodejs npm \
pkg-config libssl-dev \
&& rm -rf /var/lib/apt/lists/*
# Install Rust (rustup)
RUN curl https://sh.rustup.rs -sSf | sh -s -- -y
ENV PATH="/root/.cargo/bin:${PATH}"
# Install gcsfuse (Cloud Storage FUSE) [web:59][web:65]
RUN echo "deb http://packages.cloud.google.com/apt gcsfuse-$(lsb_release -c -s) main" \
| tee /etc/apt/sources.list.d/gcsfuse.list && \
curl https://packages.cloud.google.com/apt/doc/apt-key.gpg | apt-key add - && \
apt-get update && \
apt-get install -y gcsfuse && \
rm -rf /var/lib/apt/lists/*
# Non-root dev user
RUN useradd -m -s /bin/bash dev
USER root
COPY entrypoint.sh /entrypoint.sh
RUN chmod +x /entrypoint.sh
ENTRYPOINT ["/entrypoint.sh"]
CMD ["bash"]
entrypoint.sh with gcsfuse and per-user GCS home
#!/usr/bin/env bash
set -euo pipefail
: "${GCS_BUCKET:?GCS_BUCKET is required}"
: "${GOOGLE_APPLICATION_CREDENTIALS:?GOOGLE_APPLICATION_CREDENTIALS is required}"
: "${CF_USER_ID:=anon}"
MNT="/mnt/gcs"
USER_NAME="dev"
USER_HOME="/home/${USER_NAME}"
USER_PREFIX="users/${CF_USER_ID}"
# Ensure /etc/fuse.conf allows non-root access if you use allow_other [web:67]
if ! grep -q "user_allow_other" /etc/fuse.conf 2>/dev/null; then
echo "user_allow_other" >> /etc/fuse.conf
fi
mkdir -p "${MNT}"
chown root:root "${MNT}"
# Mount bucket via gcsfuse in foreground & background it [web:60][web:58]
# You need FUSE privileges in the container runtime. [web:61][web:70]
gcsfuse \
--foreground \
--key-file "${GOOGLE_APPLICATION_CREDENTIALS}" \
-o allow_other \
"${GCS_BUCKET}" "${MNT}" &
# Wait briefly; in a real setup, check mount availability
sleep 2
# Create per-user prefix
mkdir -p "${MNT}/${USER_PREFIX}"
chown -R "${USER_NAME}:${USER_NAME}" "${MNT}/${USER_PREFIX}"
# Bind GCS prefix to /home/dev
mount --bind "${MNT}/${USER_PREFIX}" "${USER_HOME}"
chown -R "${USER_NAME}:${USER_NAME}" "${USER_HOME}"
export HOME="${USER_HOME}"
# Language-specific layout under HOME
# $HOME/.cache/node, $HOME/.npm
# $HOME/.cache/pip, $HOME/.venvs
# $HOME/.cargo, $HOME/.rustup
su - "${USER_NAME}" <<'EOF'
mkdir -p "$HOME/.cache/node" "$HOME/.npm" \
"$HOME/.cache/pip" "$HOME/.venvs" \
"$HOME/.cargo" "$HOME/.rustup"
EOF
echo "Mounted GCS bucket ${GCS_BUCKET}/${USER_PREFIX} as ${HOME}"
# Exec the requested command as dev (Node, Rust, Python, etc.)
exec su - "${USER_NAME}" -c "$*"
You must run this container with FUSE privileges (or use whatever capabilities Cloudflare’s container runtime exposes for gcsfuse).838586
Using Node, Rust, and Python venv with this layout
Inside the container (as dev user):
- Node:
cd "$HOME/projects/my-node-app"
npm install # caches go under $HOME/.npm and node_modules in project
npm test
These artifacts persist in GCS via the mount.
- Rust:
cd "$HOME/projects/my-rust-app"
cargo build # uses $HOME/.cargo and $HOME/.rustup (also on GCS)
- Python venv:
cd "$HOME/projects/my-py-app"
python3 -m venv "$HOME/.venvs/my-py-app"
source "$HOME/.venvs/my-py-app/bin/activate"
pip install -r requirements.txt # packages cached in GCS-backed HOME
All user and tool state lives under $HOME, so when the container is recreated and gcsfuse remounts the same users/$CF_USER_ID prefix, the environment “comes back to life” with deps, venv, cargo cache, etc. already there.8287
If you want, next step I can draft a precise prompt like:
“Design a multi-tenant LLM IDE where each ephemeral container mounts a per-user GCS prefix via gcsfuse as
$HOME, supporting Node, Rust, and Python venv, and define the HTTP API (openProject,exec,listFiles) a Worker/DO uses to orchestrate it.”
which you can feed directly into your orchestration/agent layer.
draft a precise prompt like:“Design a multi-tenant LLM IDE where each ephemeral container mounts a per-user GCS prefix via gcsfuse as $HOME, supporting Node, Rust, and Python venv, and define the HTTP API (openProject, exec, listFiles) a Worker/DO uses to orchestrate it.”which you can feed directly into your orchestration/agent layer.
Design a multi-tenant LLM-first cloud IDE architecture with the following constraints and goals:
- High-level objective
- The system should provide per-user, ephemeral Linux containers that feel like persistent development machines.
- Each container must support Node.js, Rust, and Python (with per-project virtual environments).
- The IDE is driven by LLM agents (e.g., Claude Code) that call backend HTTP APIs to manage sessions, run commands, and inspect the filesystem.
- Storage and persistence model (GCS + gcsfuse)
- Treat Google Cloud Storage (GCS) as the canonical persistent backing store for user state.
- Use
gcsfuse(or Cloud Storage FUSE) to mount a per-user GCS prefix as the container’s$HOME. - Requirements:
- Bucket structure:
gs://<BUCKET>/users/{userId}/...holds that user’s entire home directory (projects, dotfiles, caches, venvs, cargo/npm/pip caches, etc.). - On container start, mount
gs://<BUCKET>with gcsfuse, then bind-mountusers/{userId}to/home/devand setHOME=/home/dev. - Ensure FUSE permissions allow non-root user access; design for running tools as a non-root
devuser.
- Bucket structure:
- Persistence expectations:
- All mutations under
$HOMEsurvive container termination and are visible in future sessions for the sameuserId. - Container images must be stateless beyond base tooling; all user-specific artifacts live under
$HOME.
- All mutations under
- Runtime environments (Node, Rust, Python)
- Node.js:
- Preinstall a recent Node and npm (or pnpm/yarn) in the base image.
- Use
$HOME/.npmand per-projectnode_modulesunder$HOME/projects/{projectId}; both persist via the GCS mount.
- Rust:
- Install Rust via
rustupin the base image. - Ensure
$HOME/.cargoand$HOME/.rustuplive on the mounted home so toolchains and caches persist.
- Install Rust via
- Python:
- Provide system
python3andpython3-venvin the base image. - For each project, create venvs under
$HOME/.venvs/{projectId}and store pip caches under$HOME/.cache/pip.
- Provide system
- Describe how the first container startup for a user/project performs any one-time initialization (e.g., cloning a template repo, creating default venv, installing baseline deps), and how subsequent starts reuse that state.
- Node.js:
- Ephemeral container lifecycle
- Model: per-user or per-(user,project) container instances that may be:
- Created on demand (
openProject), - Reused across multiple
execcalls in a session, - Automatically stopped after inactivity.
- Created on demand (
- Define:
- How containers are named/identified (e.g.,
sessionId,userId:projectId). - How long they live (idle timeout, max lifetime).
- What happens if a container is gone when an API call comes in (transparent recreation with the same GCS-backed home).
- How containers are named/identified (e.g.,
- Emphasize that containers are always safe to destroy; persistence is entirely via GCS.
- Model: per-user or per-(user,project) container instances that may be:
- Security and multi-tenancy
- Isolation:
- Each user must see only their own home directory.
- Bucket layout and application logic must prevent path traversal across users (e.g., strictly prefix-scoped mounts or checks).
- Credentials:
- Describe how the containers obtain GCS credentials (e.g., Workload Identity / service accounts / injected key files) and how scope is restricted.
- Resource limits:
- Per-container CPU/memory limits appropriate for ephemeral LLM-driven IDE sessions.
- Any per-user limits (max concurrent sessions, disk usage quotas enforced at the GCS prefix level).
- Isolation:
- HTTP API definition (Worker / Durable Object as orchestrator)
- The orchestrator (e.g., Worker or Durable Object) is the only component exposed to the IDE/LLM agents. Containers are never directly exposed.
- Define the following HTTP endpoints precisely (include request/response JSON schemas, typical status codes, and idempotency semantics):
a) POST /openProject
- Purpose: create or resume a container session for a given (userId, projectId).
- Request body fields:
- userId (string, required)
- projectId (string, required)
- languagePreferences (optional: Node/Rust/Python info, e.g., default runtime, tool versions)
- initialRepo (optional: git URL and ref for first-time project creation)
- Behavior:
- Resolve or create a sessionId.
- Start or reuse a container bound to that user/project with GCS home mounted.
- Optionally perform first-time bootstrap if no project directory exists.
- Response body:
- sessionId (string)
- status (e.g., "starting" | "ready")
- projectPath (e.g., "/home/dev/projects/{projectId}")
- metadata (language runtimes available, environment info).
b) POST /exec
- Purpose: execute a shell command or language-specific command within the container for a given session.
- Request body fields:
- sessionId (string, required)
- cwd (string, optional, default to project root)
- cmd (array of strings for argv or single shell string; specify which)
- env (object of env vars to merge on top of defaults)
- timeoutMs (integer, optional; execution timeout)
- stream (boolean, if true, use SSE or WebSocket instead of single response).
- Behavior:
- If container is not running, transparently recreate it and remount the same GCS-backed home before executing.
- Run the command as the non-root dev user with HOME pointing to the mounted directory.
- Response body (for non-streaming mode):
- exitCode (integer)
- stdout (string, possibly truncated, plus guidelines for pagination or logs)
- stderr (string)
- durationMs (integer).
- For streaming mode, specify the SSE/WebSocket message format.
c) GET /listFiles
- Purpose: list files in a directory within the project/home for a given session (used by IDE/LLM to inspect workspace).
- Query params or body fields:
- sessionId (string, required)
- path (string, required; path relative to $HOME or explicit absolute path inside the container, with clear constraints).
- Behavior:
- Perform a safe directory listing (no following of symlinks outside $HOME, no access above the home root).
- Response body:
- entries: array of objects with
- name (string),
- path (string relative to $HOME or project root),
- type ("file" | "dir" | "symlink"),
- size (integer, optional),
- modifiedAt (timestamp, optional).
- Optionally define additional endpoints like GET /readFile, PUT /writeFile, and POST /closeSession, with clear semantics for concurrency and conflict resolution (e.g., last-write-wins, ETags).
7. Integration with LLM/IDE layer
- Describe how an LLM agent (Claude Code) would use this API:
- Call openProject when a user opens a workspace.
- Use listFiles, readFile, and writeFile to browse and edit code.
- Use exec for running tests, builds, linters, or language servers (or to start long-lived background processes that the IDE connects to).
- Clarify how the orchestrator enforces per-user authorization (e.g., JWT with sub=userId, mapping to allowed sessionIds and GCS prefixes).
- Explain how telemetry and logs are captured for observability (per-session metrics, exec stats, errors).
8. Deliverables
- A clear, prose architecture description covering the above points.
- Example JSON request/response payloads for openProject, exec, and listFiles.
- A brief note on how to extend this design to support additional languages/runtimes later without breaking existing API contracts.
Use precise, implementation-oriented language suitable for a senior platform/infra engineer. Focus on clarity of contracts, lifecycle, and security isolation so this spec can directly feed into agentic orchestration and low-level implementation.