Credential-less pulls of public images. /auth/token issues a pull-only
token with an empty subject when no Basic auth is present; the
destination hold still enforces captain.Public, and push or delete always
challenges.
- token.IsPullOnlyScope and AuthMethodAnonymous;
Handler.issueAnonymousToken skips the authorizer gate and the
service-auth pre-mint, since there is no identity to reconcile and no
AppView-to-hold service token to bind. The token is still stamped
with the resolved registry domain, so anonymous pull works on
secondary front doors whose access controller demands their own
audience.
- auth.allow_anonymous_pull (default true) turns it fully off, restoring
the previous always-challenge behavior. Mirrored into the deploy
template, since the default means existing deploys pick this up.
- RegistryContext.Anonymous is plumbed from the middleware.
- ProxyBlobStore sends no Authorization header when the service token is
empty, and returns 401 rather than 403 for anonymous denials so Docker
prompts for credentials, including when a stale captain cache lets the
request through and the hold says private.
- BearerChallenge wraps the /v2/ subtree so a 401 raised deep in the
stack via errcode.ServeJSON still carries WWW-Authenticate.
Distribution's own scoped challenges are left alone.
IsPullOnlyScope allowlists the pull action instead of denylisting push and
delete. Distribution's actionSet.contains treats "*" as *every* action, so
a scope of `repository:victim/img:*` names neither denied string and would
have handed an unauthenticated caller a token valid for push and delete on
someone else's repository — clearing the authgate entirely, since anonymous
tokens deliberately skip it. Writes would still have failed further down
(no PDS credential), but the gate itself was bypassable. Now every
requested action must be exactly "pull". Covered by new claims tests.
Unresolvable identities return NAME_UNKNOWN instead of a bare error that
distribution renders as 500. This path was previously unreachable without
credentials; anonymous pull opens it to the internet, and a 5xx on
arbitrary input both misreports a bad request as a server fault and sends
clients that retry 5xx into a retry loop. That loop was real: in the auth
matrix, regclient spent 83s on a single case before this fix, and the
suite now runs in 5s.
Stat preserves an authorization verdict from getPresignedURL rather than
flattening it to ErrBlobUnknown. Distribution calls Stat before ServeBlob
on GET and HEAD, so without this an anonymous pull from a private hold
answered 404 and BearerChallenge had no 401 to annotate — the 401 path
above could never actually reach a client.
The auth matrix is updated to match: anonymous pull of the seeded public
repo now succeeds, anonymous push is denied against a real identity's
namespace (rather than an unresolvable one, which was testing name
resolution rather than authorization), and a new case pins the
NAME_UNKNOWN behavior for an unknown identity.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
ATCR UpCloud Deployment Guide
This guide walks you through deploying ATCR on UpCloud with Rocky Linux.
Architecture
- AppView (atcr.io) - OCI registry API + web UI
- Hold Service (hold01.atcr.io) - Presigned URL generator for blob storage
- Caddy - Reverse proxy with automatic HTTPS
- UpCloud Object Storage (blobs.atcr.io) - S3-compatible blob storage
Prerequisites
1. UpCloud Account
- Active UpCloud account
- Object Storage enabled
- Billing configured
2. Domain Names
You need three DNS records:
atcr.io(or your domain) - AppViewhold01.atcr.io- Hold serviceblobs.atcr.io- S3 storage (CNAME)
3. ATProto Account
- Bluesky/ATProto account
- Your DID (get from:
https://bsky.social/xrpc/com.atproto.identity.resolveHandle?handle=yourhandle.bsky.social)
4. UpCloud Object Storage Bucket
Create an S3 bucket in UpCloud Object Storage:
- Go to UpCloud Console → Storage → Object Storage
- Create new bucket (e.g.,
atcr-blobs) - Note the region (e.g.,
us-chi1) - Generate access credentials (Access Key ID + Secret)
- Note the endpoint (e.g.,
s3.us-chi1.upcloudobjects.com)
Deployment Steps
Step 1: Configure DNS
Set up DNS records (using Cloudflare or your DNS provider):
Type Name Value Proxy
────────────────────────────────────────────────────────────────────────────
A atcr.io [your-upcloud-ip] ☁️ DISABLED
A hold01.atcr.io [your-upcloud-ip] ☁️ DISABLED
CNAME blobs.atcr.io atcr-blobs.us-chi1.upcloudobjects.com ☁️ DISABLED
IMPORTANT:
- DISABLE Cloudflare proxy (gray cloud, not orange) for all three domains
- Proxied connections break Docker registry protocol and presigned URLs
- You'll still get HTTPS via Caddy's Let's Encrypt integration
Wait for DNS propagation (5-30 minutes). Verify with:
dig atcr.io
dig hold01.atcr.io
dig blobs.atcr.io
Step 2: Create UpCloud Server
- Go to UpCloud Console → Servers → Deploy a new server
- Select location (match your S3 region if possible)
- Select Rocky Linux 9 operating system
- Choose plan (minimum: 2 GB RAM, 1 CPU)
- Configure hostname:
atcr - Enable IPv4 public networking
- Optional: Enable IPv6
- User data: Paste contents of
deploy/init-upcloud.sh- Update
ATCR_REPOvariable with your git repository URL - Or leave empty and manually copy files later
- Update
- Create SSH key or use password authentication
- Click Deploy
Step 3: Wait for Initialization
The init script will:
- Update system packages (~2-5 minutes)
- Install Docker and Docker Compose
- Configure firewall
- Clone repository (if ATCR_REPO configured)
- Create systemd service
- Create helper scripts
Monitor progress:
# SSH into server
ssh root@[your-upcloud-ip]
# Check cloud-init logs
tail -f /var/log/cloud-init-output.log
Wait for the completion message in the logs.
Step 4: Configure Environment
Edit the environment configuration:
# SSH into server
ssh root@[your-upcloud-ip]
# Edit environment file
cd /opt/atcr
nano .env
Required configuration:
# Domains
APPVIEW_DOMAIN=atcr.io
HOLD_DOMAIN=hold01.atcr.io
# Your ATProto DID
HOLD_OWNER=did:plc:your-did-here
# UpCloud S3 credentials
AWS_ACCESS_KEY_ID=your-access-key-id
AWS_SECRET_ACCESS_KEY=your-secret-access-key
AWS_REGION=us-chi1
S3_BUCKET=atcr-blobs
# S3 endpoint (choose one):
# Option 1: Custom domain (recommended)
S3_ENDPOINT=https://blobs.atcr.io
# Option 2: Direct UpCloud endpoint
# S3_ENDPOINT=https://s3.us-chi1.upcloudobjects.com
# Public access (optional)
HOLD_PUBLIC=false # Set to true to allow anonymous pulls
Save and exit (Ctrl+X, Y, Enter).
Step 5: Start ATCR
# Start services
systemctl start atcr
# Check status
systemctl status atcr
# Verify containers are running
docker ps
You should see three containers:
atcr-caddyatcr-appviewatcr-hold
Step 6: Complete Hold OAuth Registration
The hold service needs to register itself with your PDS:
# Get OAuth URL from logs
/opt/atcr/get-hold-oauth.sh
Look for output like:
Visit this URL to authorize: https://bsky.social/oauth/authorize?...
- Copy the URL and open in your browser
- Log in with your ATProto account
- Authorize the hold service
- Return to terminal
The hold service will create records in your PDS:
io.atcr.hold- Hold definitionio.atcr.hold.crew- Your membership as captain
Verify registration:
docker logs atcr-hold | grep -i "success\|registered\|created"
Step 7: Test the Registry
Test 1: Check endpoints
# AppView (should return {})
curl https://atcr.io/v2/
# Hold service (should return {"status":"ok"})
curl https://hold01.atcr.io/health
Test 2: Configure Docker client
On your local machine:
# Install credential helper
# (Build from source or download release)
go install atcr.io/cmd/docker-credential-atcr@latest
# Configure Docker to use the credential helper
# Add to ~/.docker/config.json:
{
"credHelpers": {
"atcr.io": "atcr"
}
}
Test 3: Push a test image
# Tag an image
docker tag alpine:latest atcr.io/yourhandle/test:latest
# Push to ATCR
docker push atcr.io/yourhandle/test:latest
# Pull from ATCR
docker pull atcr.io/yourhandle/test:latest
Step 8: Monitor and Maintain
View logs
# All services
/opt/atcr/logs.sh
# Specific service
/opt/atcr/logs.sh atcr-appview
/opt/atcr/logs.sh atcr-hold
/opt/atcr/logs.sh atcr-caddy
# Or use docker directly
docker logs -f atcr-appview
Enable debug logging
Toggle debug logging at runtime without restarting the container:
# Enable debug logging (auto-reverts after 30 minutes)
docker kill -s SIGUSR1 atcr-appview
docker kill -s SIGUSR1 atcr-hold
# Manually disable before timeout
docker kill -s SIGUSR1 atcr-appview
When toggled, you'll see:
level=INFO msg="Log level changed" from=INFO to=DEBUG trigger=SIGUSR1 auto_revert_in=30m0s
Note: Despite the command name, docker kill -s SIGUSR1 does NOT stop the container. It sends a user-defined signal that the application handles to toggle debug mode.
Restart services
# Restart all
systemctl restart atcr
# Or use docker-compose
cd /opt/atcr
docker compose -f deploy/docker-compose.prod.yml restart
Rebuild after code changes
/opt/atcr/rebuild.sh
Update configuration
# Edit environment
nano /opt/atcr/.env
# Restart services
systemctl restart atcr
Architecture Details
Service Communication
Internet
↓
Caddy (443) ───────────┐
├─→ atcr-appview:5000 (Registry API + Web UI)
└─→ atcr-hold:8080 (Presigned URL generator)
↓
UpCloud S3 (blobs.atcr.io)
Data Flow: Push
1. docker push atcr.io/user/image:tag
2. AppView ← Docker client (manifest + blob metadata)
3. AppView → ATProto PDS (store manifest record)
4. Hold ← Docker client (request presigned URL)
5. Hold → UpCloud S3 API (generate presigned URL)
6. Hold → Docker client (return presigned URL)
7. UpCloud S3 ← Docker client (upload blob directly)
Data Flow: Pull
1. docker pull atcr.io/user/image:tag
2. AppView ← Docker client (get manifest)
3. AppView → ATProto PDS (fetch manifest record)
4. AppView → Docker client (return manifest with holdEndpoint)
5. Hold ← Docker client (request presigned URL)
6. Hold → UpCloud S3 API (generate presigned URL)
7. Hold → Docker client (return presigned URL)
8. UpCloud S3 ← Docker client (download blob directly)
Key insight: The hold service only generates presigned URLs. Actual data transfer happens directly between Docker clients and S3, minimizing bandwidth costs.
Troubleshooting
Issue: "Cannot connect to registry"
Check DNS:
dig atcr.io
dig hold01.atcr.io
Check Caddy logs:
docker logs atcr-caddy
Check firewall:
firewall-cmd --list-all
Issue: "Certificate errors"
Verify DNS is propagated:
curl -I https://atcr.io
Check Caddy is obtaining certificates:
docker logs atcr-caddy | grep -i certificate
Common causes:
- DNS not propagated (wait 30 minutes)
- Cloudflare proxy enabled (must be disabled)
- Port 80/443 blocked by firewall
Issue: "Presigned URLs fail"
Check S3 endpoint configuration:
docker exec atcr-hold env | grep S3
Verify custom domain CNAME:
dig blobs.atcr.io CNAME
Test S3 connectivity:
docker exec atcr-hold wget -O- https://blobs.atcr.io/
Common causes:
- Cloudflare proxy enabled on blobs.atcr.io
- S3_ENDPOINT misconfigured
- AWS credentials invalid
Issue: "Hold registration fails"
Check hold owner DID:
docker exec atcr-hold env | grep HOLD_OWNER
Verify OAuth flow:
/opt/atcr/get-hold-oauth.sh
Manual registration:
# Get fresh OAuth URL
docker restart atcr-hold
docker logs -f atcr-hold
Issue: "High bandwidth usage"
Presigned URLs should eliminate hold bandwidth. If seeing high usage:
Verify presigned URLs are enabled:
docker logs atcr-hold | grep -i presigned
Check S3 configuration:
docker exec atcr-hold env | grep S3_BUCKET
# Should show your S3 bucket name
Verify direct S3 access:
# Push should show 307 redirects in logs
docker logs -f atcr-hold
# Then push an image
Automatic Updates
# Install automatic updates
dnf install -y dnf-automatic
# Enable timer
systemctl enable --now dnf-automatic.timer
Monitoring
# Install monitoring tools
dnf install -y htop iotop nethogs
# Monitor resources
htop
# Monitor Docker
docker stats
Backups
Critical data to backup:
/opt/atcr/.env- Configuration- Docker volumes:
atcr-appview-data- Auth keys, UI database, OAuth tokenscaddy_data- TLS certificates
# Backup volumes
docker run --rm \
-v atcr-appview-data:/data \
-v /backup:/backup \
alpine tar czf /backup/atcr-appview-data.tar.gz /data
Scaling Considerations
Single Server (Current Setup)
- Suitable for: 100-1000 users
- Bottleneck: AppView CPU (manifest queries)
- Storage: Unlimited (S3)
Multi-Server (Future)
- Multiple AppView instances behind load balancer
- Shared Redis for hold cache (replace in-memory cache)
- PostgreSQL for UI database (replace SQLite)
- Multiple hold services (geo-distributed)
Support
- Documentation: https://tangled.org/evan.jarrett.net/at-container-registry
- Issues: https://tangled.org/evan.jarrett.net/at-container-registry/issues
- Bluesky: @evan.jarrett.net