embeddenator 0.20.0-alpha.1

Sparse ternary VSA holographic computing substrate
# ARM64 Test Results

## TASK-004 Execution Report - 2026-01-01

### Phase 1: Runner Health Check ❌ INCOMPLETE

**Test Date:** 2026-01-01 04:05 UTC  
**Executor:** Integration Specialist Agent  
**Repository:** tzervas/embeddenator

#### Runner Status
```
Total Runners Registered: 0
ARM64 Runners Online: 0
Status: NO RUNNERS CONFIGURED
```

**API Check Results:**
- GitHub API endpoint: `/repos/tzervas/embeddenator/actions/runners`
- Response: Empty (total_count: 0)
- Authentication: ✅ Verified (gh CLI authenticated as tzervas)
- Repository Access: ✅ Confirmed
- Workflow Detection: ✅ ARM64 workflow found (ID: 220132581)

#### Workflow Configuration Verified

**Workflow Name:** Build and Push ARM64 Images (Self-Hosted)  
**Workflow Path:** .github/workflows/build-push-arm64.yml  
**Workflow ID:** 220132581  
**State:** active  
**Created:** 2026-01-01 22:01:20  
**Trigger:** workflow_dispatch (manual only)

**Workflow Configuration:**
- Supports multiple runner types: `multi`, `large`, `native`
- Default labels required: `["self-hosted", "linux", "ARM64"]`
- Optional large runner labels: `["self-hosted", "linux", "ARM64", "large"]`
- Includes test suite validation (24 tests expected)
- Supports Docker image building and pushing to GHCR

### Phase 2: Manual Workflow Trigger ❌ BLOCKED

**Status:** Cannot proceed - no runners available  
**Blocker:** Zero self-hosted ARM64 runners registered

**Command Prepared (not executed):**
```bash
gh workflow run build-push-arm64.yml \
  --field os_selections="debian-stable-arm64" \
  --field tag_suffix="-test" \
  --field push_to_ghcr=false \
  --field run_tests=true \
  --field runner_type="multi"
```

### Phase 3: Validate Artifacts ❌ NOT STARTED

Cannot validate artifacts without successful workflow execution.

### Phase 4: Document Results ✅ COMPLETED

This document serves as the comprehensive status report.

---

## Runner Setup Required

### Available Runner Management Tools

The project includes comprehensive runner automation:

**Tool Location:** `runner_manager.py` (project root)  
**Documentation:** `docs/RUNNER_AUTOMATION.md`

**Quick Setup Commands:**
```bash
# 1. Configure environment
cp .env.example .env
# Edit .env to set GITHUB_REPOSITORY and GITHUB_TOKEN

# 2. One-command setup (register + start + monitor)
python3 runner_manager.py run

# 3. Or step-by-step
python3 runner_manager.py register
python3 runner_manager.py start
python3 runner_manager.py monitor
```

**Runner Configuration Options:**

1. **Multi-Runner Setup** (Recommended for ARM64)
   - 4 runners with 4 cores, 6GB RAM each
   - Labels: `self-hosted, linux, ARM64`
   - Distributes builds automatically

2. **Large Single Runner**
   - 10 cores, 16GB RAM, 100GB disk
   - Labels: `self-hosted, linux, ARM64, large`
   - Parallel builds with max-parallel: 4

3. **Native ARM64 Hardware**
   - AWS Graviton, Raspberry Pi, Apple Silicon (via Docker)
   - Best performance, no emulation overhead

4. **QEMU Emulation** (fallback)
   - x86_64 host with QEMU ARM64 emulation
   - Slower but functional for testing

### Prerequisites for Runner Setup

**Required:**
- GitHub Personal Access Token with `repo` scope
- Python 3.7+ with packages: requests, python-dotenv
- Docker (for containerized runners)
- 50-100GB disk space per runner
- Network connectivity to github.com

**ARM64 Specific:**
- Native ARM64 hardware OR
- QEMU user-mode emulation on x86_64 host

---

## Blocker Analysis

### Root Cause
No self-hosted runners are currently registered with the repository. The ARM64 workflow is properly configured but requires self-hosted infrastructure.

### Impact
- ❌ Cannot test ARM64 builds
- ❌ Cannot validate workflow configuration
- ❌ TASK-005 (auto-trigger enablement) blocked
- ❌ Multi-architecture container builds unavailable

### Resolution Path

**Option A: Quick Test with Emulation (Development)**
```bash
# On x86_64 host with Docker
python3 runner_manager.py run --runner-count 1 \
  --labels "self-hosted,linux,ARM64" \
  --emulation qemu
```

**Option B: Production ARM64 Deployment**
```bash
# On native ARM64 host (AWS Graviton, etc.)
export GITHUB_REPOSITORY=tzervas/embeddenator
export GITHUB_TOKEN=ghp_your_token_here
python3 runner_manager.py run --runner-count 4 \
  --labels "self-hosted,linux,ARM64" \
  --runner-mode auto
```

**Option C: Hybrid Multi-Arch**
- Deploy AMD64 runners for primary CI
- Deploy ARM64 runners for cross-platform validation
- Use matrix builds to test both architectures

---

## Go/No-Go Recommendation for TASK-005

### Status: 🔴 NO-GO

**Recommendation:** DO NOT enable auto-trigger on main branch until ARM64 runners are deployed and validated.

**Rationale:**
1. Zero runners available - workflow will fail immediately
2. No validation of workflow functionality completed
3. Risk of blocking main branch CI if auto-triggered without infrastructure
4. Could prevent merges if required status checks configured

### Prerequisites for TASK-005:
1. ✅ Workflow file created and pushed (completed)
2. ❌ At least 1 ARM64 runner online and healthy (blocked)
3. ❌ Successful manual workflow execution (blocked)
4. ❌ Test suite validation on ARM64 (blocked)
5. ❌ Docker image build verification (blocked)

### Next Actions Required:

**Immediate (Blocks TASK-005):**
1. Deploy at least 1 self-hosted ARM64 runner using runner_manager.py
2. Execute manual workflow trigger to validate configuration
3. Verify all 24 tests pass on ARM64 architecture
4. Confirm Docker images build successfully
5. Re-run TASK-004 with runners active

**Post-Validation:**
1. Document actual test results in this file
2. Performance comparison with AMD64 runners
3. Update workflow with any platform-specific fixes
4. Enable auto-trigger on main branch (TASK-005)

---

## Additional Findings

### Workflow Ecosystem Status

**Total Workflows in Repository:** 10
- ✅ CI Pre-Checks (active)
- ✅ CI amd64 Build and Test (active)
- ✅ CI arm64 Build and Test (active)
- ✅ Build and Push ARM64 Images (active) ⚠️ needs runners
- ✅ Build and Push Holographic OS Images (active)
- ✅ Nightly Holographic OS Builds (active)
- ✅ Build Holographic OS Containers (active)

**Recommendation:** Consider runner capacity for multiple workflows

### Infrastructure Cost Estimation

**Self-Hosted ARM64 Options:**

1. **AWS EC2 t4g.medium (2 vCPU, 4GB RAM)**
   - Cost: ~$0.0336/hour = ~$24/month
   - Suitable for: Single runner, light workloads

2. **AWS EC2 t4g.xlarge (4 vCPU, 16GB RAM)**
   - Cost: ~$0.1344/hour = ~$96/month
   - Suitable for: Multi-runner or heavy builds

3. **Oracle Cloud ARM (Ampere A1)**
   - Cost: FREE tier (4 vCPU, 24GB RAM)
   - Best value for experimentation

4. **On-Premises / Raspberry Pi**
   - One-time hardware cost
   - Zero ongoing runner costs

---

## Test Execution Results

### Status: AWAITING RUNNER DEPLOYMENT

*This section will be populated after runners are configured and manual workflow execution completes.*

**Expected Test Matrix:**
- Unit Tests: TBD
- Integration Tests: TBD
- E2E Tests: TBD
- Doc Tests: TBD
- Total Tests: 24 expected

**Performance Metrics:** TBD
**Architecture Validation:** TBD
**Docker Images:** TBD

---

## Summary

**TASK-004 Status:** ⚠️ PARTIALLY COMPLETE  
**Phase 1:** ✅ Complete (runner status documented)  
**Phase 2-3:** ❌ Blocked (no runners available)  
**Phase 4:** ✅ Complete (comprehensive documentation)

**Critical Path:** Deploy ARM64 runner → Execute workflow → Validate results → Approve TASK-005

**Estimated Time to Unblock:** 1-2 hours (runner deployment + first test run)

---

*Report generated by Integration Specialist Agent on 2026-01-01*
4. **Caching:** Implement build caching to reduce build times

## Future Considerations

- **macOS ARM64:** Apple Silicon runners for full multi-platform coverage
- **GPU Runners:** For future GPU-accelerated VSA operations
- **Container Builds:** ARM64 container image building and testing

## Test Logs

```
running 14 tests
test test_vsaconfig_new ... ok
test test_vsaconfig_presets ... ok
... (all tests passed)
```

## Conclusion

ARM64 CI pipeline is operational and all tests pass. Ready for production use with auto-triggering enabled.