# Execution Environment Integration - Research Summary

**Document Purpose:** Executive-level summary of research findings and design recommendations
**Date:** 2026-01-28
**Audience:** Project stakeholders, development team leads

---

## Research Overview

This research synthesized requirements for integrating execution environments into TraceRTM, evaluated technology options, and produced a comprehensive technical design. The focus was understanding:

1. How to safely execute CLI and browser automation in isolated environments
2. How to capture multimedia evidence (GIFs, videos, screenshots)
3. How to integrate AI agents (Codex CLI) for autonomous review tasks
4. How to maintain local-only storage without cloud dependencies
5. How to extend existing webhook infrastructure for execution triggers

---

## Key Findings

### 1. Technology Landscape Analysis

**VHS (CLI Recording):** charmbracelet/vhs is the clear winner for terminal recording
- Produces output directly as GIF/video (no player needed)
- Declarative .tape file format (reproducible, automatable)
- Active project with good maintenance
- Alternative (asciinema) produces text-only format requiring web player

**Playwright (Browser Automation):** Python-first implementation with native video support
- Built-in video recording (WebM), HAR (network), trace files (debugging)
- Active development, excellent debugging tools
- Superior to Selenium/Puppeteer for this use case

**FFmpeg (Video Processing):** Industry standard with excellent GIF output
- Palette optimization for high-quality GIFs
- Frame extraction, thumbnail generation, video composition
- Well-documented filters and effects

**Codex CLI Agent:** Purpose-built OpenAI agent tool
- Works with OAuth (not API keys)
- Can review images/videos and make decisions
- Built-in agent loop (vs raw API requiring framework)
- Natural fit for execution environment integration

### 2. Architecture Validation

**Docker Containers:** Best fit for local execution
- Access to codebase (mount volumes)
- Long-running task support (no timeout limits)
- Full tool ecosystem (can install VHS, FFmpeg, Playwright)
- Existing project experience (docker-compose.test.yml)
- Local-only (no cloud dependency)

**OAuth Over API Keys:** Superior security model
- Reuses existing GitHub OAuth infrastructure
- Token rotation via refresh tokens
- Scope-based access control
- Audit trail from OAuth provider

**Event-Driven via Webhooks:** Matches existing patterns
- WebhookIntegration model already established
- Real-time triggering (no polling overhead)
- Integrates with external CI/CD systems
- Audit trail via integration_sync_logs

**SQLite + Local Filesystem:** Appropriate for local deployment
- Zero external dependencies
- Simple backup/restore
- Sufficient for typical usage
- Configurable retention policies prevent disk bloat

### 3. Security Architecture

**Defense in Depth:**

| Layer | Implementation |
|-------|--------|
| Authentication | OAuth credentials (no API keys stored in config) |
| Authorization | Per-project execution ACLs via write permissions |
| Validation | Webhook signature verification (HMAC-SHA256) |
| Isolation | Docker sandbox (read-only FS, non-root user) |
| Secrets | AES-256 encryption at rest, never logged |
| Auditing | All executions logged, agent interactions recorded |

**Risk Mitigation:**
- Container escape: read-only root filesystem, no privileged capabilities
- Credential exposure: secrets only injected to containers, encrypted in DB
- Authorization bypass: signature verification before processing
- Data exfiltration: network isolation, no external volume mounts
- DoS: rate limiting, timeout enforcement, resource limits

### 4. Data Model Insights

**Central Models:**
- `Execution`: Orchestration record (status, timing, logs)
- `ExecutionArtifact`: Binary artifact metadata (GIFs, videos, screenshots)
- `CodexAgentInteraction`: Agent task history and decisions
- `ExecutionEnvironmentConfig`: Project-specific settings

**Integration Points:**
- Extends `WebhookIntegration` (triggers)
- Extends `IntegrationCredential` (OAuth tokens)
- Links to `IntegrationSyncLog` (audit trail)
- Relates to `Project` (execution context)

### 5. Implementation Feasibility

**Estimated Effort by Phase:**

| Phase | Duration | Complexity | Dependencies |
|-------|----------|-----------|--------------|
| 1: Schema & Core Services | 2 weeks | Moderate | None |
| 2: Docker Integration | 2 weeks | High | Phase 1 |
| 3: VHS Integration | 2 weeks | Moderate | Phase 2 |
| 4: Playwright Integration | 2 weeks | Moderate | Phase 2 |
| 5: Codex Agent Integration | 2 weeks | High | Phase 1, 4 |
| 6: Webhook Triggers | 2 weeks | Moderate | Phase 1, 2 |
| 7: Security Hardening | 2 weeks | High | Phase 1-6 |
| 8: Performance Optimization | 2 weeks | Moderate | Phase 1-7 |

**Total: 16 weeks (4 months)**

### 6. Scalability Considerations

**Current Design Limits:**
- Single machine deployment
- Docker daemon local connection
- SQLite write contention (eventual)
- Artifact filesystem (~1TB typical)

**Growth Path:**
- Phase 1 (Years 1-2): 1000s of executions/day per machine
- Phase 2: Distributed queue, multiple execution hosts
- Phase 3: Pluggable storage (S3, GCS), distributed coordination

**No blocking issues at current scale**

### 7. User Experience Insights

**Key Interactions:**
1. **Trigger Point:** Webhook from CI/CD, UI button, or scheduled
2. **Queuing:** Execution created, user gets immediate feedback
3. **Progress:** Real-time WebSocket updates (status, logs, artifacts)
4. **Results:** Browsable artifacts (GIFs play directly, videos embedded)
5. **History:** Searchable execution history with filtering

**Design Principle:** Transparent, real-time feedback with artifact artifacts

---

## Recommendations

### Immediate Actions (Week 1)

1. **Validate Technology Choices**
   - Install VHS locally, test .tape generation
   - Verify FFmpeg GIF output quality
   - Confirm Codex CLI OAuth flow works

2. **Align with Team**
   - Present architecture decisions to team
   - Gather feedback on Phase 1 database schema
   - Identify any blocking concerns

3. **Prepare Infrastructure**
   - Create Dockerfile.executor template
   - Set up Docker layer caching
   - Document Docker resource requirements

### Implementation Strategy

1. **Start with Phase 1:** Database schema, core services
   - Low risk (data models only)
   - Highest value (foundation for all phases)
   - Enables parallel development

2. **Parallelize Phases 3-4:** VHS and Playwright
   - Independent implementations
   - Both generate artifacts
   - Can test simultaneously

3. **Delay Phase 5 (Codex):** Wait for Phases 2-4 stable
   - Highest complexity
   - Depends on artifact storage
   - Can be added incrementally

4. **Integrate Phase 6 Early:** Webhook triggers
   - Demonstrates real-world usage
   - Validates data flow
   - Provides testing mechanism

### Risk Mitigation

| Risk | Likelihood | Impact | Mitigation |
|------|-----------|--------|-----------|
| Docker daemon unavailable | Low | High | Document setup, health checks |
| FFmpeg GIF quality issues | Low | Medium | Pre-test with real videos |
| Container resource limits exceeded | Medium | High | Monitoring, configurable limits |
| Artifact disk fills quickly | Medium | Medium | Implement cleanup policies early |
| OAuth token refresh fails | Low | High | Retry logic, alerting |
| Codex agent produces invalid actions | Medium | Medium | Action whitelist, validation |
| WebSocket connection drops | Low | Medium | Reconnect logic, state persistence |

### Success Criteria

**Technical:**
- [ ] Phase 1 complete with 90%+ test coverage
- [ ] VHS recordings produce valid GIFs
- [ ] FFmpeg conversions < 10s for typical videos
- [ ] Docker containers start in < 5s
- [ ] Webhook signature validation passes security audit

**Operational:**
- [ ] Documentation complete for all services
- [ ] Runbook for common issues
- [ ] Monitoring dashboards deployed
- [ ] Artifact cleanup working for 30+ days

**User:**
- [ ] End-to-end execution flow works (webhook → artifacts)
- [ ] Real-time progress updates via WebSocket
- [ ] Artifacts easily accessible via API and UI
- [ ] Existing webhook users can opt-in without changes

---

## Competitive Landscape

### Similar Systems

**GitHub Actions:**
- Pros: Runs in GitHub, integrates seamlessly
- Cons: Limited to GitHub ecosystem, no local control
- Comparison: Ours is complementary (local, VHS/Playwright specific)

**CI/CD Platforms (CircleCI, Travis):**
- Pros: Managed execution, scaling
- Cons: Requires paid tier, cloud-dependent
- Comparison: Ours is self-hosted, local-only

**Execution Environments (Docker Cloud, Kubernetes):**
- Pros: Distributed, scalable
- Cons: Complex setup, operational overhead
- Comparison: Start simple (single Docker), can scale later

**Media Capture (Playwright, Puppeteer):**
- Pros: Existing tools for browser automation
- Cons: Not integrated into traceability system
- Comparison: Ours integrates into execution framework

**AI Agents (OpenAI, Anthropic):**
- Pros: Powerful models, multi-modal
- Cons: Cloud-based, API key exposure
- Comparison: Ours uses OAuth, local execution control

---

## Learning Resources

### VHS Documentation
- [charmbracelet/vhs GitHub](https://github.com/charmbracelet/vhs)
- Tape file format reference
- Example recordings

### Playwright Documentation
- [Playwright Python Docs](https://playwright.dev/python/)
- Video/trace recording guides
- Browser context management

### FFmpeg
- [FFmpeg Documentation](https://ffmpeg.org/documentation.html)
- GIF encoding best practices
- Video filtering reference

### Docker Security
- [Docker Security Best Practices](https://cheatsheetseries.owasp.org/cheatsheets/Docker_Security_Cheat_Sheet.html)
- Read-only filesystem configuration
- User privilege limitation

---

## Open Questions & Future Exploration

### 1. Codex CLI Availability
**Question:** How widely available is Codex CLI? Is it compatible with GitHub OAuth?

**Next Step:** Contact OpenAI/Anthropic to validate availability and OAuth support

### 2. Performance Under Load
**Question:** How many concurrent executions can single Docker daemon handle?

**Next Step:** Load testing with Phase 2, determine scale limits

### 3. Artifact Storage Growth
**Question:** At what scale does SQLite become a bottleneck?

**Next Step:** Monitor in production, plan Phase 2 migration if needed

### 4. Agent Action Safety
**Question:** How to safely execute autonomous agent actions?

**Next Step:** Design action whitelist and validation framework in Phase 5

### 5. Cross-Platform Compatibility
**Question:** Does this work on macOS/Windows (not just Linux)?

**Next Step:** Test Docker setup on macOS (Docker Desktop), document platform requirements

---

## Conclusion

The execution environment integration is **technically feasible**, **architecturally sound**, and **strategically valuable** for TraceRTM. Key advantages:

1. **Local-First:** No cloud dependencies, full control
2. **Extensible:** Pluggable coordinators for different execution types
3. **Secure:** Defense-in-depth, OAuth-based, encrypted secrets
4. **Observable:** Full audit trail, multimedia artifacts
5. **Pragmatic:** Phased approach, incremental value delivery

The proposed 16-week implementation plan balances risk (start simple) with value (deliver fast). The architecture supports current needs and scales for future growth.

**Recommendation:** Proceed with Phase 1 (database schema and core services) immediately to validate assumptions and get quick wins.

---

## Document References

1. **EXECUTION_ENVIRONMENT_INTEGRATION_DESIGN.md** - Comprehensive technical design
2. **EXECUTION_ENVIRONMENT_ARCHITECTURE_DECISIONS.md** - Detailed ADRs with rationales
3. **EXECUTION_ENVIRONMENT_QUICK_REFERENCE.md** - Developer reference guide

---

## Appendix: Technology Evaluation Matrix

### VHS Evaluation

| Criterion | Score | Reasoning |
|-----------|-------|-----------|
| Output Quality | 9/10 | Pixel-perfect GIFs with FFmpeg backend |
| Ease of Use | 8/10 | .tape files declarative but need generation logic |
| Community Support | 8/10 | Active project, good docs, responsive maintainers |
| Performance | 9/10 | Efficient encoding, reasonable file sizes |
| Flexibility | 7/10 | Limited to terminal recording, not general-purpose |
| **Overall** | **8.2/10** | **Excellent choice for CLI recording** |

### Playwright Evaluation

| Criterion | Score | Reasoning |
|-----------|-------|-----------|
| Output Quality | 9/10 | Video, screenshots, traces, HAR files |
| Python Support | 10/10 | First-class Python async support |
| Debugging Tools | 10/10 | Trace files, visual debugging, inspector |
| Performance | 9/10 | Fast execution, efficient resource usage |
| Flexibility | 9/10 | Multiple browsers, headless/headed modes |
| **Overall** | **9.4/10** | **Best-in-class browser automation** |

### FFmpeg Evaluation

| Criterion | Score | Reasoning |
|-----------|-------|-----------|
| GIF Quality | 10/10 | Palette optimization, excellent output |
| Performance | 9/10 | Highly optimized, fast conversions |
| Flexibility | 10/10 | 100+ filters, endless possibilities |
| Ease of Use | 7/10 | CLI-based, learning curve but well-documented |
| Community | 10/10 | Mature project, 20+ years, tons of resources |
| **Overall** | **9.2/10** | **Industry standard, no alternatives** |

### OAuth vs Alternatives Evaluation

| Criterion | OAuth | API Keys | PAT | Basic Auth |
|-----------|-------|----------|-----|-----------|
| Security | 10/10 | 4/10 | 7/10 | 2/10 |
| Revocation | 10/10 | 5/10 | 5/10 | 8/10 |
| Scope Control | 9/10 | 5/10 | 6/10 | 2/10 |
| Existing Pattern | 10/10 | 5/10 | 5/10 | 3/10 |
| **Overall** | **9.75/10** | **4.75/10** | **5.75/10** | **3.75/10** |
| **Choice** | ✅ | ❌ | ❌ | ❌ |

---

## Glossary

- **VHS:** charmbracelet/vhs - CLI recording tool
- **FFmpeg:** Video processing Swiss Army knife
- **Playwright:** Browser automation framework
- **Codex CLI:** OpenAI's agent tool with OAuth support
- **Execution Environment:** Isolated Docker container for task execution
- **Artifact:** Generated output (GIF, video, screenshot, log)
- **OAuth Token:** Credential from GitHub allowing API access
- **HMAC:** Hash-based Message Authentication Code (signature verification)
- **WebSocket:** Real-time bidirectional communication protocol
- **ADR:** Architecture Decision Record

