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title: DevOps Assessment - Executive Summary
type: note
permalink: assessments/dev-ops-assessment-executive-summary
tags:

- devops
- executive-summary
- assessment
- roadmap

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# DevOps/Infrastructure Assessment - Executive Summary

**Status:** CRITICAL GAPS IDENTIFIED - Roadmap feasible with infrastructure investment

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## Bottom Line

**Current Infrastructure (v0.28.0):** 3/10 readiness for roadmap

- CLI tool with batch processing: ✓ Working well
- Real-time service: ✗ Not ready
- Multi-sport platform: ✗ No infrastructure

**Roadmap Tasks 1-2 (Weeks 1-2):** READY - No infrastructure changes needed
**Roadmap Task 3 (Weeks 3-6):** BLOCKED - Requires infrastructure build
**Roadmap Tasks 4-5 (Weeks 5-7):** PARTIALLY READY - Scaling concerns

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## Critical Issues

### 1. NO CONTAINERIZATION (CRITICAL)

- Current: CLI runs locally
- Required: Docker image for real-time service
- **Action:** Build Dockerfile Week 1-2 (estimated 3-5 days)
- **Impact:** Blocks all deployment/scaling work

### 2. NO DEPLOYMENT PIPELINE (CRITICAL)

- Current: Manual CLI installs
- Required: Automated staging + production deployment
- **Action:** Build CI/CD for containers Week 2-3 (estimated 5-7 days)
- **Impact:** Can't push to production without this

### 3. NO LOAD/PERFORMANCE TESTING (HIGH)

- Current: Unit tests only (261 tests, all unit/integration)
- Required: Concurrent load tests, latency profiling
- **Action:** Add Locust + benchmarking Week 1 (estimated 3-4 days)
- **Impact:** Unknown if \<200ms latency achievable

### 4. NO MONITORING/OBSERVABILITY (HIGH)

- Current: Zero metrics collected
- Required: Prometheus + Grafana for real-time tracking
- **Action:** Add monitoring infrastructure Week 2-3 (estimated 5 days)
- **Impact:** Blind in production, can't detect issues

### 5. LATENCY RISK - UNVALIDATED (HIGH)

- Target: \<200ms end-to-end for real-time coaching
- Unknown: If MediaPipe + streaming meets this
- **Action:** Performance testing in Week 1 of Task 3 (MANDATORY)
- **Decision Point:** If latency >250ms, must pivot architecture

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## Infrastructure Gaps by Task

| Task         | Gap                                          | Severity | Timeline | Impact                  |
| ------------ | -------------------------------------------- | -------- | -------- | ----------------------- |
| 1: Ankle fix | None                                         | -        | 2-3 days | ✓ Can start immediately |
| 2: CMJ tests | None                                         | -        | 3-4 days | ✓ Can start immediately |
| 3: Real-time | Docker, deployment, load testing, monitoring | CRITICAL | 4 weeks  | ✗ BLOCKS this task      |
| 4: Running   | Performance regression testing               | MEDIUM   | 1 week   | ~ Can parallel Task 3   |
| 5: APIs      | Integration testing framework                | MEDIUM   | 1 week   | ~ Can parallel Task 3   |

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## Required Infrastructure Investment

### Build (Week 1-3)

| Component             | Effort         | Priority | When          |
| --------------------- | -------------- | -------- | ------------- |
| Dockerfile            | 3-5 days       | CRITICAL | Week 1        |
| Docker Compose        | 2-3 days       | HIGH     | Week 1        |
| Load Testing (Locust) | 3-4 days       | CRITICAL | Week 1        |
| Performance Profiling | 3-4 days       | HIGH     | Week 1        |
| Deployment Pipeline   | 5-7 days       | CRITICAL | Week 2-3      |
| Prometheus + Grafana  | 4-5 days       | HIGH     | Week 2-3      |
| WebSocket Testing     | 3-4 days       | HIGH     | Week 2        |
| Staging Environment   | 2-3 days       | HIGH     | Week 2        |
| **TOTAL**             | **25-35 days** | -        | **Weeks 1-3** |

### Cost Estimate

**Development (local):** $0/month
**Staging (cloud):** $100-200/month
**Production:** $500-1000/month (Year 1)
**CI/CD Tools:** $0-50/month

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## Critical Decisions Required

### DECISION 1: Latency Validation (End of Week 1, Task 3)

**Question:** Can we achieve \<200ms end-to-end latency?

**What We Need to Know:**

- MediaPipe detection time on real hardware
- Network streaming overhead
- Encoding/decoding latency
- Total frame-to-metrics time

**Testing Approach:**

- Run performance tests on local hardware (Week 1 of Task 3)
- Measure with realistic video resolution
- Target: \<50ms server-side processing
- If achievable: Proceed with real-time architecture
- If not: Plan fallback (async processing, client-side lite model)

**Fallback Options:**

- **Fallback 1 (250ms real-time):** Accept slower latency, still competitive
- **Fallback 2 (Async):** Queue-based, not truly real-time but fast
- **Fallback 3 (Client-side):** Lower accuracy, faster, but defeats server architecture

### DECISION 2: Cloud Platform Selection (Week 2)

**Options:**

1. **AWS ECS + Fargate** (Recommended)

   - Native GitHub Actions integration
   - Pay-per-use (efficient for variable load)
   - Full ecosystem (S3, RDS, CloudWatch)
   - Cost: ~$600-1000/month production

1. **Google Cloud Run**

   - Simpler deployment
   - Better for initial MVP
   - Limitation: 1 concurrent request per instance (WebSocket issue)
   - Cost: ~$400-800/month

1. **Kubernetes (self-hosted or managed)**

   - Most flexible
   - Steeper learning curve
   - Best for 100+ concurrent at scale
   - Cost: ~$800-1500/month

**Recommendation:** AWS ECS Fargate (good balance of simplicity + power)

### DECISION 3: Real-Time Scaling Strategy (Week 3)

**Challenge:** MediaPipe is CPU-bound, can't easily handle 100+ concurrent users

**Options:**

1. **Multi-instance strategy** (Recommended)

   - 4-8 instances, each handling 12-25 users
   - Load balancer distributes traffic
   - Cost scales with users
   - Best for 100+ concurrent

1. **GPU acceleration** (Expensive)

   - Use GPU instances for MediaPipe
   - Lower latency, faster detection
   - 3-5x cost increase
   - Use only if load requires it

1. **Asynchronous queue** (Queue-based)

   - Client sends video, gets results later
   - Not truly real-time, but fast (\< 5 second delay)
   - Much cheaper, handles 1000s of concurrent
   - Trade-off: Not coaching feedback

**Recommendation:** Start with multi-instance (option 1), scale based on actual load

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## Recommended Implementation Timeline

### Week 1 (Tasks 1-2 + Infrastructure Planning)

- **Tasks:** Ankle fix + CMJ tests (proceed as planned)
- **Infrastructure:** Build Dockerfile, add load tests, performance profiling
- **Decision point:** Latency validation (\< or > 200ms)

**Deliverable:** Dockerfile ready, latency baseline established

### Week 2 (Task 2 Complete + Infrastructure Build)

- **Tasks:** CMJ tests complete, Task 5 API docs started
- **Infrastructure:** Deployment pipeline, Prometheus setup, staging environment
- **Status:** Real-time code scaffolding begins

**Deliverable:** Staging environment ready, monitoring live

### Week 3 (Task 3 Real-Time Starting)

- **Tasks:** Task 3 implementation begins
- **Infrastructure:** Real-time service deployed to staging, load testing begins
- **Decision point:** Performance acceptable? Scale strategy chosen?

**Deliverable:** Sub-200ms latency validated OR fallback plan activated

### Week 4-5 (Task 3 Active + Task 4 Starting)

- **Tasks:** Real-time optimization, running gait metrics defined
- **Infrastructure:** Canary deployment pipeline ready, monitoring tuned
- **Status:** All staging tests green

**Deliverable:** Production deployment approval ready

### Week 6-7 (Task 3 Complete + Tasks 4-5 Complete)

- **Tasks:** Real-time to production, running gait complete, APIs ready
- **Infrastructure:** Production monitoring live, alerts active
- **Status:** Multi-sport platform operational

**Deliverable:** 3-sport platform with real-time in production

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## Risk Mitigation Summary

| Risk                | Mitigation                                    |
| ------------------- | --------------------------------------------- |
| Latency > 200ms     | Perf testing Week 1, fallback plan if needed  |
| Deployment failures | Staging-only for 2 weeks, then canary rollout |
| No alerting in prod | Monitoring mandatory before production deploy |
| Scaling bottleneck  | Start multi-instance, scale based on metrics  |
| WebSocket bugs      | Advanced testing framework + stress tests     |

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## Required Approvals

- [ ] Budget approval ($100-200/month staging, $500-1000/month prod)
- [ ] Cloud platform selection (ECS vs Cloud Run vs Kubernetes)
- [ ] Performance testing schedule (Week 1, Task 3)
- [ ] Infrastructure resource allocation (DevOps engineer 60% FTE)
- [ ] On-call rotation and alerting procedures

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## Success Criteria (Month 6)

✓ All 5 tasks complete
✓ 3+ sports supported (CMJ, Drop Jump, Running + others)
✓ Real-time capability live in production
✓ \<200ms latency (p95) achieved
✓ APIs published, SDKs available
✓ \<1% error rate, 99%+ uptime
✓ Monitoring alerts working
✓ Auto-scaling handles 100+ concurrent

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## Bottom Line Recommendation

**PROCEED with caution. Infrastructure investment is substantial but necessary.**

Current bottleneck: **Infrastructure readiness, not feature complexity.**

If infrastructure built by Week 3: **Roadmap on track, all tasks achievable**
If infrastructure delayed beyond Week 3: **Real-time launch delayed 2-4 weeks**

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**Status:** Ready for approval and implementation
**Owner:** DevOps/CI-CD Engineer
**Next Steps:** Schedule perf testing and approve cloud platform selection
