From POC to Nationwide: The 18-Week Carrier Deployment Playbook
Deploying AI-driven caching at carrier scale is not a flip-the-switch moment. It is a sequenced operation across MEC infrastructure, UPF integration, compliance frameworks, and NOC tooling—tested to carrier-grade standards before a single subscriber touches it.
We built this 18-week playbook from direct experience with Tier-1 carriers. Every phase has a gate. Every gate has measurable criteria. No phase begins until the previous one passes.
The 18-Week Phased Deployment
The playbook is structured in five phases, each building on validated outcomes from the previous one. Rushing phases is how carrier deployments fail. This timeline is aggressive but proven.
Discovery & MEC Environment Setup
Before any traffic touches Cachee, we need to understand the carrier's network topology, traffic patterns, and MEC infrastructure. This phase is about preparation—not performance.
- Deploy Cachee containers into carrier MEC Kubernetes clusters across 10+ initial markets
- Map UPF traffic steering to understand how subscriber data flows from gNodeB through the User Plane Function to the internet
- Establish baseline latency measurements across all target markets—P50, P95, P99, and max—to quantify the "before" state
- Configure AI models with carrier-specific traffic patterns: peak hours, content mix, regional preferences, device type distribution
Single-Market POC
One metro market. Full stack. Progressive traffic steering with a kill switch at every step.
- Shadow mode for 48 hours: Cachee's AI makes caching decisions but does not serve responses. Every decision is logged and compared against what the origin actually served. This validates correctness before any subscriber impact.
- Progressive traffic steering: 5% → 25% → 50% → 100% of market traffic, with 24-hour hold periods between each ramp and automated rollback triggers.
- A/B comparison: Cachee-served subscribers vs. control group, measured on P50 latency, throughput, and error rates.
- POC target: P50 latency reduction of 60%+ and cache hit rate exceeding 90%.
Multi-Market Expansion
Scale from one market to ten. This is where cross-market intelligence and compliance become critical.
- 10 metro markets brought online simultaneously, each following the same progressive steering pattern validated in Phase 2
- Federated learning enables cross-market intelligence: a viral video trending in Dallas pre-warms caches in Houston and Austin before the traffic wave arrives
- Event detection models activate for sports game patterns, morning/evening commute spikes, and regional content surges
- CPRA compliance engine engaged—ensuring data sovereignty, subscriber privacy, and opt-out handling across all jurisdictions
Load Testing & Stress
Before nationwide rollout, the system must survive everything a carrier network can throw at it—and things that should never happen but will.
- Sustained load: 1M+ req/sec/node for 72 continuous hours with zero degradation
- Chaos engineering: MEC node kills, entire region outages, and Super Bowl-scale traffic spikes—injected without warning
- Self-healing validation: <60 second recovery from any single-node failure with zero data loss and no subscriber-visible errors
- Handover testing: Subscriber mobility across MEC zones—driving a car at 70 mph across cell boundaries while streaming—must produce zero session interruptions
Nationwide Production
All MEC sites go live. The system transitions from project to product.
- All MEC sites activated with 5G SA network slicing integration—Cachee operates as a first-class network function within the carrier's slice architecture
- Cost optimization engine enabled: 30–40% reduction in backhaul and origin costs through intelligent prefetching and deduplication
- NOC dashboards deployed across CloudWatch, PagerDuty, and Slack with carrier-specific alert thresholds and escalation paths
- 20+ operational runbooks delivered covering every failure mode encountered during Phase 4 chaos testing, plus standard day-2 operations
Carrier-Grade Testing
Carrier-grade is not a marketing term. It is a specific set of requirements that separate enterprise software from telecom infrastructure. Every test category below must pass before Phase 5 begins.
1. Load & Performance
| Test | Requirement | Duration |
|---|---|---|
| Sustained throughput | 1M+ req/sec/node | 72 hours |
| Burst capacity | 5M req/sec/node | 15-minute spikes |
| Soak test | Zero memory leaks, zero degradation | 72 hours |
| Tail latency | P99 <50ms | Across all load levels |
2. Chaos Engineering
| Failure Scenario | Requirement |
|---|---|
| Single node kill | <60 sec recovery |
| Region failover | <5 sec failover |
| Data integrity | Zero data loss |
| Sustained availability | 99.99% uptime |
3. Compliance & Security
| Category | Requirement |
|---|---|
| Regulatory coverage | 30+ regulations |
| Penetration testing | Passed (third-party) |
| Audit log retention | 7-year retention |
| Data sovereignty | 100% jurisdictional compliance |
4. Handover & Mobility
| Test | Requirement |
|---|---|
| Handover latency | <50ms handover |
| Session continuity | 100% continuity |
| MEC zone transitions | Seamless (zero drops) |
5. A/B Latency Validation
| Parameter | Requirement |
|---|---|
| Sample size | 100M+ requests |
| Statistical confidence | 99.9% |
| Market coverage | 10+ MSAs |
| Expected latency delta | 60–85% reduction |
6. Disaster Recovery
| Metric | Requirement |
|---|---|
| Recovery Time Objective (RTO) | <60 sec |
| Recovery Point Objective (RPO) | Zero |
| Failover mechanism | Fully automatic |
| DR drill cadence | Quarterly |
The Business Case: $895M–$1.55B Annual Value
Carrier executives do not approve 18-week deployments on technical merit alone. They approve them on business impact. Here is the financial model for a Tier-1 carrier with 80M+ subscribers.
Revenue Upside
| Revenue Stream | Annual Value | Mechanism |
|---|---|---|
| Low-latency premium services | $180–320M | Premium tiers for gaming, AR/VR, and live sports with guaranteed sub-10ms edge latency |
| Reduced subscriber churn | $400–600M | 0.5% churn improvement from measurably better streaming, browsing, and app performance |
| Enterprise MEC contracts | $50–120M | Sell edge caching as a managed service to enterprise and content provider customers |
| Network slicing revenue | $30–80M | Cache-aware slices with SLA-backed latency guarantees command premium pricing |
| Total Revenue Upside | $660M–$1.12B/yr |
Cost Savings
| Cost Category | Annual Savings | Mechanism |
|---|---|---|
| Backhaul bandwidth reduction | $120–200M | Cache hits served at the MEC edge never traverse expensive backhaul links |
| Origin infrastructure downsizing | $40–80M | 90%+ hit rates mean origin servers handle a fraction of previous load |
| Autonomous operations | $15–30M | 96% reduction in manual cache management, TTL tuning, and invalidation operations |
| Cost optimization engine | $60–120M | AI-driven prefetch scheduling that shifts traffic off peak-rate transit windows |
| Total Cost Savings | $235–$430M/yr |
Combined Annual Impact
| Metric | Value |
|---|---|
| Total revenue upside | $660M–$1.12B/yr |
| Total cost savings | $235–$430M/yr |
| Combined annual value | $895M–$1.55B/yr |
| Return on investment | >10:1 ROI |
| Time to value | 18 weeks |
Why 18 Weeks Instead of 18 Months
Traditional carrier vendor deployments take 12–24 months. Three factors compress Cachee's timeline:
- Container-native architecture. Cachee runs as standard K8s pods on existing MEC infrastructure. No custom hardware. No proprietary appliances. No rack-and-stack.
- Protocol-transparent proxy. UPF traffic steering routes HTTP/HTTPS through Cachee without application awareness. No SDK integration. No API changes. No subscriber device modifications.
- Self-tuning AI. The AI models begin learning carrier-specific patterns from hour one of Phase 1 traffic ingestion. By Phase 2, the models have already optimized for the carrier's content mix, peak patterns, and regional behavior—without manual configuration.
The 18-week constraint is not technical. It is organizational. Carrier security reviews, compliance attestations, and operations team onboarding define the timeline. The technology is ready from week three.
The Bottom Line
Deploying AI caching at carrier scale is a solved problem. The playbook is five phases, six test categories, and 18 weeks. The business case is nearly a billion dollars annually at the low end.
The carriers who deploy first capture the premium positioning. Low-latency tiers, enterprise MEC contracts, and cache-aware network slicing are all first-mover markets. The technology exists today. The only variable is the decision to start week one.
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