3.1 Control Plane vs Agent Execution Plane
3.2 Project Scope Model
3.3 Data Flow: Source -> Release -> Pipeline -> Logs/Artifacts
3.4 Runtime Configuration Layers (global / project / environment)
3.5 Pipeline Execution Semantics
3.6 Release Governance Path
3.7 Rollback Architecture (Policy-driven)
3.8 Security and Trust Boundaries
3.9 State and Persistence Model
3.10 Scalability Model
3.11 Failure Modes and Recovery Patterns
3.12 Why This Architecture Works in Practice
3.10 Scalability Model
Orbnetes deployment and release orchestration documentation for operators and platform teams.
Scaling is primarily execution-plane horizontal scaling:
- add more agents with correct tags,
- segment runner capabilities by role/environment,
- keep control plane centralized.
Throughput depends on:
- agent availability and tag distribution,
- job complexity and external system latency,
- queue depth and dependency structure.
Practical scaling strategy:
- start with one stable agent pool,
- split by workload type (build/deploy/ops),
- then split by risk domain (prod vs non-prod).