Aviation Communication Command Solution

Overall System Technical Solution

This solution is built around a microservices + containerized cloud-native architecture, adopting a full-stack domestic adaptation approach and implementing a "two sites, three centers + same-city dual-active" high-availability deployment to ensure local data autonomy and controllability. Seamless integration with the client's existing business systems is achieved through a unified API gateway. All designs are tailored to the professional scenarios of aviation operation command, balancing stability, scalability, security, and operational convenience.

1.1 Cloud-Native Microservices Architecture Design

1.1.1 Core Architecture Implementation

Strictly following the tender requirements, a microservices + containerized architecture is adopted, providing a unified WEB access entry based on the B/S model. The system is divided into three tiers: access layer, service layer, and data layer. Each service module is independently deployed and decoupled, supporting individual scaling and canary releases, achieving high business cohesion and loose coupling, and meeting future requirements for flexibly adding server nodes or resource instances.

Access Layer: Deploys load balancers, domestic firewalls, and a unified API gateway to implement request distribution, security protection, interface authentication, and traffic control, supporting unified access from multiple terminals (PC, tablet, mobile);

Service Layer: Split by business domain into independent microservices such as communication services, user authentication, speech transcription, recording storage, message push, and emergency command, with inter-service communication via service registration and discovery;

Data Layer: Adopts a domestic distributed database + tiered storage architecture to achieve classified storage and unified management of business data, audio/video data, and log data, ensuring data security and access efficiency.

1.1.2 Technology Stack Selection and Implementation

The ByteDance CloudWeGo microservices ecosystem + Kubernetes (K8s) container orchestration platform is adopted to achieve automated service deployment, elastic scaling, fault self-healing, and canary releases. A private container image registry + CI/CD pipeline is deployed in parallel, supporting one-click deployment and version management across development, testing, and production environments, significantly improving system iteration efficiency.

Elastic Scaling: Automatic elastic scaling triggered by CPU/memory/business metrics is implemented based on K8s Horizontal Pod Autoscaler. When new business modules or server nodes are added, the scaling process is completely transparent to users, with scaling efficiency improved by over 70% compared to traditional architectures;

Service Governance: Sentinel is integrated to implement circuit breaking, degradation, and rate limiting for microservices, preventing single-point fault propagation and ensuring system stability under peak loads;

Link Monitoring: SkyWalking is integrated for full-link tracing of microservices, combined with Prometheus + Grafana to build a full-link performance monitoring and alerting platform, enabling visualization of business health, early prediction of performance bottlenecks, and early detection and handling of faults.

1.2 Localized Deployment and Full-Stack Xinchuang Adaptation Solution

1.2.1 Localized Deployment Implementation

Strictly following the tender requirement of "core data autonomy and controllability," a "two sites, three centers" private deployment architecture is adopted (Beijing production center, Nanjing production center, remote disaster recovery center). All operational data and communication records (including audio/video, text messages, and operation logs) are stored in the internal data center designated by the client, without transmission over the internet, achieving dual security assurance of physical isolation + logical isolation, with 100% data autonomy and controllability.

The deployment architecture adopts a network partition design, divided into DMZ zone, application zone, and data zone, with strict access control enforced by firewalls between zones, opening only necessary ports and services;

All data is backed up with multiple replicas, business data is synchronized in real time, and audio/video data is synchronized periodically, ensuring no data loss, along with data backup and recovery procedures and testing plans.

1.2.2 Full-Stack Domestic Adaptation

Based on the Feiteng CPU and Galaxy Kylin OS required by the tender, full-stack domestic software and hardware adaptation is implemented, covering chips, operating systems, databases, middleware, and all other components. Smooth migration solutions and tools from traditional databases to domestic databases are also provided, addressing the client's Xinchuang transformation challenges. Domestic compatibility mutual certification reports + joint test reports are provided with the solution.

Adaptation Category	Basic Adaptation (Meets Tender Requirements)	Extended Adaptation (Positive Deviation)	Supporting Services
Domestic CPU	Phytium FT-2000+/64	Kunpeng 920, Hygon DCU, Loongson 3A5000	Hardware Compatibility Testing
Domestic Operating System	Kylin V10 (Server/Desktop Edition)	Uniontech UOS, NFS China, NeoKylin	System Optimization and Customization
Domestic Database	DM8 (DaMeng), KingbaseES (Renmin Jincang)	OceanBase, TiDB, Oscar (Shenzhou General)	Data migration tools + migration training
Domestic Middleware	TongWeb (TongTech)	AAS (Kingdee Tianyan), CIC middleware	Interface adaptation and tuning

1.3 7×24-Hour High Availability and Reliability Design

1.3.1 Core High Availability Implementation

In strict compliance with the tender requirements, all core communication services (signaling, voice, messaging, recording, and authentication) adopt a 1:1 active/standby hot-standby configuration. The active and standby units are deployed on different physical servers, with 100ms heartbeat detection enabling millisecond-level automatic seamless failover. The switchover process causes no service interruption and no data loss, ensuring system service availability ≥99.9%.

1.3.2 High Availability Upgrade Design

Building upon the active/standby configuration, a "same-city dual-active + remote disaster recovery" high availability architecture is designed to meet the aviation industry's core requirement of "uninterrupted operation," achieving multi-tier fault protection:

• Same-City Dual-Active: The Beijing and Nanjing production centers are deployed in dual-active mode, with load balancing distributing business pressure. When either center fails, the other center can seamlessly take over all services, achieving RPO≈0 and RTO<30s.
• Remote Disaster Recovery: A data-level disaster recovery center is established at a remote site designated by the client, enabling real-time synchronization of core data to address extreme scenarios such as earthquakes and fires, ensuring business continuity.
• Full-Node Redundancy: In addition to core services, network equipment, load balancers, and storage devices are all configured with redundancy to eliminate single points of failure and achieve end-to-end high availability.

1.4 System Interfaces and Cross-Platform Integration Solution

1.4.1 Interface Integration Implementation

In strict compliance with the tender requirements, standardized open interfaces are provided free of charge to achieve seamless data interoperability with the client's FOC system, emergency response platform, and other specialized business systems, as well as office platforms such as Feishu and WeCom. Customized interface adjustments and joint debugging testing are supported.

1.4.2 Interface Architecture Upgrade

A unified API gateway based on Spring Cloud Gateway is established to implement unified authentication, authorization, rate limiting, monitoring, auditing, and log tracing for all interfaces, resolving the pain points of interface management in multi-system integration. Meanwhile, RESTful design specifications are followed, with OpenAPI 3.0 standard interface documentation and multi-language SDKs provided to reduce integration costs.

• Integration Methods: Multiple integration methods are supported, including RESTful API, Webhook, and message queues (RocketMQ/Kafka), to meet the integration requirements of different systems.
• Interface Security: All interfaces use HTTPS encrypted transmission, combined with IP whitelisting, Token authentication, and data signing, to prevent unauthorized invocation and data leakage.
• Interface Monitoring: An interface monitoring dashboard is built on the unified API gateway, displaying real-time interface call counts, response times, and call success rates. Multi-channel alerts are triggered upon interface anomalies, and multi-condition query and export of interface logs are supported.

1.5 System Fluency and Performance Assurance

1.5.1 Core Performance Indicators

• Concurrency Support: Based on the tender requirement of 50-seat concurrency, a maximum of 80 seats can be online simultaneously, with all core functions (contacts query, information loading, audio/video calls) responding within ≤1s.
• Real-Time Assurance: Instant messaging and status notifications use long-connection + message push protocols, with end-to-end delivery latency ≤200ms and delivery success rate ≥99.999% (exceeding the tender requirement of 99.99%).
• Peak Load Assurance: Verified through stress testing, the system experiences no performance degradation or interruption under peak load, and supports elastic scaling by adding resource instances, with the scaling process being transparent to users.
• Performance Planning Solution: We will develop a scientific and reasonable performance planning solution based on the project's business scenarios, user scale, and future business growth expectations. First, a comprehensive business requirement analysis is conducted to clarify the system's daily load, peak load values, and business growth trends, and to determine system performance indicators (concurrent users, response time, throughput, etc.). Second, resource planning is carried out based on performance indicators, including server configuration, database selection, and network bandwidth design, ensuring precise alignment between resource allocation and business requirements, while reserving more than 30% resource redundancy to accommodate future business expansion. Finally, a performance iterative optimization mechanism is established to periodically adjust performance planning based on business development, optimize system architecture and resource allocation, and ensure that system performance continuously meets business development needs.
• Stress Testing Solution: We will provide a complete performance stress testing solution, rigorously verifying system performance through testing to ensure compliance with tender requirements. The stress testing solution mainly includes: 1. Test Preparation: Define the test scope (covering all core business modules) and test indicators (concurrent users, response time, throughput, resource utilization, etc.), build a test environment consistent with the actual production environment, and prepare test data and test scripts. 2. Test Execution: Conduct stress testing in phases, including baseline testing, load testing, peak testing, and stability testing, simulating daily load, peak load, and extreme load scenarios, with real-time monitoring of system performance indicators and resource usage. 3. Test Analysis and Optimization: After testing is completed, conduct a comprehensive analysis of test data, identify system performance bottlenecks (such as insufficient resources or unreasonable architecture), develop targeted optimization plans and implement them, then re-run stress tests for verification until system performance fully meets requirements. 4. Test Report: Produce a complete stress testing report detailing the testing process, test results, performance bottlenecks, and optimization measures, ensuring that test results are traceable and verifiable.

1.5.2 Performance Optimization Measures

Frontend optimization: Built with Vue3 + Vite, implementing lazy loading of frontend code and resource compression to improve page load speed;

Backend optimization: Uses distributed caching (Redis) to cache hot data, reducing database access pressure, while also performing database sharding, table partitioning, and index optimization;

Audio/video optimization: Uses WebRTC technology to achieve low-latency audio/video transmission, with support for adaptive bitrate that automatically lowers the bitrate under poor network conditions to ensure communication continuity;

Adopts tiered storage and archiving strategies to ensure online retrieval of call recordings for no less than 6 months, with support for longer-term archiving for future reference; provides storage architecture and capacity planning solutions to meet tender requirements.