AeroVance
Platform API Reference Architecture Compliance Support

1. System Overview

The AeroVance Platform operates as a hybrid cloud-edge architecture, connecting ground control stations, orbital assets, and satellite payloads through a unified telemetry and command mesh. The system is designed for low-latency data routing, high availability, and strict defense-grade compliance.

Note: All architectural decisions must align with AS9100D quality standards and ITAR/EAR export control classifications. Cross-border data routing requires pre-approval from the Security Compliance Board. ground stations operate on isolated VPCs with strict microsegmentation.
Ground Station Secure Cloud Mesh Processing & Storage API Gateway & Auth Satellite / Payload
Figure 1.1: High-Level Data Flow Architecture (Ground → Cloud → Orbit)

The architecture enforces a zero-trust model where every hop requires mutual TLS authentication. Data is encrypted at rest using AES-256-GCM and in transit via TLS 1.3 with forward secrecy. Mission-critical telemetry follows a priority-based routing queue to prevent packet loss during high-congestion downlink windows.

2. Integration Patterns

External systems and third-party payloads integrate with AeroVance via standardized REST/gRPC endpoints and MQTT telemetry brokers. All integrations must adhere to the following patterns:

2.1 REST API Gateway

Stateless, versioned endpoints for mission planning, payload configuration, and metadata retrieval. Rate-limited to 1000 req/min per API key.

GET /v3/missions/{mission_id}/payloads
curl -X GET "https://api.aeravance.com/v3/missions/mv-2025-08/payloads" \
  -H "Authorization: Bearer $AEROVANCE_API_KEY" \
  -H "Content-Type: application/json" \
  -H "X-Request-ID: req_8f3a9c2d"

2.2 gRPC Telemetry Streaming

High-frequency sensor data (IMU, thruster pressure, star tracker) streams via gRPC bi-directional channels. Protobuf schemas are version-controlled in the `proto/` repository.

stream TelemetryFeed (TelemetryRequest) returns (stream TelemetryResponse)
syntax = "proto3";

package aero.telemetry.v1;

message SensorReading {
  int64 timestamp_ns = 1;
  string sensor_id = 2;
  double value = 3;
  string unit = 4;
  bool calibrated = 5;
}

2.3 MQTT for Low-Power Payloads

Smaller cubesats and secondary payloads use MQTT over TLS for command-and-control. Topics follow the hierarchy: `aero/{mission}/cmd/{type}` and `aero/{mission}/telem/{stream}`.

3. Security & Compliance

AeroVance systems operate under strict defense and aerospace regulatory frameworks. All architectural components must satisfy the following baseline:

Standard Scope Implementation Requirement
ITAR/EAR Export Control Data residency in US/Australia/Japan VPCs only. No cross-border replication without CCL approval.
AS9100D Quality Management All CI/CD pipelines require signed artifact manifests and traceable change logs.
Zero Trust Network Security mTLS between all services. Short-lived JWTs with hardware-bound signing keys.
FIPS 140-2 Cryptography Only approved algorithms (AES-256, RSA-2048+, ECDSA P-256). No custom crypto primitives.
⚠️ Critical: Never hardcode cryptographic keys or ITAR-classified configuration parameters in source control. Use the AeroVance Vault SDK for secret injection at runtime.

3.1 Authentication Flow

Service-to-service authentication uses short-lived certificates issued by the internal PKI. Human operators authenticate via SSO + hardware M2FA. All privileged actions require multi-person authorization (MPA) with audit trails retained for 7 years.

4. Telemetry Data Pipeline

The telemetry ingestion pipeline processes millions of data points per second during active downlink windows. It consists of four primary stages:

  1. Ingestion: Raw UDP/TCP streams captured at ground station edge nodes. Deduplication and sequence validation applied.
  2. Normalization: Protobuf/JSON conversion, unit standardization (SI), and timestamp synchronization to UTC(LEAP).
  3. Processing: Real-time anomaly detection via ML models (isolation forests, threshold guards). Routing to hot/cold storage.
  4. Persistence: Time-series database (hot), Parquet partitioned S3 (warm), and cold archival tape systems for long-term mission records.
Python SDK Example: Streaming Telemetry Subscription
import aerovance_telemetry as avt

# Initialize secure connection with mTLS
client = avt.Client(
    region="us-east-1-gov",
    auth="hardware_token://env/AEROVANCE_CERT_PATH"
)

async def process_stream():
    async for frame in client.subscribe("mission-orion-7/raw"):
        if frame.anomaly_score > 0.85:
            await client.trigger_alert("THRUSTER_PRESSURE_SPIKE", frame)
            await client.pause_ingestion(frame.sequence_id)

if __name__ == "__main__":
    avt.run(process_stream())

5. Edge & Deployment Architecture

Ground control and satellite payloads utilize a GitOps-driven deployment model. Manifests are stored in private repositories and applied via sealed secrets and policy-as-code validation.

5.1 Ground Station Deployment

On-prem Kubernetes clusters run hardened OS images with kernel hardening, SELinux enforcement, and eBPF-based runtime security. Deployments are rolled out canary-first with automatic rollback on health check failure.

5.2 Payload Updates (Space-Grade)

Satellite software updates follow a strict A/B partitioning model. Updates are delta-compressed, signed with Ed25519, and verified against a public key pinned in the bootloader. Rollback requires dual confirmation from mission control and safety officer.

CLI: Submit Payload Update
avctl payload update \
  --mission orion-7 \
  --payload comms-array-v3 \
  --manifest ./releases/2.4.1/payload.yaml \
  --signing-key hw:///certs/mission-control \
  --dry-run # Validate before ground uplink
Best Practice: All space-bound artifacts must pass static analysis, fuzz testing, and radiation-hardened memory allocation checks before signing. Use the `av-test-suite` CLI to validate compliance automatically.