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SATS High-Frequency Telemetry Pipeline - Technical Execution Roadmap

This document outlines the objective, non-speculative engineering milestones structured to scale infrastructure throughput, harden security perimeters, and implement high-availability state persistence layers.

Phase 1: Ingestion Performance & Server Modernization (Current)

  • ASGI Server Migration: Replace standard Uvicorn local development server loops with the high-throughput, Rust-based Granian runtime to maximize network request handling per second.
  • Environment Extraction: Abstract all configuration states and remote data endpoints out of application modules into distinct .env parameters to ensure deployment environment isolation.
  • Network Handshake Hardening: Enforce strict cross-origin header checks (CSWSH defense) and regular expression whitelisting across all active endpoint route parameters.

Phase 2: Distributed State Persistence & Horizontal Scaling

  • Decoupled Cache Architecture: Migrate the in-memory stateful rolling history array out of local application memory into an independent Redis data cache cluster layer.
  • Zero-Loss Replay Syncing: Ensure client synchronization cycles pull historical ticks directly from the Redis cluster storage layer to prevent telemetry dropouts during backend process restarts.
  • State Management Abstracting: Transition the frontend configuration states into structured web-storage persistence layers to lock user interface preferences seamlessly across independent browsing sessions.

Phase 3: Tokenized Authentication & Granular Access Controls

  • Handshake Authentication: Implement strict JSON Web Token (JWT) or HMAC-signed handshake authorization parameters across all active WebSocket channels.
  • Dynamic Throttling Windows: Upgrade from simple fixed-window memory tables to a distributed Redis token-bucket algorithm to enforce precise, tiered API rate-limiting rules across public networks.
  • Input Validation Schemas: Expand the parameter regular expression checks into comprehensive structural input sanitization blocks to completely mitigate advanced parameter injection vectors.

Phase 4: Automated Verification & Infrastructure Observability

  • End-to-End Testing Suites: Construct integration test pipelines using pytest-asyncio to programmatically mock full-duplex WebSocket data transmissions and exception dropouts.
  • Continuous Testing Pipeline: Expand the GitHub Actions CI workflow to run automated linting, security audits (bandit), and unit testing across multiple target runtime setups (Python 3.13 and Python 3.14-dev).
  • Telemetry Metrics Exporting: Implement structured Prometheus metric endpoints (/metrics/system) to track performance statistics such as connection volume, network latency, and processing times.