Satellite Monitoring & Diagnostics

Overview

When high-throughput satellite services scale, the “prime” control and provisioning systems can become a bottleneck. This project delivered a global monitoring and diagnostics solution that collected assurance data across points-of-presence and beams worldwide, normalised it, and streamed it into multiple analytics backends (including a big-data SIEM/observability stack). The architecture deliberately reduced load on prime systems, boosting reliability and speeding safe rollout of new satellite services.

My Role

Lead Solution Architect — end-to-end design, technical governance, and delivery leadership. Defined data contracts, ingestion strategy, and system boundaries; set non-functional targets (reliability, latency, blast-radius control); and guided implementation across platform, data, and operations teams.

Goals

  • Global capture of assurance telemetry and service KPIs across GX-5 coverage
  • Lossless, schema-controlled ingestion into analytics systems for near-real-time insight
  • Decouple/insulate prime control & provisioning systems from reporting/analytics load
  • Provide deep-dive tooling for CSO/operations to remotely diagnose incidents and drive root-cause analysis (RCA)

What I Designed

1) Data & Telemetry Plane

  • Edge collectors at gateways/PoPs normalising multi-vendor signals (network, service, and platform KPIs).
  • Schema-versioned event pipeline with back-pressure handling, idempotent writes, and replay for late/duplicate data.
  • Fan-out routing to multiple sinks: hot analytics (search/visualisation), cold storage (compliance/forensics), and ML feature stores.

2) Prime-System Offload Architecture

  • Read isolation: mirrored operational metrics into analytics stores; no direct reporting queries against prime systems.
  • Bulkhead & circuit-breaker patterns: analytics outages cannot cascade into control/provisioning planes.
  • Rate-limited exports and bounded connectors to guarantee SLOs for provisioning flows.

3) Diagnostics & RCA Tooling

  • CSO deep-dive views: per-beam/per-gateway timelines, correlated alarms, and customer-impact overlays.
  • Guided RCA: symptom → suspected domain (RF, backhaul, platform, service) with drill-downs and evidence trails.
  • Remote triage workflows to reduce truck rolls and compress Mean Time to Resolve.

Results & Impact

  • ~70% improvement in reliability when provisioning new satellite services, driven by load isolation and clearer SLOs.
  • Near-real-time visibility across global coverage, accelerating incident detection and response.
  • Consistent RCAs with auditable evidence, improving customer communications and reducing repeat incidents.
  • Safer scaling: analytics growth no longer threatens core control/provisioning availability.

Key Decisions & Why They Mattered

  • Event-first design with strict schemas → stable integrations and painless evolution.
  • Hot/cold tiering → fast operator queries without sacrificing forensic depth.
  • Operational bulkheads → analytics failures never impact service activation paths.
  • Correlation by customer/beam/gateway → faster, more actionable RCAs for the CSO team.

Tech Highlights (generic)

  • Stream ingestion & processing, schema registry, time-series/observability stack
  • Object storage for long-term retention
  • Role-based access and audit logging
  • Infrastructure-as-code and CI/CD for repeatable deploys

What I Learned

  • In mission-critical environments, protecting prime systems is the fastest path to real reliability gains.
  • Standardised telemetry and contracts out-perform ad-hoc dashboards when teams and vendors scale.
  • RCA tools must mirror how operations think: timeline + topology + impact beats raw metrics every time.