EdgeOps

Roadmap — Full Details

The complete, staged plan for evolving Cortx from μscope to a full EdgeOps platform.

Stage 1

Record and Replay

Save all sensor data and replay it later for debugging.

  • Record all sensor streams with synchronized timestamps
  • Playback controls: pause, scrub through timeline, bookmarks
  • Export recordings to standard formats
Dependencies: Current μscope serial implementation
Stage 2

Connect More Devices

Add network transports and secure channels so foundation is ready for remote control.

  • Support for TCP/UDP network connections
  • MQTT and WebSocket for IoT devices
  • CAN bus support for automotive and industrial systems
Dependencies: Current μscope serial implementation
Stage 3

Remote Control & Updates

Use the new network transports to send commands and push firmware updates.

  • Send commands to devices over WiFi, Bluetooth, TCP, MQTT
  • Push signed firmware updates remotely (with automatic rollback on failure)
  • Staged rollout (test a few devices first, then expand)
  • Track which devices have which firmware versions
Dependencies: Stage 2 (network transports)
Stage 4

Visualize More Sensors

Visualize LiDAR, camera, motion, and other sensor data together in a single synchronized workspace.

  • LiDAR point cloud visualization
  • Camera/video stream display
  • Flexible dashboards for any sensor telemetry
Dependencies: Stage 2
Stage 5

Cloud Dashboards

Monitor fleets remotely while devices continue to work offline.

  • Cloud dashboards with device list, health, and metrics
  • Trigger OTA updates and view update history
  • Browse logs and download recordings for support
  • Basic roles and access control for team members
Dependencies: Stages 1 & 3
Stage 6

Fleet Policy & Rollout Orchestration

Give teams a control plane to plan, approve, and monitor large-scale rollouts safely.

  • Policy engine for staged rollouts and approvals
  • Scheduling (maintenance windows, blackout periods)
  • Compliance dashboard showing firmware/config drift
  • Automatic rollback based on health metrics
  • Integration hooks for ticketing / incident workflows
Dependencies: Stages 1, 3 & 5
Stage 7

On-Device Automation

Run automations on-device so fleets can respond instantly without cloud latency.

  • Create rules that trigger alerts when sensor data crosses limits
  • Combine readings from multiple sensors to make decisions
  • Deploy pre-trained ML models for detection or tracking
  • Trigger local actuations or safe-state commands
Dependencies: Stages 3 & 4
Stage 8

Complete Platform

Everything working together as one integrated system.

  • All sensor types working in one unified view
  • 3D visualization with playback and collaboration
  • Full device fleet management with secure updates
Dependencies: Stages 1-7