Our Work
EdgeCloud Monitor
Cloud-Native Monitoring & Edge Computing
A monitoring platform concept connecting edge-device measurements with a service-based backend and dashboard. The MSc implementation established its first foundation; Version 2.0 continues that development.
01 / Engineering overview
From edge signals to a usable monitoring view.
The engineering problem
Measurements from edge devices are useful only when they can be collected, communicated and understood in one place. The MSc project explored that connection across device software, backend services and an operator-facing dashboard.
The original approach
Version 1 combined a Python edge agent, Java Spring Boot services and a React dashboard. The agent sent telemetry and heartbeat requests to backend REST endpoints, while the dashboard presented device monitoring information. Later work extends the platform without making Version 2.0 a completed release.
02 / System architecture
A clear path from device to data.
The diagram shows the original telemetry path. Supporting services and the dashboard have distinct roles; it does not imply that every request uses the same gateway route.
Python edge agent
Collects CPU, memory and temperature readings, and sends heartbeats.
REST endpoints
Receive telemetry and device heartbeat requests.
Spring Boot services
Handle monitoring and device information within the service-based backend.
MySQL databases
Store data for the respective backend services.
- The React dashboard presents monitoring information through backend APIs.
- Spring Cloud Gateway supports API routing; Eureka supports service discovery.
- Docker Compose was used to run the development environment.
03 / Engineering highlights
Decisions behind the foundation.
Separated service responsibilities
Monitoring, device and alert concerns were divided across backend services and their data stores.
Collection at the edge
A Python agent gathered device measurements and sent telemetry and heartbeat requests via REST.
Monitoring interface
A React dashboard made device monitoring information available in one interface.
Development integration
Gateway routing, Eureka discovery and Docker Compose brought the services together for development and testing.
04 / Technical challenge
Routing inside the container environment.
Challenge
Historical end-to-end testing found a mismatch between the gateway's internal port and its Docker Compose port mapping.
Engineering response
The container mapping was corrected and the gateway was recreated during the documented validation.
Lesson learned
Service routing needs to be checked in the assembled development environment, not only in individual components.
05 / Development stages
A documented foundation, with continuing work.
Original MSc implementation
Version 1
The academic implementation established the edge agent, service-based backend and monitoring dashboard.
- Telemetry and heartbeat handling
- React monitoring dashboard
- Historical end-to-end, Raspberry Pi and simulated telemetry testing
Under development
Version 2.0
Later records document further increments, without establishing a completed or released Version 2.0.
- Project workspaces
- Project-scoped alert-rule management
- Device maintenance functionality
06 / Technology
The engineering stack.
Frontend
React
Backend
Java · Spring Boot · REST APIs
Service infrastructure
Spring Cloud Gateway · Eureka · Docker Compose (development)
Data
MySQL
Edge
Python · Raspberry Pi testing
07 / Evidence & attribution
Historical validation.
Project records document end-to-end integration, physical Raspberry Pi compatibility and simulated telemetry testing of the original implementation. The later project-level metric aggregation endpoint remains unsupported; Version 2.0 is still under development. JWT-based access controls are present in relevant backend components, without a claim of end-to-end authenticated telemetry.
Project attribution
Originating as an MSc academic engineering project, with subsequent continued development. It was not commissioned TK Software client work.
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