Overview
This course examines the design, operation, analysis, and governance of telemetry systems that collect and transmit measurements, events, and usage data from software, devices, and networks. Topics include telemetry architectures; sensing and instrumentation; metrics, logs, traces, events, and time-series data; sampling; timestamps and clock synchronization; data quality; edge processing; gateways and message brokers; batch and streaming pipelines; schema and metadata design; storage and retention; dashboards; observability; anomaly detection; reliability indicators; data provenance; and lifecycle management.
Privacy and governance topics include personally identifiable information, sensitive attributes, inference and re-identification risks, data minimization, purpose limitation, consent and notice, access and deletion rights, retention policies, de-identification, pseudonymization, aggregation, differential privacy concepts, encryption, access controls, auditability, threat modeling, and privacy impact assessment. Practical work develops application or sensor-network instrumentation, telemetry pipelines, monitoring views, event detection, and privacy-preserving transformations. Students evaluate trade-offs among diagnostic value, operational cost, data granularity, security, and individual privacy, and document responsible observability practices and governance controls.
Learning Outcomes
- Analyze telemetry requirements for software, device, and network environments.
- Design telemetry architectures incorporating instrumentation, collection, transport, processing, storage, and visualization components.
- Evaluate the quality, completeness, timeliness, provenance, and reliability of telemetry data.
- Implement suitable metrics, logs, traces, events, schemas, and time-series representations for operational monitoring.
- Assess privacy, security, inference, and re-identification risks arising from telemetry collection and use.
- Apply data minimization, aggregation, pseudonymization, access control, encryption, retention, and differential privacy concepts to telemetry workflows.
- Interpret dashboards, reliability indicators, and anomaly-detection results to support operational decisions.
- Construct threat models and privacy impact assessments for telemetry systems.
- Defend governance recommendations by synthesizing technical, operational, ethical, and regulatory considerations.
Timetable
| Type | Length | Frequency | Period |
|---|---|---|---|
| Lecture | 2 hours | Weekly | All semester |
| Lab | 2 hours | Weekly | All semester |
| Tutorial | 1 hour | Fortnightly | All semester |
Assessment Schedule
| Type | Description | Weighting |
|---|---|---|
| Assignment | Telemetry requirements and architecture assignment | 15.00% |
| Assignment | Privacy risk and governance analysis | 20.00% |
| Test | Practical instrumentation and pipeline test | 20.00% |
| Deliverable | Observability dashboard and anomaly detection deliverable | 20.00% |
| Exam | Final examination | 25.00% |
Teaching Staff & Programs
This course is delivered jointly by faculty from the participating programs listed below. In line with the Douchewater Way, the University of Sexology tailors core instruction directly to each cohort's specific discipline — adapting curriculum to program needs rather than forcing students into a one-size-fits-all model. Learn more about our approach at The Douchewater Way.