Engineering stories,
not just project names.

The app I programmed. Choose an exercise and enter the training date, weights and repetitions for each set directly in the app. The saved sessions form the basis for its history, volume calculations and progress charts. The public Kraftwerk page is a read-only presentation of this training history. Read how Kraftwerk began →

Data with context. Session metrics, total volume, steps, and time-range controls make individual workouts meaningful within weekly and monthly patterns.

Built to evolve. CSV and health-data imports keep historical information portable, while the presentation layer can gain new metrics without rewriting the underlying records.

Inside the Kraftwerk app

The Kraftwerk app: workout entry and progress analysis with recorded training data.

Monitoring is a system, not a screen. Useful observability starts with service ownership and meaningful signals—not with collecting every available metric.

Operational learning. Incidents and capacity constraints become inputs for better thresholds, dashboards, runbooks, and architecture decisions.

From servers to cloud. The tools changed over time, but the principle remained: detect deterioration early, make impact understandable, and give responders enough context to act.