PERFORMANCE
Real-time scale
Event-driven platforms for peak load and forensic observability.
What it solves
Batch-only platforms miss modern expectations; naive streaming creates inconsistency and operational blind spots.
How it works
- 1Characterise load, SLOs, and consistency requirements per journey.
- 2Select patterns—events, CQRS, caching—where they earn their complexity.
- 3Engineer idempotency, backpressure, and recovery with explicit trade-offs.
- 4Instrument tracing and SRE practices aligned to executive risk appetite.
Where it applies
- Payments, trading-adjacent, and mobility marketplaces
- Telemetry and network operations in telecom
- Peak-event retail and digital sales
Business outcomes
- — Predictable behaviour under stress tests and seasonal peaks
- — Shorter recovery time through reversible change and clear runbooks
- — Capacity planning grounded in measured utilisation
Event-driven architectures engineered for peak-load reliability, forensic observability, and sub-second recovery.