Echtzeit-Operations-Hub

Streaming-Pipelines und operative KPIs, damit Dispatch und Kundenteams Verzögerungen und Ausnahmen in Minuten sehen — nicht erst im Nachtbatch.

Dispatch and customer teams were flying blind until the nightly batch landed. We connected shipment and exception events to streaming pipelines and operational dashboards so teams could act while freight was still moving.

Unser Ansatz

Stream topology

Kafka topics partitioned for scale, with stream processing for joins, windows, and late-arriving events.

SLA-driven monitoring

Freshness and lag alerts tied to SLOs; DLQ handling and replay paths documented for on-call.

Operational BI

Role-specific views for hubs and linehaul with drill-down to problematic legs without leaving the ops tool.

Was wir geliefert haben

Kafka-Ingestion und Stream-Processing für Sendungsereignisse
Operatives BI mit Alerts an Freshness-SLOs
Observability-Dashboards für Lag, Backlog und DLQs
Incident-Runbooks für Replay und Teilausfälle

Ergebnisse

Minutes-to-insight instead of next-day batch for critical lanes
Shared vocabulary between dispatch, CS, and engineering
Foundation for ETA and exception models on the same event fabric

Repräsentativer Stack

KafkaFlinkClickHouseGrafanaKubernetes