Raw Message Streaming (RMS) is ZF SCALAR’s real‑time, high‑volume data delivery mechanism that streams raw telematics events directly from ZF devices to customer systems through Kafka. It enables developers to build low‑latency, scalable data processing applications with direct access to device‑generated events.

🔍 1. What Is RMS?

RMS provides an end‑to‑end pipeline that streams raw device events without intermediate processing, allowing developers to consume real‑time data feeds from SCALAR devices.

Key features:

Real-time data feeds: Events stream directly from SCALAR devices into customer-facing Kafka topics with minimal latency.
Highly scalable: Designed for enterprise fleet integrations.
Publisher–consumer architecture: SCALAR publishes → customer applications consume.
Secure & centralized streaming: Managed by ZF with organizational-level access control.

🧩 2. How Integration Works

End-to-end workflow

SCALAR devices generate events (e.g., TPMS, TBS, drive-state).
RMS filters and maps events to standardized schemas.
Events are pushed to organization-specific Kafka topics.
Developer apps implement Kafka consumers to ingest and process data.

Subscription requirements

Access must be requested through ZF Sales or Customer Success.
Approval is processed internally and topics are created by ZF support.
Only one RMS subscription per customer is allowed.

📦 3. Supported Event Types

RMS publishes a variety of telematics and configuration events:

Event Type	Description
position.registered	Registers device position updates.
status.tpms	Tire pressure, temperature, and status details.
status.tbs	Trailer braking system status: lining, power, color codes.
status.trailer	Trailer status: lining, power, color codes.
status.comunit.power	Communication unit power status: lining, power, color codes.
config.tbs	TBS configuration (brand, model, serial, VIN).
event.drive.state	Fuel, mileage, coordinates, drive state.
config.tpms	Updated TPMS configuration details.
event.harshbrake	Harsh braking events: axle load, speed, coordinates.
event.rssactivation	RSS activation safety events.
event.absactivation	Anti-lock braking system activation events.
event.tbs.dtc.raised	Diagnostics for TBS-related issues.

These events power applications such as:

Real-time dashboards
Predictive maintenance systems
Safety event monitoring
Fleet tracking and optimization

🛠 4. Developer Responsibilities

✔ Implement Kafka Consumers

Developers must consume organization-specific Kafka topics using any Kafka client (Java, Go, Python, Node.js, etc.).

✔ Handle High-Volume Data

RMS is built for enterprise fleets — expect:

Burst events
High-frequency data
Need for stream processing and scalable consumption

✔ Event Parsing & Mapping

Each event type has a structured schema; map them into internal application models for:

Analytics
Alerting
Storage
Visualization

✔ Monitoring & Observability

Recommended components:

Consumer lag monitoring
Schema validation
Retry & replay logic
Health checks and logging

🔐 5. Security & Access Control

Topic access is controlled by ZF and tied to approved subscriptions.
Customer applications authenticate to Kafka using the credentials provided by ZF.
All messages delivered belong exclusively to the customer organization.

🚦 6. When Should Developers Use RMS?

RMS is ideal if your solution needs:

Pure real-time data without SCALAR UI/processing layers
High-throughput ingestion for fleets
Custom telematics logic (alerts, scoring, routing, analytics)
Low-latency triggers (alerts, workflows, edge automation)

If you need raw device-level events, RMS is the correct integration pathway.

🧭 7. RMS in the Broader SCALAR Ecosystem

RMS is part of the SCALAR Fleet Orchestration Platform — a large digital ecosystem providing full transport orchestration. It supports both human-driven and autonomous fleets using AI-based, real-time optimization.

📘 Summary

RMS enables developers to integrate directly with ZF device telemetry through Kafka, offering a secure, enterprise-grade, real-time data pipeline. With standardized event formats and high scalability, it’s ideal for building modern fleet intelligence applications.