Definition
What Is Freight Observability?
Freight observability is the application of software observability principles to freight logistics. Just as Datadog monitors server health through logs, metrics, and traces, freight observability monitors shipment health through scan events, GPS data, and exception alerts. The three pillars of freight observability are events (scan in, scan out, departure, arrival, delivery), metrics (on time rate, damage rate, dwell time, transit time), and alerts (proactive exception notifications before your team has to chase them).
The three pillars of freight observability
Pillar 1: Events
What happened, when, and where.
Every shipment generates a stream of events: scan in at pickup, departure from origin, arrival at cross dock, scan out from cross dock, departure from cross dock, arrival at delivery, scan in at delivery, proof of delivery captured. Each event includes a timestamp, GPS coordinates, and associated data (photos, signatures, item counts).
Pillar 2: Metrics
Aggregated performance data.
Metrics are events aggregated over time. On time pickup rate. On time delivery rate. Average dwell time at cross dock facilities. Average transit time per lane. Damage rate per carrier. These metrics reveal trends that individual events cannot show. A single late delivery is an event. A carrier whose on time rate is declining over 30 days is a metric.
Pillar 3: Alerts
Proactive exception notifications.
Alerts fire when events or metrics deviate from expected behavior. A late pickup triggers an alert. A temperature reading outside the safe range triggers an alert. A carrier whose on time rate drops below threshold triggers an alert. The goal is to notify your team before they have to go looking for problems.
How freight observability works at Warp
Warp's observability stack starts with data collection. Every local 3rd party carrier operates through the Warp driver app, which provides live GPS tracking, scan in and scan out events at every stop, proof of delivery photos, and electronic signature capture. For line haul trucks, ELD integrations provide continuous location data, hours of service status, and route compliance. At Warp operated cross dock facilities, every pallet is scanned in and scanned out.
All of this data flows into our AI backbone, Orbit. Orbit processes events in real time, compares them against expected behavior, and flags anomalies. If a pickup is running late, Orbit alerts the operations team. If a shipment is trending toward a late delivery based on current speed and remaining distance, Orbit flags it before the delivery window is missed.
Shipment event types
Every Warp shipment generates 12+ granular status events. Your system receives each event through webhooks with timestamps and GPS coordinates.
bookedShipment confirmedarrivedAtPickupDriver at originpickupSuccessfulFreight scanned ininRouteToWarehouseEn route to cross dockarrivedAtWarehouseAt cross dock facilitydepartedFromWarehouseLeft cross dockinRouteToDeliveryEn route to destinationarrivedAtDeliveryDriver at destinationdeliveredPOD capturedexceptionIssue flagged by OrbithotSwappedCarrier reassignedcancelledShipment cancelledKey freight observability metrics
On time rate
Pickup and delivery performance.
Percentage of shipments picked up and delivered within the scheduled window. Tracked per carrier, per lane, and across the network. Declining on time rates trigger alerts and carrier performance reviews.
Dwell time
Time at each stop.
How long freight sits at pickup locations, cross dock facilities, and delivery locations. Excessive dwell time indicates operational bottlenecks. Warp tracks dwell at every stop and flags anomalies.
Transit time
Origin to destination duration.
Actual transit time compared to estimated transit time per lane. Consistent overruns indicate carrier or route issues. Transit time metrics help optimize lane selection and carrier assignment.
Comparison to software observability
Logs vs Events
Individual records of what happened.
In software, a log entry records an event (request received, error thrown, response sent). In freight, a scan event records a status change (picked up, departed, arrived, delivered). Both are timestamped, structured, and queryable.
Metrics vs Metrics
Aggregated measurements over time.
In software, metrics track request rate, error rate, and latency percentiles. In freight, metrics track on time rate, damage rate, and transit time. Both reveal trends that individual records cannot show.
Traces vs Shipment traces
The full path from start to finish.
In software, a distributed trace follows a request through multiple services. In freight, a shipment trace follows freight from origin through cross docks to destination. Both help diagnose where things went wrong.
Warp's observability data sources
Warp driver app
Every local carrier reports through it.
Live GPS tracking, scan in and scan out events with barcode and pallet ID scanning, proof of delivery photos, electronic signature capture, pickup and delivery instructions, and route guidance. This is the primary data source for local pickup and delivery observability.
ELD integrations
Continuous line haul visibility.
On all line haul trucks (LTL line haul, truckload, zone skipping, pool distribution). Provides continuous location data, hours of service status, and route compliance. Not just check calls at pickup and delivery. Continuous visibility.
Cross dock scans
Every pallet tracked through facilities.
At 50+ Warp operated cross dock facilities, every pallet is scanned in and scanned out. Inbound arrival, sortation, and outbound departure events provide facility level observability and dwell time metrics.
Frequently asked questions
How is freight observability different from freight tracking?
Freight tracking tells you where a shipment is right now. Freight observability tells you whether the shipment is healthy. Tracking is a single data point (current location). Observability is the combination of events, metrics, and alerts that lets you understand the full state of a shipment and predict whether it will arrive on time and intact.
What are the three pillars of freight observability?
The three pillars are events (scan in, scan out, departure, arrival, delivery), metrics (on time rate, damage rate, dwell time, transit time), and alerts (proactive exception notifications). Together, these three data types give you complete visibility into shipment health across your entire freight operation.
What data sources power freight observability at Warp?
Warp's freight observability is powered by the Warp driver app (live GPS, scan events, proof of delivery photos, electronic signatures), ELD integrations on line haul trucks (continuous location, hours of service status), cross dock facility scans (inbound and outbound), and our AI backbone, Orbit, which processes all of this data to detect anomalies.
Can I receive freight observability data through webhooks?
Yes. Warp pushes shipment events to your system through webhooks as they happen. Each event includes timestamps, GPS coordinates, and scan data. You can register webhook URLs in your Warp dashboard and receive events for every status change, from booked through delivered.
How does freight observability help reduce claims and damage?
Observability data creates an audit trail for every shipment. Scan in photos at pickup document the condition of freight before it moves. Scan out photos at delivery document the condition at receipt. If a damage claim arises, the observability data provides timestamped evidence of when and where the issue occurred.
See every shipment. Catch every exception.
Warp's freight observability stack gives you events, metrics, and alerts across every load. Powered by the Warp driver app, ELD integrations, and our AI backbone, Orbit.