See the fleet as it actually is. Operate it with confidence.

Core product workflows for fleet telemetry, device visibility, topology, alerting, incidents, monitoring and audit are already in place.

The Rust agent, Next.js dashboard and Python platform services are built around a production deployment model rather than a prototype stack.

The product is now in deployment preparation, infrastructure hardening and early commercial onboarding rather than foundational product invention.

Collect The Signals

Onyx captures telemetry, logs, device health and reachability across distributed environments without assuming perfect connectivity or ideal operating conditions.

Map The Relationships

Topology and infrastructure context help operators understand how devices, networks and operational dependencies relate instead of treating the fleet as isolated endpoints.

Detect The Drift

Alerting, health signals and investigative context help teams surface degraded devices, abnormal behaviour and fleet changes earlier.

Operate The Fleet

Incidents, monitoring, audit and device operations surfaces turn observability into an operating layer that supports response and ongoing fleet control.

Fleet Visibility With Real Context

Onyx brings telemetry, logs, health signals and device relationships into one operational view so teams can reason about the fleet as a system rather than a list of endpoints.

Operational Awareness Beyond Dashboards

Topology, alerting, incidents, monitoring and device-level investigation work together, helping operators move from signal to action faster.

Resilient Edge Collection

The agent and collection model are built for real distributed environments, with buffering, failover and self-healing behaviour that support continuity when connectivity is imperfect.

Fragmented Visibility

Teams often have telemetry, logs and alerts, but not a coherent fleet picture that shows what is unhealthy, where it sits and how it relates to the wider environment.

Slow Incident Context

Operators lose time stitching together dashboards, logs and network knowledge before they can understand what is really happening during a fleet issue.

Blind Spots At The Edge

Distributed and field infrastructure often sits outside the assumptions of centralised observability tooling, leaving gaps in visibility and confidence.

Collection That Breaks Under Real Conditions

Many environments need collection and transport layers that tolerate imperfect connectivity, endpoint churn and operational variance instead of failing under them.

Earlier Detection Of Real Issues

Operators get a clearer picture of degraded devices, blind spots and abnormal fleet behaviour before those issues become larger operational problems.

More Useful Context During Response

Telemetry, logs, topology and device state stay closer together, helping teams move from alert to understanding with less manual stitching across tools.

Stronger Control Across Distributed Environments

Onyx improves confidence in environments where infrastructure is geographically distributed, operationally diverse and difficult to reason about from a single vantage point.

Separate Dashboards For Separate Signals

Many teams manage fleet state through disconnected dashboards for telemetry, logs, networking and incidents, which makes real operational understanding slower than it should be.

Centralised Monitoring Assumptions

Traditional monitoring stacks often assume stable connectivity and datacentre-like conditions that do not reflect how distributed infrastructure behaves in practice.

Topology And Device Context Outside The Workflow

Operators frequently need human memory, separate documentation or external tools to understand how the fleet is connected and where a problem actually sits.

Fleet-Native By Design

Onyx is built for distributed infrastructure and edge fleets where device state, topology and operational conditions have to be understood together, not approximated from centralised infrastructure assumptions.

Operationally Useful Context

Telemetry, logs, topology, alerts and investigation surfaces support real operator workflows, not just passive monitoring.

Resilient Collection Model

The agent and collection pipeline are designed for continuity under imperfect connectivity, using buffering, failover and self-healing rather than assuming ideal conditions.

Operational Analysis With Context

Intelligence workflows can reason over telemetry, topology and operational history to help teams interpret fleet state with more context than dashboards alone.

Fleet Understanding That Compounds

As operators build a richer picture of device state, topology and recurring issues, Onyx becomes a stronger system for interpreting what matters across the fleet.

Production-Oriented Assistance

The intelligence layer supports operational investigation and decision-making inside the platform rather than acting as a disconnected assistant beside it.

AWS-Native Delivery

Onyx uses an AWS deployment model that supports secure ingress, fleet-facing endpoints and production infrastructure control for distributed environments.

Resilient Data Path

The collection and platform model preserve operational continuity across telemetry ingest, buffering, transport and backend services when conditions are less than perfect.

Platform Architecture For Operations

Dashboard, APIs, agent services and backend telemetry infrastructure are structured to support serious fleet operations, not just visualisation.