What is TechFabric Radar?
Governed mission control for data and ML workloads on Databricks. Monitors with SLOs, evidence-backed anomalies, and gated interventions.
TechFabric Radar is a governed mission control for running data and ML workloads, pipelines, experiment runs, model deployments, and the cost, quality, and freshness anomalies they produce, built as a TechFabric family vertical on Databricks. It watches what is live, detects when reality breaches declared SLOs, and makes every intervention a governed, auditable action.
Radar is deliberately thin. Your Databricks workspace stays the system of record for telemetry and truth, and system tables, MLflow and Unity Catalog are the sources Radar reads. Radar adds the three things a workspace does not give you on its own.
- Declared monitors with SLOs. A watched workload plus its cost ceilings, freshness lags, and quality floors, declared as a governed action so the watch list itself is audited.
- Evidence-backed anomalies, TechFabric Experiments evaluators over system tables and MLflow cross a threshold and raise an anomaly with the verdict attached, into an inbox humans or a finite triage agent can work.
- Governed interventions. Pause a pipeline, cancel a run, or quarantine a model through TechFabric Platform actions with blast-radius policy gates, durable execution, and an evaluator that confirms recovery before the anomaly resolves.
Every state transition is a TechFabric Platform action invocation. Raw telemetry is the one deliberate exception. It flows append-only and never becomes a mutation path.
Start here
Quickstart
Declare your first monitor over a live workload and watch the detection loop start.
Architecture
Monitors, anomalies, and interventions, the concepts and the loop that connects them.
Deployment
How Radar's docs, console, and control plane are deployed across Cloudflare and Databricks.
What Radar owns, and what it delegates
Radar owns the monitoring domain. That is the monitor registry, the anomaly lifecycle, the intervention action definitions, the projections and the console. It delegates everything else to the Fabric product that owns it.
| Responsibility | Product |
|---|---|
| Governed mutations, policy, state machine, audit, recovery | TechFabric Platform |
| Databricks transport, Temporal intervention workflows, triage agents | TechFabric Harness |
| Evaluators over system tables and MLflow, anomaly evidence | TechFabric Experiments |
| Delivery and promotion of Radar itself | TechFabric Runway |
| Monitoring domain, anomaly inbox, intervention definitions, console | TechFabric Radar |
Harness builds the agents. Experiments judges them. Runway ships them. Tower flies the missions. Radar watches everything in the air. Platform keeps everyone honest.
Radar does not implement a second orchestrator, an anomaly-detection engine, a metrics TSDB, or a bespoke approval queue. Temporal stays the runtime of record; Radar signals it, never replaces it.
Tower steers agents; Radar steers workloads
Fabric Tower is mission control for human-steered agent squads; Radar is mission control for machine-run workloads. They share the Platform runtime, the event log, and the console shell, nothing else. When a Tower mission needs to act on a workload, its agent calls Radar's governed intervention actions; Tower never grows its own intervention machinery.