Capabilities

Fleet Orchestration

Device/resource registry, configuration at scale, and orchestrated deployments across many sites and controllers.

Design intent

Use this lens when adopting Fleet Orchestration: define success criteria, start narrow, and scale with safe rollouts and observability.

Fleet scale requires fast answers: what’s running, what changed, what’s degraded
Reconciliation prevents drift from becoming an incident multiplier
Progressive rollouts keep blast radius low

What it is

The backend acts as the fleet control plane: it persists configuration and versions designs, and orchestrates deployments to edge devices.

Design constraints

Fleet scale requires fast answers: what’s running, what changed, what’s degraded
Reconciliation prevents drift from becoming an incident multiplier
Progressive rollouts keep blast radius low

Architecture at a glance

Fleet control plane defines desired state (config + versions) across devices/resources
Agents reconcile desired vs actual; platform surfaces drift and rollout state
Safe operations require policies, gates, and deterministic rollback paths
This is a capability surface concern: scale changes how you design processes

Typical workflow

Define scope and success criteria (what should change, what must stay stable)
Create or update a snapshot, then validate against a canary environment/site
Deploy progressively with health/telemetry gates and explicit rollback criteria
Confirm acceptance tests and operational dashboards before expanding

System boundary

Treat Fleet Orchestration as a capability boundary: define what success means, what is configurable per site, and how you will validate behavior under rollout.

Example artifact

Implementation notes (conceptual)

topic: Fleet Orchestration
plan: define -> snapshot -> canary -> expand
signals: health + telemetry + events tied to version
rollback: select known-good snapshot

What it enables

Consistent configuration and rollout across sites
Repeatable deployments tied to versioned snapshots
Operational visibility into fleet health and status

Engineering outcomes

Fleet scale requires fast answers: what’s running, what changed, what’s degraded
Reconciliation prevents drift from becoming an incident multiplier
Progressive rollouts keep blast radius low

Quick acceptance checks

Ensure every site/device/resource has stable identifiers and metadata
Plan deployments from snapshots and track desired vs actual state

Common failure modes

Drift between desired and actual running configuration
Changes without clear rollback criteria
Insufficient monitoring for acceptance after rollout

Acceptance tests

Verify the deployed snapshot/version matches intent (no drift)
Run a canary validation: behavior, health, and telemetry align with expectations
Verify rollback works and restores known-good behavior

Deep dive

Practical next steps

How teams typically turn this capability into outcomes.

Key takeaways

Fleet scale requires fast answers: what’s running, what changed, what’s degraded
Reconciliation prevents drift from becoming an incident multiplier
Progressive rollouts keep blast radius low

Checklist

Ensure every site/device/resource has stable identifiers and metadata
Plan deployments from snapshots and track desired vs actual state
Use canaries and staged rollouts for fleet-wide changes
Build fleet views that surface drift, health, and rollout status first

Next steps

Common questions

Quick answers that help align engineering and operations.

What does fleet management need to answer every day?

“What is running where?”, “What changed recently?”, and “Which sites are degraded/offline?” If those are fast, operations scales.

What is drift and why is it dangerous?

Drift means sites diverge from the intended snapshot/config. It creates irreproducible behavior and makes incidents hard to diagnose. Detect and reconcile it continuously.

How do we roll out safely across many sites?

Progressive rollouts + health/telemetry gates + quick rollback to previous snapshots.