1
Define Workload Characteristics
Before debating edge vs. cloud, get specific about what the cameras actually see and how fast you need an answer.
For: CTOs, Plant IT Leads, Vision Architects
✓
Inference latency budget (ms)Document the maximum acceptable end-to-end latency per use case. Anything under 100ms typically rules out pure cloud.
✓
Frame rate and resolution per cameraList FPS and megapixels per stream. A 4K@30fps line generates ~12 Mbps — multiply by camera count to size bandwidth.
✓
Model complexity tierClassify each model as light (MobileNet-class), medium (YOLO-class), or heavy (transformer-based). This drives GPU vs. NPU choice.
✓
Decision criticalityRate each use case: advisory, quality-gate, or safety-interlock. Safety-interlocks must run on-prem with deterministic timing.
2
Score the Three Architectures
Use this matrix to rate edge, cloud, and hybrid across the criteria that matter most to your plants. Score 1–5 per cell, weight by priority.
For: Architecture Review Boards
Criterion (weight 1–5)
Edge
Cloud
Hybrid
Latency under 50ms
__ / 5
__ / 5
__ / 5
Bandwidth cost at scale
__ / 5
__ / 5
__ / 5
Model update velocity
__ / 5
__ / 5
__ / 5
Data residency / sovereignty
__ / 5
__ / 5
__ / 5
Plant network reliability
__ / 5
__ / 5
__ / 5
5-year total cost of ownership
__ / 5
__ / 5
__ / 5
Operational complexity
__ / 5
__ / 5
__ / 5
3
Run the Cost & Capacity Math
Walk through these calculations for each candidate plant before committing to a topology.
For: Finance Partners, Solution Architects
01Sum egress bandwidth per shift
Cameras × bitrate × active hours. If sustained egress exceeds 250 Mbps per site, cloud-first is rarely defensible.
02Calculate GPU-hours per model per day
Multiply inference calls by ms-per-call. Convert to GPU-hours and price against both on-prem amortization and cloud GPU SKUs.
03Add storage and retention costs
Audit, training reuse, and incident review each have different retention windows. Tier hot/warm/cold explicitly.
04Model failure-mode cost
Estimate the cost of one hour of vision downtime per line. This sets the bar for redundancy investment.
05Compare 5-year TCO, not sticker price
Include refresh cycles, MLOps headcount, network upgrades, and licensing. Edge wins on opex; cloud wins on capex flexibility.
4
Pressure-Test for Operations
A topology that scores beautifully on paper can still fail at 3 a.m. on a Sunday. Check these before approval.
For: Plant Operations, SRE Leads
✓
Documented MTTR targetSet a recovery time objective per architecture. Edge nodes typically demand <30 min on-site swap; cloud regions need failover plans.
✓
Model rollout and rollback pathConfirm canary deployment to a single line, then ringed expansion. One-click rollback is non-negotiable.
✓
Observability across the stackCamera health, inference latency, drift detection, and prediction confidence must surface in one dashboard.
✓
Security posture per zoneScore IEC 62443 zone segregation, secrets management, and signed model artifacts for each architecture option.
5
Decide, Document, and Stage the Rollout
The matrix is only useful if it converts into a decision your board, ops team, and vendors can all align behind.
For: Executive Sponsors, Program Managers
01Lock the weighted score
Multiply each architecture's raw scores by criterion weights. The winning topology should exceed runner-up by ≥15%.
02Write a one-page decision memo
Document trade-offs you knowingly accepted. Future-you will need this when reality shifts.
03Pilot one plant for 90 days
Measure against the latency, cost, and uptime targets you set in sections 1–4. Don't roll out to plant #2 until pilot KPIs are green.
04Plan the fleet rollout in waves
Group plants by network maturity and use-case criticality. Ship to the easiest three first, learn, then scale.
Pro Tip
Hybrid is the right answer more often than people admit — but only when the split is intentional. Define exactly which inferences run at the edge (latency-sensitive, safety-critical) and which run in the cloud (analytics, retraining, fleet-wide drift detection). A vague "hybrid" usually means duplicated cost and ambiguous ownership.
Get the editable scoring template
Download the full matrix as a working spreadsheet — pre-weighted, with formula-driven scoring, vendor comparison tabs, and a board-ready summary view.
Download the Matrix