Cloud-first has been the default for so long that 'we'll run it locally' sometimes sounds like a step backwards. It often isn't. For the kind of systems we build — retail installations, brand activations, kiosks, live events — edge is the right answer more often than the industry would have you believe. After ten years of installation work, we have a framework.
When edge is the right call
- 01 Privacy — pixels and PII never leaving the building.
- 02 Latency — interactive installations that need <50ms response budgets.
- 03 Resilience — venues where the internet is a suggestion, not a guarantee.
- 04 Cost — when the cloud bill for streaming raw data dwarfs the cost of a small box on-site.
- 05 Regulation — financial, medical, education environments where data residency is non-negotiable.
- 06 Compliance — venues with their own IT security policies that ban outbound traffic by default.
The edge-vs-cloud decision matrix
| Concern | Cloud-first | Edge-first | Hybrid |
|---|---|---|---|
| Latency-critical interaction | Risky | Default | Edge for interaction, cloud for analytics |
| Identifiable / sensitive data | Compliance risk | Compliant by design | Anonymise at edge, send aggregates |
| Venue network is patchy | Bad | Default | Edge with cloud sync when available |
| Heavy data, light interaction | Default | Wasteful | Edge processing, cloud archive |
| Many distributed sites | Easier ops | Heavier ops | Edge per site, cloud control plane |
| Frequent software updates | Easier | Harder | Containerised at edge, push from cloud |
Decision matrix — edge vs cloud vs hybrid for installation work.
Hardware we deploy
- 01 Mac mini M2/M4 — our default for any installation that needs MacOS-tied software, Final Cut workflows, or simple admin via Apple Remote Desktop.
- 02 Intel NUC / Beelink mini PC with Linux — when the workload is Linux-native or the client's IT has a Windows / Linux preference.
- 03 Raspberry Pi 5 for low-spec installations — signage, kiosk shells, IoT bridges.
- 04 Jetson Orin for on-prem computer vision — when we need GPU-class inference without the cloud round-trip.
- 05 Arduino / ESP32 for the bridge layer — the silicon that turns API calls into LED flips.
What the conversation looks like
We start every installation engagement with the same question: what has to leave this building, and what doesn't? The answer determines everything else — hardware spec, network design, what we even need an account in the cloud for. It also tends to make the legal team much happier.
" On-prem isn't a step backwards. Sometimes it's the entire reason the project is possible.
Hybrid patterns we keep reaching for
- 01 Edge processing + cloud archive — heavy lifting happens locally, anonymised metrics ship up overnight.
- 02 Edge inference + cloud training — models train in the cloud, deploy to edge devices once a month.
- 03 Edge realtime + cloud control plane — devices run autonomously, ops team manages them from a central dashboard.
- 04 Edge capture + cloud transcode — raw video stays local, processed previews uploaded for review.
- 05 Edge fallback for cloud-first products — local cache means the UX survives a network blip.
Why teams resist edge
- 01 Operational pain. A box on-site needs visiting when it breaks.
- 02 Software update story is harder. SSH + containerised deploy is the answer.
- 03 Hiring and skill profile — fewer engineers have run real on-prem infrastructure in the last decade.
- 04 'The cloud is the default' — three years of conference talks have made cloud-first feel mandatory.
- 05 Asset management — keeping track of devices across many sites is a discipline most teams haven't built.
We solve most of these with operational discipline. Devices have a known build, a remote management agent, a clear update channel, and an inventory. Edge is harder to operate — and dramatically better for the user experience when it's the right call.