Cloud Infrastructure & Compute3 min readUpdated September 2026

AWS or Google Cloud for a Precision Contract Manufacturer's Systems

A precision contract manufacturer's cloud decision has to account for something most software companies never think about: a physical shop floor with ERP, MES and quality systems that can't tolerate the same kind of experimentation a pure software team takes for granted. Here's a checklist of the pitfalls that trip up manufacturers moving these systems to AWS or Google Cloud, and what to check before you commit.

Vendors Covered in this Article

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Why is shop-floor connectivity different from a typical web app?

Real-time machine control and safety systems generally stay on the shop floor, on dedicated industrial networks, not in the cloud, and that's the right call for latency and safety reasons. What belongs in the cloud is everything downstream of that: production scheduling, quality records, ERP and MES data, and analytics on machine telemetry. Draw this line clearly before you start moving anything, since blurring it is how manufacturers end up trying to run latency-sensitive control logic somewhere it doesn't belong.

Pitfall: underestimating ERP and MES integration work

Most contract manufacturers run an established ERP or MES platform that predates any cloud migration conversation, and connecting it cleanly to AWS or Google Cloud is real integration work, not a simple lift-and-shift. Check what your specific ERP or MES vendor already supports for cloud connectivity before assuming either platform, since vendor-specific connectors and certified architectures vary and can save months of custom integration work.

Why is chasing high availability a pitfall where it isn't needed?

Production scheduling and quality record systems benefit from real reliability, but they don't need the same availability tier as a payment system, and chasing an unnecessarily high tier adds cost without a matching benefit for a system that can tolerate a short, planned maintenance window overnight. Match your availability target to how the shop floor actually uses each system, not to a generic best-practice number.

Pitfall: not budgeting for the staffing this actually requires

Manufacturers often underestimate what it costs to hire or retain the operations talent who can bridge shop-floor systems and cloud infrastructure, and a median salary of $105,770 for a general operations manager role gives a useful anchor for budgeting this properly rather than treating it as a rounding error in the project plan1. Underbudgeting this role is a common reason cloud migration projects stall in manufacturing.

Pitfall: ignoring how a bad change on the cloud side disrupts the shop floor

A bad deploy to a scheduling system that feeds the shop floor can cascade into real, physical disruption, not just an error page. Test changes against a staging environment that reflects real production scheduling data, and give shop-floor supervisors a clear, simple way to flag when something looks wrong before it cascades into a missed shipment.

Pitfall: forgetting that a quality audit will ask about this too

Precision manufacturing clients typically operate under a quality management standard that includes recordkeeping requirements for traceability, and an auditor reviewing your quality records will want to understand how they're stored, backed up and protected from unauthorized change once they move to the cloud. Loop your quality team into the infrastructure decision early rather than presenting them with a finished system to audit after the fact, since a quality process built without their input often needs costly rework once an actual audit surfaces a gap.

Document the chain of custody for quality records explicitly, from the shop floor sensor or inspector's tablet through to long-term cloud storage, so an auditor's questions have a clear, pre-written answer rather than requiring someone to reconstruct the path on the spot.

Pitfall: assuming your customers care which cloud you use

A precision manufacturer's own customers rarely ask which cloud platform runs behind the quality portal or the order status page, but they do care about the outcomes it produces: accurate quality records, on-time shipment visibility, and no surprises when an audit finds a gap. Keep this in mind when a vendor's sales pitch tries to make the platform choice itself the headline feature, since the platform is infrastructure, not a selling point your own customers are evaluating.

Spend the marketing effort on the outcomes instead: on-time delivery rates, audit pass records, and responsiveness when something needs correcting. Those are the numbers a prospective customer actually cares about, regardless of which cloud produced them, and they're the numbers that actually win the next contract, far more than a vendor logo on a proposal ever will.

One more thing worth checking before you finalize anything

Ask your existing ERP or MES vendor directly whether they've certified or specifically recommend one platform over the other for your exact configuration, since vendors sometimes have real, undisclosed reasons for a preference, like a support arrangement or a tested reference architecture that saves you real integration time either way.

Check these items before you finalize the move:

  • Keep real-time machine control and safety systems on the shop floor, and move only scheduling, quality records, ERP and MES data and telemetry analytics to the cloud.
  • Ask your ERP or MES vendor whether it certifies or recommends one platform for your exact configuration.
  • Match each system's availability target to how the shop floor actually uses it.
  • Budget for operations talent who can bridge shop-floor systems and cloud infrastructure.
  • Involve your quality team early so auditors can see how records are stored, backed up and protected from unauthorized change.
Executive Capability Standard

What Good Looks Like

A manufacturer can point to a clear, documented line between what stays on the shop-floor network and what runs in the cloud, with a named owner for the integration between them.

Building The Capability (5-Stage Skill Ladder)

1. Learn:Map every shop-floor system currently feeding data upstream and where that data actually needs to land.
2. Do Manually:Run scheduling and quality-record changes through a manual review by a shop-floor supervisor before they go live.
3. Delegate:Assign a dedicated operations or engineering owner for the connection between shop-floor systems and cloud infrastructure.
4. Automate:Automate telemetry ingestion from machine sensors into your analytics layer instead of relying on manual exports.
5. Buy:License a certified ERP or MES cloud connector from your existing vendor rather than building custom integration from scratch.

How to Get Started

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Frequently Asked Questions

Should we move our MES system to the cloud at all?

Many manufacturers keep time-sensitive control logic on-premises and move the data and reporting layer to the cloud, which captures most of the analytics and visibility benefit without the latency risk of moving real-time control off the shop floor.

How do we choose between AWS and Google Cloud for IoT and machine telemetry?

Check what your specific machine controllers and sensors already support for connectivity, since compatibility with your existing equipment matters more here than a general platform preference. Some equipment vendors have stronger existing integrations with one platform than the other.

What's a realistic budget for the staff needed to run this integration?

Beyond the cloud infrastructure cost itself, budget for a dedicated operations or engineering role to own the integration between shop-floor systems and the cloud layer. Treating this as a part-time addition to an existing role's workload is a common way these projects stall.

Sources

Where we quote a benchmark, we show its source. Other figures in this guide are estimates or general guidance, so check them against your own numbers.

  1. Annual wage, General and Operations Managers (SOC 11-1021), US all industries. BLS OEWS May 2025, 2025.

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