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Keep plant functions at the edge when they need a fast local response, must keep working through cloud outages, or can reduce unnecessary data transfers there. Use cloud services for work that can tolerate network delay and benefits from shared analytics, enterprise integration, or longer-term storage. Most plants need a split by function, not a single choice for all data.
How to decide where each plant function belongs
Apply these questions to each workload—such as machine monitoring, production execution, reporting, or enterprise-system updates—rather than deciding where all plant data should live.
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- How quickly must it respond? If a network round trip or brief cloud interruption could disrupt an operation, keep the decision or immediate processing on premises. AWS says some manufacturing execution system (MES) functions have low latency requirements and are better suited to on-premises execution. AWS Prescriptive Guidance: Industrial edge computing.
- Must it keep operating when cloud connectivity is intermittent? If the process cannot pause or wait for a connection, preserve the required processing and data path locally. AWS identifies intolerance of intermittent cloud connectivity as a reason to run relevant functions on premises.
- Does all the data need to leave the plant? If not, filtering, aggregating, or selecting data near its source can reduce unnecessary transfers. AWS lists bandwidth optimization among industrial edge considerations. AWS Industrial IoT Architecture Patterns.
- Would pooled compute, shared analytics, enterprise integration, or extended retention help? If the task tolerates network delay, cloud components can support reporting and analytics, enterprise updates, and longer-term storage.
- What security, regulatory, and operational constraints apply? Map permitted data flows, the OT network boundary, device capabilities, and connectivity requirements before choosing a location. Neither location is automatically safer; plant-side devices and connections still need protection and lifecycle management.
This is a qualitative test, not a scoring formula. The cited guidance does not set a universal latency, bandwidth, or data-volume threshold. Define requirements for the actual process and plant.
Which work should stay on premises?
Keep the parts of a workload local when they have immediate operational consequences or need to remain available without cloud connectivity. AWS gives MES functions that guide work in progress as an example: some require low latency and cannot tolerate intermittent cloud connections. In those cases, the function that makes or supports the immediate decision belongs close to the operation.
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Local processing can also make sense when sending every raw reading upstream is unnecessary. An edge system can select or aggregate data before transfer, while retaining the information needed locally for the process. That is a design choice to validate against the plant’s analysis, monitoring, and retention needs—not a reason to discard data indiscriminately.
Which work fits the cloud?
Cloud components are a stronger fit for work that can tolerate delay and gains value from centralization. AWS identifies product lifecycle management (PLM) updates, enterprise resource planning (ERP) confirmations, data-lake reporting, and analytics as cloud-suited examples. A plant can send selected operational data for fleet-wide analysis or longer retention while keeping time-sensitive functions local.
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Microsoft’s OPC UA reference solution illustrates an edge-to-cloud ingestion pipeline that can feed different analytics back ends, including Azure Data Explorer, Databricks, and Fabric. This is an architecture example, not a requirement to use a particular cloud service. Microsoft Learn: OPC UA reference solution.
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Compare the trade-offs by function
| Decision factor | Edge tends to help when… | Cloud tends to help when… |
| Response time | A fast local response is required or latency tolerance is low. | The task can tolerate network delay. |
| Connection resilience | The operation must continue through intermittent cloud connectivity. | The function can pause, queue work, or accept delayed transfer. |
| Data transfer | Local selection or processing avoids unnecessary bandwidth use. | Data needs central combination or analysis and transfer is acceptable. |
| Compute and retention | A bounded local function is sufficient. | The workload benefits from cloud scale, analytics, or extended storage. |
| Integration | The function must interact with plant OT locally. | It updates systems such as PLM or ERP, or supports shared reporting. |
| Security and governance | Plant-side handling is required by local constraints. | Approved centralized services meet the organization’s access and data controls. |
These are tendencies, not claims that one location is always safer or cheaper. AWS describes hybrid manufacturing workloads and multiple connectivity approaches; the appropriate design depends on the site’s process and controls. AWS: Security Best Practices for Manufacturing OT.
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What an edge gateway does—and does not do
An industrial edge gateway is an intermediary processing and integration point between plant operational technology (OT) and cloud services. It can connect older OT systems that lack some security capabilities, but deploying a gateway does not decide which functions belong locally or make the overall system secure by itself. AWS describes gateways as one component in an industrial edge architecture. AWS Industrial IoT Architecture Patterns.
Before selecting a gateway, check that its supported industrial protocols, environmental rating, compute and storage capacity, and security controls match the plant’s requirements. The cited guidance establishes the gateway’s architectural role; it does not verify a particular model’s suitability.
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Secure both sides of the boundary
A hybrid design expands the number of components and connections that need protection. AWS guidance calls for attention to edge devices and networks, secure communications, software updates, logging, monitoring, auditing, and network segmentation. A cloud connection does not remove the need to protect the plant side. AWS Prescriptive Guidance: Providing secure edge computing and connectivity.
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1Scan for outdated or missing drivers - takes under a minute2Repair Windows errors before they cause bigger problems3Fix the driver behind crashes, sound loss and screen glitches- Define which OT data may cross into IT or cloud environments, and control those flows.
- Use secure communications and appropriate industrial protocols.
- Segment networks so a connection between plant systems and cloud services does not imply unrestricted access.
- Plan how edge devices will receive updates and how their activity will be logged, monitored, and audited.
Microsoft warns that some defaults in its OPC UA reference solution favor ease of deployment over hardening and should be addressed before production. Treat reference architectures as starting points to review against production security requirements, not as a finished security prescription.
Turn the test into a deployment plan
- List functions, not just data sources. Separate immediate control or production execution from monitoring, reporting, analytics, and enterprise updates.
- Record the process requirement for each function. Specify acceptable response delay, what must continue during a cloud outage, and whether work can queue until connectivity returns.
- Choose a location for the processing decision. Keep latency-sensitive or outage-intolerant decisions local; place delay-tolerant work in the cloud when centralized capabilities are useful.
- Decide what crosses the boundary. Identify raw readings or events that need to move, and where local selection or aggregation can avoid unnecessary transfer without undermining analysis or retention needs.
- Review the architecture and its safeguards. Check OT connectivity, gateway capabilities, permitted data flows, segmentation, secure communications, and device maintenance before deployment.
Do not assign a fixed percentage of plant data to either location. The official architecture guidance cited here offers workload criteria, not a universal cutoff; the right split follows from each process’s response, availability, transfer, integration, and governance requirements.
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