Start by defining the outcome and constraints for each integration point, then keep the shared contract small and put unavoidable customer differences behind explicit connector boundaries. A request that sounds like “one integration” may actually involve several data flows, each with different triggers, latency, security, and support needs.
Define what the integration must do
Write a one-sentence description of the customer outcome before selecting a platform or writing code. Then identify the systems involved, who owns the data, which direction it moves, and which component makes each decision. Classify the work as remote-data access, a command sent to another system, event exchange, or record synchronization.
Scope every integration point separately. Even two links between the same products can differ: one may retrieve data on demand while another sends changes in batches. For remote data, Salesforce Architects frames a useful question: “How do you view, search, and modify data that’s stored outside of Salesforce, without moving the data from the external system into Salesforce?” That describes a federated-access case, not every integration request.
Capture constraints before choosing a pattern
Record operational and technical constraints while the requirement is still being shaped. Salesforce Architects’ Integration Patterns guidance distinguishes real-time, small-volume work from batch processing and identifies timeliness and endpoint capabilities as selection factors.
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#1 Best Overall
- Freshness and latency: How current must the information be, and what response time can the source system actually support?
- Volume and payload: Estimate records, request size, peak load, and whether work fits within an interactive request or requires a batch window.
- Trigger and direction: Identify the user action, event, schedule, or process that starts the flow, and whether data moves one way or both.
- Connectivity and identity: Record network routes, supported protocols, authentication method, and any data-residency or access limits.
- Failure ownership: Name who notices and responds to timeouts, throttling, invalid data, or a downstream outage.
Do not promise interactive response times when source capabilities, data volume, or network conditions cannot support them.
Set the common contract, then isolate variation
Define canonical data and error representations, supported transports, authentication boundaries, versioning expectations, and ownership of mapping changes. A shared format reduces customer-by-customer customization and retesting, according to Microsoft’s guidance on tenant integration and data access.
Rank #2
Different customer formats or connectivity requirements may still be legitimate. Put those differences in a bounded connector or adapter that normalizes data before it reaches the shared process. Keep reusable retrieval, transformation, and transmission steps discrete so that different workflows can compose them without copying an entire flow.
Microsoft’s Power Platform integration patterns guidance cautions against both monolithic flows and excessive centralization. A modular, purpose-built flow can accommodate changing business processes without turning every customer variation into a permanent fork.
Rank #3
Choose a pattern that matches the workflow
| Need | Suitable pattern | Decisions to settle |
|---|---|---|
| A user needs information or an action now, without continuously copying records | On-demand request/response | Response-time limits, timeout behavior, and what status or failure feedback the user sees |
| A change should trigger work, and the systems should not depend on each other being available at the same moment | Event- or message-driven workflow | Event ownership, duplicate handling, ordering needs, and recovery when a consumer is unavailable |
| Separate stores must hold aligned records for business, performance, or regulatory reasons | Synchronization | Direction, conflict rules, watermarks, and recovery from missed or failed updates |
| Large volumes need to move within an agreed processing window | Batch | Window, restart behavior, and protections against contention on source and target systems |
These choices are not interchangeable defaults. Salesforce Architects’ pattern guidance treats data volume, timeliness, endpoint support, and error handling as design factors; Microsoft’s basic enterprise integration reference architecture describes queues and events as ways to decouple systems.
Decide whether a special case belongs in the product
For every customer-specific request, classify it before approving implementation:
Rank #4
- Reusable variation: A documented configuration option or composable step can serve more than one workflow without weakening the shared contract.
- Different connector: The customer requires a distinct transport, schema, or identity integration, but the connector can normalize its behavior at a defined boundary.
- One-customer requirement: The need is genuinely unique. Keep its logic isolated, and make the ongoing cost and retirement path explicit rather than spreading the exception through shared code.
Microsoft notes that tenant-specific code adds paths that are harder to test and modify. Before accepting one, record who pays for implementation and maintenance, which regression cases must pass, how upgrades affect it, who supports it, and when it can be retired. If those owners or conditions cannot be named, the exception is not yet adequately scoped.
Design security and failure handling into the boundary
Specify who may call each API, how identity is verified, how requests are bounded, what is logged, and how secrets are stored. A gateway can centralize API policies; customers should not receive direct credentials to primary data stores. Microsoft’s Azure enterprise integration reference illustrates API management, connectors, authentication, secrets, and messaging as parts of an integration architecture.
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Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Compare options and assign lifecycle ownership
Use the following comparison to expose design trade-offs before committing to an implementation. It is a decision aid, not a scorecard: choose the side that fits the documented workflow, and record the reason where an exception is necessary.
| Decision axis | Option A | Option B | Question to resolve |
|---|---|---|---|
| Timing | Real-time | Batch | How fresh must data be, and what volume can the endpoint handle? |
| Interaction | Request/response | Event/message | Must the caller receive an immediate result, or can processing complete asynchronously? |
| Data access | Copy or synchronize records | Federated access to remote data | Must data be stored locally, or can it remain in the source system? |
| Schema | Shared canonical format | Customer-specific format | Can a connector map the customer format into the shared contract? |
| Implementation boundary | Shared connector | Isolated adapter | Is the variation broadly reusable or specific to one tenant? |
| Failure behavior | Synchronous dependency | Decoupled processing | Can work wait in a queue, or does the user need an immediate outcome? |
| Operations | Shared operational ownership | Customer-specific support | Who monitors health, handles incidents, and coordinates changes? |
| Lifecycle burden | One shared implementation | Separate customer path | Who owns implementation, regression coverage, upgrades, support, and deprecation? |
Before launch, name the owners for schema changes, connector health, customer onboarding, incident response, and deprecation. Salesforce Architects’ Architecture Patterns recommends explicit interfaces, reusable components, configuration-driven behavior, and separation of integration concerns from core domain logic. Treating those boundaries and owners as part of the design helps keep a customer exception from silently becoming everyone’s permanent maintenance burden.
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