AWS integration patterns for Salesforce — pick between Amazon AppFlow, Event Relay → EventBridge, Amazon S3 ingestion paths, and direct Apex → Lambda callouts. Decision matrix + AppFlow deep dive (Salesforce as source / destination, OAuth Authorization-Code vs JWT, REST vs Bulk 2.0 API, 15 GB / run cap). NOT for the Event Relay setup details themselves (see integration/event-relay-configuration), NOT for MuleSoft, NOT for in-AWS architecture (Lambda code style, EventBridge bus topology).
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AWS integration patterns for Salesforce — pick between Amazon AppFlow, Event Relay → EventBridge, Amazon S3 ingestion paths, and direct Apex → Lambda callouts. Decision matrix + AppFlow deep dive (Salesforce as source / destination, OAuth Authorization-Code vs JWT, REST vs Bulk 2.0 API, 15 GB / run cap). NOT for the Event Relay setup details themselves (see integration/event-relay-configuration), NOT for MuleSoft, NOT for in-AWS architecture (Lambda code style, EventBridge bus topology).
["salesforce to aws integration which service should I use","amazon appflow salesforce connector setup oauth","should I use appflow or event relay for cdc","salesforce s3 file integration ingestion paths","apex callout to aws lambda pattern","amazon connect service cloud voice integration"]
["Direction of data flow (Salesforce → AWS, AWS → Salesforce, or bidirectional)","Latency requirement (real-time event, scheduled batch, on-demand)","Volume estimate (records / day; total bytes / run)","Whether Change Data Capture is already enabled in the source org"]
outputs
["Recommendation: which AWS integration service (AppFlow / Event Relay / S3 connector / Apex callout / Service Cloud Voice + Connect)","Auth model decision (OAuth Authorization Code vs JWT Bearer Flow vs IAM role)","Specific limits the chosen path will hit and how to budget around them"]
dependencies
[]
version
1.0.0
author
Pranav Nagrecha
updated
2026-05-01T00:00:00.000Z
AWS Salesforce Integration Patterns
When a Salesforce org needs to talk to AWS — read S3 files, sync records to a
data lake, react to a contact event with a Lambda, route a call through Amazon
Connect — there are five distinct managed paths and a sixth do-it-yourself
fallback. Picking the wrong one costs operational debt: a custom Apex callout
where AppFlow would have handled it, or AppFlow where Event Relay's at-least-once
durability is the actual requirement.
This skill is the decision layer. It will not re-derive the Event Relay
setup steps — that lives in integration/event-relay-configuration. It will not
explain MuleSoft (different decision tree).
Before Starting
Confirm whether the integration is Salesforce → AWS, AWS → Salesforce, or bidirectional. The first two have very different recommended paths; bidirectional usually means stitching two unidirectional flows.
Check whether Change Data Capture is already enabled in the source org. AppFlow's event-driven trigger and Event Relay both need it — turning it on retroactively means a backfill plan.
Note the volume budget. AppFlow caps at 15 GB / 7.5 M records per single run (Salesforce as source, ~2 KB / record); above that you split across flows or move to Event Relay + downstream batch.
Get the AWS account id and region of the consuming services. Cross-region traffic costs and PrivateLink availability vary by region.
Core Concepts
The five managed AWS integration paths
Amazon AppFlow (Salesforce connector) — managed bidirectional sync. Salesforce can be source, destination, or both. Scheduled / on-demand / event-driven (CDC) triggers. AWS-managed connected app for OAuth, or bring-your-own connected app for JWT. Right when you want declarative record-level sync without writing code.
Event Relay → Amazon EventBridge — Salesforce streams Platform Events and CDC events to an EventBridge bus on your AWS account. At-least-once delivery, replay, 72-hour buffer. Right for event-driven architectures where you want AWS-side fan-out (multiple Lambdas, Step Functions, etc.) reacting to Salesforce events.
Amazon S3 ingestion (Data Cloud connector or Files Connect) — Data Cloud's S3 connector ingests structured files into Data Model Objects; Files Connect surfaces S3 as external file references inside Salesforce. Right when the source of truth is files in a data lake.
Apex → Lambda callout — Salesforce makes an HTTP request to a Lambda Function URL or API Gateway endpoint via Named Credential.
Right when you need a synchronous response inside a transaction (validation, enrichment, screen-flow callout).
Service Cloud Voice + Amazon Connect — telephony integration. Amazon Connect routes the call; contact flows can invoke Lambda; Salesforce records the contact + transcript. Right for voice channel; not a generic data-integration path.
Why the choice usually comes down to two axes
Direction × Latency. Real-time event-driven from Salesforce → Event Relay. Scheduled batch in either direction → AppFlow. Synchronous request-response from Salesforce → Apex callout to Lambda. AWS-side data lake to Salesforce → S3 → Data Cloud or AppFlow source-from-S3.
Code budget. AppFlow and Event Relay are zero-Apex. Lambda callouts and custom S3 work require code, error handling, monitoring, and tests on the Salesforce side.
Decision Guidance
Situation
Recommended Approach
Reason
React to a Salesforce record change in AWS within seconds
Event Relay → EventBridge
At-least-once, replay, no Apex code. Configure once.
Nightly sync of accounts/contacts to Redshift
AppFlow scheduled flow
Field mapping in console, built-in retry, no Apex.
Bulk-import 50 M rows from S3 into Data Cloud
Data Cloud S3 connector
Native ingestion to DMOs; AppFlow caps below this volume.
Inline credit-check during opportunity save
Apex callout to Lambda Function URL
Need synchronous response inside transaction.
Phone agent answers a Service Cloud case
Service Cloud Voice + Amazon Connect
Telephony is the channel — generic data-integration paths don't apply.
Salesforce reads a small JSON file from S3 once a day
Apex callout with Named Credential OR a daily AppFlow flow
Either works; pick AppFlow if you want zero-code, Apex if you need the data inside a custom transaction.
Bidirectional account sync with a partner CRM hosted on AWS
AppFlow source + AppFlow destination
Two flows; let AppFlow handle field mapping in both directions.
Stream high-volume Platform Events to multiple AWS services
Event Relay → EventBridge → fan-out
EventBridge handles fan-out natively; one rule per target.
Common Patterns
Pattern A — Event-driven sync via Event Relay
When to use. Real-time reaction in AWS to a Salesforce change. The
canonical example is "when an Opportunity moves to Closed-Won, kick off
Lambda + Step Functions to provision downstream resources."
How it works. Configure the Pub/Sub API channel, define a Relay Config
that points at the AWS event-bus partner-source, accept the source in
EventBridge, attach rules. Salesforce delivers events at-least-once with a
72-hour replay window. See integration/event-relay-configuration for the
full setup recipe.
Why not the alternative. A Platform-Event-trigger Apex class doing the
HTTP callout to AWS works but reinvents at-least-once delivery,
back-pressure handling, and retries. Event Relay is a managed equivalent.
Pattern B — Scheduled batch sync via AppFlow
When to use. Hourly / nightly snapshot of Salesforce records to a data
lake, warehouse, or another SaaS. Or pull-from-S3 to upsert Salesforce
records by external id.
How it works. AppFlow connection (OAuth Authorization-Code is the
recommended starting auth — AWS manages the connected app on its side; JWT
when you need server-to-server with no interactive consent). Pick API
Preference (Automatic is right for most loads — REST under 1 M source
records, Bulk 2.0 above; Bulk only if compound fields are not in scope).
Cap is 15 GB or ~7.5 M records per single run; split larger workloads.
Why not the alternative. Hand-rolled Apex Batch + ScheduledApex works
but needs monitoring, retry, and CDC-style change detection. AppFlow is
the managed version of all of that.
Pattern C — Apex callout to Lambda
When to use. Inside a transaction you need an external decision —
fraud check, real-time enrichment, currency conversion. Synchronous,
small payload, sub-second latency required.
How it works. Define a Named Credential with the Lambda Function URL
(or API Gateway). Use HttpClient from templates/apex/HttpClient.cls.
Wrap with circuit-breaker + timeout. Test class uses MockHttpResponseGenerator
from templates/apex/tests/.
Why not the alternative. AppFlow is async. Event Relay is async. If
you need the answer before the trigger commits, only a callout works.
Use templates/apex/HttpClient.cls rather than reimplementing — there's
a documented pattern for retry, circuit-breaker, and observable logging.
Recommended Workflow
State the integration in one sentence. Direction, latency, volume, payload type. If you can't fill all four, gather more context before recommending.
Walk the Decision Guidance table top-to-bottom. First match wins. If two rows match, the more constrained one (specific volume / specific latency) takes precedence over the generic one.
Confirm the auth model. OAuth Authorization-Code (default for AppFlow), JWT Bearer Flow (server-to-server, AppFlow or custom), Named Credential + IAM (Apex → Lambda), or Connected App + IAM Role for cross-account EventBridge (Event Relay).
Budget against limits. AppFlow 15 GB / run; Event Relay's 72-hour replay window; Apex callout governor (100 callouts / transaction, 120 s wall-clock per callout).
Pick the related skill for implementation depth. Cite it in the recommendation rather than re-deriving the setup.
Review Checklist
Direction (Salesforce → AWS, AWS → Salesforce, bidirectional) named explicitly in the recommendation.
Volume estimate compared against the path's hard limit.
Auth model named (Authorization-Code / JWT / IAM / Named Credential).
Cross-account / cross-region considerations called out where relevant.
If recommending Event Relay, link to integration/event-relay-configuration for setup; do not re-derive.
If recommending Apex callout, point at templates/apex/HttpClient.cls rather than inlining example code.
Salesforce-Specific Gotchas
AppFlow connection version-locks the Salesforce API. A connection created on API v58 stays on v58 — newly added Salesforce fields do not auto-import on existing flows. Either rebuild the flow on a new connection or manually re-map. (AWS AppFlow Salesforce connector docs)
AppFlow Bulk API 2.0 silently drops compound fields. Address (BillingAddress), Name (Name on a person account), and Geolocation compound fields are not transferable on the Bulk path. If you need them, force Standard API preference and accept the timeout risk on big runs. (AWS docs)
Event Relay does not push back to Salesforce. It is one-way (Salesforce → AWS). Reverse direction needs EventBridge API Destinations writing to a Salesforce REST endpoint, configured separately on the AWS side.
OAuth refresh-token policy must be "Valid until revoked" when bringing your own connected app to AppFlow. The default "Refresh token is valid until first use" silently kills the flow as soon as the first refresh occurs.
Apex callouts to a Lambda Function URL count against the 100-callout governor and the 120-second wall-clock — bulkify them through a single batched payload rather than per-record.
Output Artifacts
Artifact
Description
Decision recommendation
One paragraph naming the chosen path, the auth model, the cited limit, and the linked skill for implementation depth.
Configuration checklist
Numbered list of the AWS-side and Salesforce-side prerequisites for the chosen path.
Risk register
Any limit the design will get within 50 % of, plus the mitigation.
Related Skills
integration/event-relay-configuration — full Event Relay setup recipe; this skill points at it rather than duplicating.
apex/apex-callout-patterns — Named Credential + circuit-breaker + bulkified callouts; cite when recommending Pattern C.
architect/hybrid-integration-architecture — broader integration topology decisions; consult before picking an AWS path if MuleSoft / Heroku / private VPC are also options.
standards/decision-trees/integration-pattern-selection.md — the master integration decision tree; AWS paths are one branch.
