Apache Kafka and Confluent integration services

Apache Kafka and Confluent Integration Services for Ecommerce

CCI designs and delivers Apache Kafka and Confluent integrations between ecommerce platforms and the wider middleware and ipaas ecosystem, with clean data ownership, traceable events, and production runbooks.

Book discovery · See integration patterns

Book discovery·See integration patterns

Designed around: SAP Commerce Cloud · Salesforce Commerce Cloud · Shopify Plus · Adobe Commerce · commercetools · BigCommerce · ERP · OMS

Use Case Grid

What the Apache Kafka and Confluent integration usually needs to prove

A useful Apache Kafka and Confluent integration is not only a working API call. It has to support the business process around API orchestration, transformation, queues, event routing, retries, monitoring, middleware governance, and connector strategy. That means the integration must define when data is created, which system can change it, how conflicts are resolved, which events are customer-visible, and how finance or operations validates the result.

CCI maps Apache Kafka and Confluent into the full commerce landscape so the integration survives real order volume, promotions, returns, supplier changes, regional rules, and release cycles.

Data Flow

Core data flows for Apache Kafka and Confluent

API contracts, transformations, validation, and canonical data models
event streams, queues, retry logic, and dead-letter handling
connector governance, credential rotation, rate limiting, and observability
release management, runbooks, and incident escalation

Architecture Notes

Architecture patterns we use

Direct API integration when the platform and Apache Kafka and Confluent both support stable APIs and the flow needs tight control.
iPaaS or middleware orchestration when mappings, transformations, approvals, and multi-system routing need a managed layer.
Event-driven services when order, inventory, payment, or status events must trigger downstream actions reliably.
File or EDI exchange when legacy systems, suppliers, warehouses, or finance tools require batch transfer.
Staging and reconciliation layers when auditability matters more than moving data as fast as possible.

Checklist

Launch checklist

Step 1

Source of truth, sync direction, and latency are documented for every object.

Step 2

Mapping covers required fields, optional fields, null handling, localization, currency, and identifiers.

Step 3

Retries, idempotency, duplicate detection, and dead-letter handling are in place.

Step 4

Monitoring covers success, failures, delays, rejected payloads, and business exceptions.

Step 5

Runbooks explain who owns each failure and how to recover without corrupting data.

Platform Coverage

Commerce platforms covered

We integrate Apache Kafka and Confluent with SAP Commerce Cloud, Salesforce Commerce Cloud, Shopify Plus, Adobe Commerce, commercetools, BigCommerce, VTEX, Spryker, OroCommerce, Elastic Path, WooCommerce, and custom headless stacks. The right pattern depends on your current middleware, API maturity, data model, volume, and operating model.

Can you integrate Apache Kafka and Confluent with our commerce platform?

Yes. We start by confirming the platform, the Apache Kafka and Confluent API or connector options, the surrounding systems, and the data owners. From there we design the safest pattern for build and long-term operation.

What should we prepare before the Apache Kafka and Confluent integration project?

Prepare sample payloads, credentials or sandbox access, current process diagrams, field mapping, edge cases, reporting requirements, and a list of teams who own failures.

Do you replace existing connectors?

Not always. If a connector is stable and supportable, we may keep it and add monitoring, mapping, or governance around it. If it is limiting the business, we design a replacement path with controlled cutover.

Middleware and iPaaS Integration Services

Integration audit

Direct API vs iPaaS

Real-time vs batch