Fordeq
Corporate Enterprise Background
Event Streaming Platform

Apache Kafka Integration
Built for Enterprise

KAFKA · REAL-TIME · RELIABLE DELIVERY · REPLAY

Connect enterprise event streams through Apache Kafka with reliable delivery, replay capabilities and real-time operational visibility. Produce and consume events at scale with built-in monitoring and orchestration.

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Kafka Producers & Consumers

Native support for Apache Kafka producers and consumers with flexible configuration and operational control.

  • Kafka producer integration
  • Consumer groups management
  • Partition-aware routing
  • Offset management
  • Schema Registry support
  • Avro, JSON and Protobuf schemas

Event Retry & Replay

Reliable event processing with automatic retry, manual replay and dead-letter queue handling.

  • Automatic retry with backoff
  • Manual event replay from history
  • Dead-letter queue (DLQ) handling
  • Event idempotency support
  • Offset tracking and recovery
  • Transactional processing

Event-Driven Flow Orchestration

Orchestrate complex workflows triggered by Kafka events across your entire integration platform.

  • Event-based workflow triggers
  • Conditional routing and branching
  • Multi-step event processing
  • Downstream system integration
  • Filter and transformation rules
  • Correlation and aggregation

Real-Time Monitoring

Complete visibility into Kafka event streams with consumer lag tracking and performance metrics.

  • Consumer lag monitoring
  • Throughput and latency metrics
  • Topic and partition visibility
  • Real-time dashboards
  • Performance trending
  • Grafana integration

Reliable Delivery

Enterprise-grade reliability guarantees for event processing at scale.

  • At-least-once delivery semantics
  • Exactly-once processing support
  • Message ordering guarantees
  • Failure recovery
  • Backpressure handling
  • Circuit breaker patterns

Operational Excellence

Manage Kafka infrastructure and events with ease across your organization.

  • Multi-cluster support
  • Role-based access control
  • Audit logging for all events
  • Performance optimization
  • Topic management
  • Security and encryption

Common Use Cases

Popular patterns and integration workflows for Apache Kafka event streaming across enterprises.

Real-Time Data Pipeline

Stream data in real-time from multiple sources into data warehouses, lakes or analytics platforms.

Event-Driven Microservices

Build loosely coupled microservices that communicate through event streams with reliable delivery.

Activity & Audit Logging

Centralize all application and system events for compliance, auditing and troubleshooting.

Real-Time Alerts & Monitoring

Process event streams to trigger alerts, dashboards and notifications based on business rules.

Event Replay & Recovery

Replay events from Kafka history for reprocessing, data recovery or handling failed deployments.

Consumer Lag Monitoring

Track consumer lag across all topics and get alerts when processing falls behind.

Architecture & Scalability

The event streaming platform is built on proven Kafka architecture principles for handling enterprise-scale event volumes.

Distributed Brokers

Leverage Kafka's distributed architecture for fault tolerance and high throughput.

Consumer Groups

Scale event processing with multiple consumer instances in coordinated groups.

Topic Partitioning

Distribute events across partitions for parallel processing and fault isolation.

Replication & Durability

Built-in replication ensures no message loss even during broker failures.

Offset Management

Flexible offset tracking enables processing exactly where you left off.

Kafka Best Practices

Built-in patterns and configurations for reliable, efficient Kafka event streaming.

  • Use meaningful topic naming conventions
  • Configure appropriate replication factors
  • Monitor consumer lag continuously
  • Implement idempotent producers
  • Use schemas for event validation
  • Plan partition strategy for scalability
  • Set retention policies aligned with needs
  • Implement circuit breakers for failure handling

Frequently Asked Questions

What Kafka versions are supported?
The platform supports Apache Kafka 2.8 and later, including the latest versions. It's tested and optimized for all recent releases.
Can I use multiple Kafka clusters?
Yes. You can configure and manage multiple Kafka clusters, enabling multi-cluster event streaming and disaster recovery scenarios.
How do you handle consumer lag?
Consumer lag is monitored in real-time with alerts when processing falls behind. You can also view detailed lag metrics per consumer group and topic.
Is event replay supported?
Absolutely. You can manually replay events from Kafka's retained history, enabling recovery from processing failures or logic updates.
What about schema validation?
The platform supports schema registries and validates events against Avro, JSON and Protobuf schemas before processing.
Can I correlate events across topics?
Yes. Event orchestration features enable correlation, aggregation and complex join patterns across multiple Kafka topics.

Stream Your Event Data at Scale

Connect your Kafka infrastructure to the rest of your integration platform and unlock real-time event-driven automation.

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