Apache Kafka and Confluent consultants and engineers

Digiventi provides Apache Kafka consultants and Confluent engineers to assess existing clusters or establish a streaming platform. They translate throughput and recovery requirements into partitioning, replication, retention and capacity decisions.

• Platform configuration: Configure Apache Kafka, Confluent Platform or Confluent Cloud to match hosting requirements.
• Architecture assessment: Review broker topology and producer-consumer dependencies. Identify partition hotspots and failure risks before expanding workloads.

Specialists can also configure authentication and access controls, with responsibility boundaries documented for application and infrastructure teams.

Connect operational databases and downstream applications through pipelines that can recover from interruptions. Distributed data engineers configure Kafka Connect and Debezium for change data capture, including initial snapshots and subsequent database changes.

Work covers connector configuration and reconciliation between source records and destination data. Engineers define event contracts through Confluent Schema Registry and check schema compatibility before releases. They also implement retry handling and dead-letter queues so failed records can be investigated without silently discarding business data.

Develop event-driven applications when business logic depends on continuously arriving data. Kafka developers implement producers and consumers, while stream-processing engineers use Kafka Streams or Apache Flink for stateful calculations.

• Processing logic: Build aggregations and joins with explicit handling of event time and late arrivals.
• Application correctness: Configure delivery semantics and idempotency to control duplicate effects. Test replay behavior against downstream side effects.

Engineers investigate serialization errors and consumer-group behavior, with application tests that cover rebalances and interrupted processing.

Bring in Kafka engineers for ongoing platform maintenance or incidents affecting data freshness. They trace consumer lag and broker saturation using platform metrics and application telemetry, then address the measured bottleneck.

Support can cover configuration tuning and version upgrades, including KRaft migration planning where applicable. For platform moves, specialists assess replication with MirrorMaker 2 or Confluent Cluster Linking and validate consumer cutover behavior. Recovery work includes testing data replay and checking that dependent applications resume processing without unintended duplicate actions.