Streaming

Apache Kafka

Distributed event streaming for real-time data architectures

https://kafka.apache.org

What It Is

Apache Kafka is a distributed event streaming platform capable of handling trillions of events per day. Originally developed at LinkedIn, Kafka has become the backbone of real-time data architectures worldwide. It serves as a high-throughput, low-latency message bus that decouples data producers from consumers — enabling event-driven architectures, real-time analytics, and Change Data Capture pipelines.

How We Use It

We design and implement Kafka-based architectures for clients who need real-time data movement: CDC streams from production databases, event collection from applications, log aggregation, and real-time analytics pipelines. Kafka typically sits at the center of the data architecture — connecting source systems with warehouses, data lakes, and streaming processors.

Our Expertise

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Architecture Design

We design Kafka clusters for reliability: sizing, broker configuration, replication, and multi-datacenter setups with MirrorMaker 2.
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Topic Design & Partitioning

We design topic schemas and partitioning strategies balancing throughput, ordering, and consumer parallelism.
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Kafka Connect

We deploy source connectors for CDC (Debezium) and sink connectors for warehouses (ClickHouse, BigQuery, S3).
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Producer & Consumer Development

We build reliable producers and consumers in Python and Java with exactly-once semantics.
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Monitoring & Operations

We set up Kafka monitoring: broker health, consumer lag, partition balance, and alerting via Grafana/Prometheus.