Streaming Architecture & Build
Event streams designed like the infrastructure they are.
The expensive streaming mistakes are design mistakes: topics keyed so ordering breaks under growth, schemas that cannot evolve, exactly-once bought where an idempotent sink was enough — or not bought where reprocessing corrupts state. We do the design work up front, in writing, and then build it with you.
Design
- Topic design — partitioning and key strategy from measured throughput and real key distributions, retention and compaction policy, naming and ownership conventions your teams can actually follow.
- Schema design and governance — Avro or Protobuf with Schema Registry, compatibility modes chosen deliberately, evolution rules enforced in CI rather than code review.
- Delivery guarantees — an explicit, written decision per pipeline: at-least-once with idempotent sinks, or exactly-once semantics where the trade-off earns its cost.
Build
- Producers and consumers — implementation or review in JVM languages and beyond: batching, idempotence, error handling, dead-lettering, graceful rebalancing on deploys.
- Kafka Streams — topology design, state-store sizing, standby replicas, interactive queries, and the operational side (restoration time, changelog topics) that demos skip.
- Kafka Connect — pipeline design for CDC and system integration, connector selection and configuration, single-message transforms, and error-tolerance policy.
How it runs
As a project (we deliver a system) or as staff augmentation (our engineers work inside your team's repos, reviews, and on-call reality). Either way the design decisions land in documents your team owns after we leave — the goal is a platform your engineers can reason about, not a dependency on ours.
Bring the whiteboard photo. Early design conversations are the cheapest ones.
Discuss your design