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Data · Sub-service

Real-time Streaming

"Sub-minute latency for live decisions"

Low-latency event-driven architectures with Kafka, Flink, and Spark Streaming — for live analytics, operational decisions, and reactive systems.

Streaming

What we deliver

01

Kafka & Kinesis

Producer/consumer design, partitioning, exactly-once setup.

02

Flink & Spark Streaming

Stateful operators, windowing, joins, watermarks.

03

Stream-to-warehouse

CDC, hot-cold split, exactly-once into Snowflake/BigQuery.

04

Schema registry

Avro/Protobuf contracts, evolution, compatibility checks.

05

Operational metrics

End-to-end latency, lag, and throughput dashboards.

06

Dead-letter & replay

Poison-message handling, audit, and idempotent replay.

How we approach it

Working lifecycle

01

Model events

Capture domain events with clear ownership and contracts.

02

Build pipelines

Producers, brokers, processors, sinks — all observable.

03

Validate

Load tests at 10x peak, replay drills, schema-evolution tests.

04

Operate

On-call runbooks, lag alerts, and steady-state cost tracking.

Ready to start?

Talk to us about Real-time Streaming

Tell us about your data estate and the outcome that matters. We will reply with a scoped plan.