Real-time streaming
Event ingest and stream processing on Amazon Kinesis for telemetry, transactions, and operational signals that lose their value overnight.
Latency target
Sub-second
Ingest to actionable, under normal load.
- Basis
- Fixed price
- Target
- Kinesis + Lambda
- Includes
- Replay & DLQ
What we deliver
Streams you can replay.
Real-time is only useful if it is also recoverable. Every pipeline we build can be replayed from source after a bad deploy.
Ingest
High-throughput event capture with backpressure handling and partitioning.
Stream processing
Enrichment, aggregation, and windowing close to the point of arrival.
Replay & DLQ
Failed events quarantined and reprocessable without data loss.
Live dashboards
Operational views fed directly from the stream, not a nightly batch.
Alerting
Threshold and anomaly triggers wired into the workflows that respond.
How it runs
One stream, then scale.
We ship a single high-value stream to production before generalising the pattern across the rest.
Pick the signal
The one event stream where latency demonstrably costs money.
Build the pipeline
Ingest, process, and sink with replay and dead-letter handling.
Instrument
Lag, throughput, and error metrics with alerts before go-live.
Generalise
Extract the pattern so the next stream is configuration, not a project.
Technology
What we build it on.
- Kinesis Data Streams
- Kinesis Firehose
- Lambda
- DynamoDB
- OpenSearch
- CloudWatch
Cost & AWS pricing
Fixed-price build. Kinesis is billed by shard-hour and payload, so we size and model throughput during design — an over-provisioned stream is the most common waste we find.
See funded AWS programsNext step
Stop waiting for the nightly batch.
Discovery comes first — a short, bounded review that ends in an architecture, a scope, and a price. You keep the output either way.