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Amazon Kinesis integration

Connect AWS event streams with the business records they affect. Uplyst brings transaction updates, application activity and telemetry into a shared operational view.

How it connectsDiscuss your integration
From AWS events to operational decisions
  1. Kinesis Data StreamsApplication events, telemetry and transaction updates
  2. Uplyst intelligence layerBusiness entities enriched with their latest events
  3. Operational responseExceptions connected to the teams and processes they affect

Connect AWS streams to Uplyst

Amazon Kinesis Data Streams collects data from applications and services for continuous processing. Uplyst connects these events with its business model, relating a payment update to an account or a device observation to an asset.

The integration is defined around the selected streams, workload permissions and business identifiers. Source event details remain useful alongside the records from ERP, CRM and other systems that provide wider context.

Delivery of individual records

Kinesis supports individual record writes and batch writes through PutRecords. A batch response can contain both successful and failed records, and PutRecords does not guarantee record order.

Delivery status matters when a business process depends on a complete sequence of events. Application event identifiers and source timestamps help connect stream activity with the transaction or operation it describes.

Settlement event deliveryPutRecords
Streampayments.operations
HTTP response200 OK
FailedRecordCount1
Application eventResult
settlement.4817Merchant 041
Accepted
settlement.4818Merchant 106
Retry required
settlement.4819Merchant 212
Accepted
settlement.4820Merchant 310
Accepted

Retry the failed entry

settlement.4818
Failure
ProvisionedThroughputExceededException
Next request
1 record, after backoff
Application identity
Same event ID and payload

The three accepted records stay out of this retry.

Delivery and processing are separate.

Kinesis acceptance confirms the write. Consumer processing and its checkpoint establish downstream progress.

Consumer checkpoints and recovery

The Kinesis Client Library coordinates consumption across shards and stores checkpoints for recovery. A consumer can resume from its saved position after a worker restarts.

Records may be processed again during recovery. Linking them to stable business event identifiers helps preserve a consistent history across retries and consumer changes.

Recoverable stream processing
  1. ReceiveRead the event and its shard position
  2. ProcessApply the event to the relevant business state
  3. CheckpointSave completed progress for recovery

AWS access controls

Stream access
IAM permissions for the required operations
Encryption
KMS access where the stream configuration requires it
Consumer state
Permissions for checkpoint and lease metadata

AWS permissions and encryption

AWS IAM policies control access to Kinesis streams and operations. Depending on the deployment, the consuming workload may also need permissions for encryption keys and the resources used to track consumer state.

The stream's region, network path and credential mechanism are part of the connection configuration. These define how the integration accesses the approved data.

Operational use cases

Kinesis feeds can support shipment monitoring, transaction analysis and connected asset operations. In Uplyst, an incoming event can be understood alongside the customer, order or asset information held elsewhere.

Stream lag and processing errors gain business relevance when teams can see which accounts, sites or processes are waiting for an update.

Related integrations

Apache Kafka integrationAmazon S3 integration

Connect your systems
with Uplyst.

Talk with our team about the systems you use and the decisions they need to support.

Discuss an integration