Amazon Kinesis Data Analytics | Managing Kinesis Data Analytics Applications

Question 1

What delivery model does Kinesis Data Analytics provide?

Managing Kinesis Data Analytics Applications

Amazon Kinesis Data Analytics | Analytics

Answer 1

Kinesis Data Analytics uses an “at least once” delivery model for application output to the configured destinations. Kinesis Data Analytics applications take internal checkpoints, which are points in time when output records were delivered to the destinations and there was no data loss. The service uses the checkpoints as needed to ensure that your application output is delivered at least once to the configured destinations. For more information about the delivery model, see Configuring Application Output in the Kinesis Data Analytics Developer Guide.

Question 2

How can I monitor the operations and performance of my Kinesis Data Analytics applications?

Managing Kinesis Data Analytics Applications

Amazon Kinesis Data Analytics | Analytics

Answer 2

AWS provides various tools that you can use to monitor your Kinesis Data Analytics applications. You can configure some of these tools to do the monitoring for you. For more information about how to monitor your application, see Monitoring Kinesis Data Analytics in the Kinesis Data Analytics Developer Guide.

Question 3

How do I manage and control access to my Kinesis Data Analytics applications?

Managing Kinesis Data Analytics Applications

Amazon Kinesis Data Analytics | Analytics

Answer 3

Kinesis Data Analytics needs permissions to read records from the streaming data sources that you specify in your application. Kinesis Data Analytics also needs permissions to write your application output to data streams that you specify in your application output configuration. You can grant these permissions by creating IAM roles that Kinesis Data Analytics can assume. The permissions you grant to this role determine what Kinesis Data Analytics can do when the service assumes the role. For more information, see Granting Permissions in the Kinesis Data Analytics Developer Guide.

Question 4

How does Kinesis Data Analytics scale my application?

Managing Kinesis Data Analytics Applications

Amazon Kinesis Data Analytics | Analytics

Answer 4

Kinesis Data Analytics elastically scales your application to accommodate the data throughput of your source stream and your query complexity for most scenarios. Kinesis Data Analytics provisions capacity in the form of Amazon Kinesis Processing Units (KPU). A single KPU provides you with the memory (4 GB), and corresponding compute and networking.

Each streaming source is mapped to a corresponding in-application stream. While this is not required for many customers, you can more efficiently use KPUs by increasing the number of in-application streams that your source is mapped to by specifying the input parallelism parameter. Kinesis Data Analytics evenly assigns the streaming data source’s partitions, such as an Amazon Kinesis data stream’s shards, to the number of in-application data streams that you specified. For example, if you have a 10-shard Amazon Kinesis data stream as a streaming data source and you specify an input parallelism of two, Kinesis Data Analytics assigns five Amazon Kinesis shards to two in-application streams named “SOURCE_SQL_STREAM_001” and “SOURCE_SQL_STREAM_002”. For more information, see Configuring Application Input in the Kinesis Data Analytics Developer Guide.