canonical: https://jentic.com/apis/amazonaws.com/kinesisanalytics

# AWS Amazon Kinesis Analytics

Jentic publishes the only available OpenAPI specification for Amazon Kinesis Analytics, keeping it validated and agent-ready. Kinesis Analytics is the v1 SQL-based service for running continuous queries over streaming data from Kinesis Data Streams or Kinesis Firehose. Its 20-endpoint API covers application creation, input and output configuration, reference data sources, CloudWatch logging options, schema discovery, and lifecycle controls to start and stop applications. The service is suited to teams running SQL transformations on event streams without standing up Spark or Flink clusters themselves.

## For AI agents

Run continuous SQL queries over streaming data from Kinesis Data Streams or Firehose without managing the underlying compute.

## Scope

Does not handle Apache Flink applications, raw stream produce or consume traffic, or batch ETL - use for v1 SQL-based streaming application management only.

## Capabilities

- Create SQL streaming applications via CreateApplication
- Configure inputs from Kinesis Data Streams or Firehose with AddApplicationInput
- Add reference data from S3 with AddApplicationReferenceDataSource
- Stream output to Lambda or Firehose via AddApplicationOutput
- Discover input schemas automatically with DiscoverInputSchema
- Start and stop applications to control billing and throughput
- Configure CloudWatch logging for SQL diagnostics

## Use cases

### Real-Time Fraud Signals

Run continuous SQL queries over a transaction event stream to flag anomalous patterns in seconds. The Kinesis Analytics application reads from a Kinesis Data Stream, joins reference data from S3, and emits alerts to a downstream Firehose or Lambda output. Teams use this to detect velocity violations, dollar-amount thresholds, and other rule-based anomalies without writing Flink jobs.

Example prompt: Create application 'fraud-rules' with SQL that flags transactions where amount > 10000 from input stream txn-events

### Stream Aggregation for Dashboards

Aggregate a high-volume event stream into per-minute metrics for live dashboards. Kinesis Analytics supports tumbling and sliding windows in SQL, which makes it straightforward to compute count, sum, and average over time windows and write the results into a destination stream that powers a near-real-time dashboard or alerting system.

Example prompt: Create an application that emits per-minute counts of input stream click-events to output stream click-counts using a tumbling window

### Schema Discovery for Pipelines

Bootstrap a new streaming pipeline by discovering the schema of an input stream automatically. The DiscoverInputSchema operation samples records from a Kinesis stream and infers column names, types, and record format, which speeds up onboarding new event sources and reduces manual SQL configuration mistakes.

Example prompt: Run DiscoverInputSchema against stream txn-events with role arn:aws:iam::123:role/kinesis-analytics-discovery and return the inferred columns

### AI Agent Streaming Pipeline Operations

AI agents call Kinesis Analytics through Jentic to create new applications when teams onboard event sources, start and stop applications based on cost guards, and inspect schemas before configuring downstream consumers. Through Jentic, the agent searches by intent, loads the operation schema, and executes with credentials stored in the vault. SigV4 signing happens inside Jentic so the agent runtime stays slim.

Example prompt: Search Jentic for 'start kinesis analytics application', load the StartApplication schema, and execute against application 'fraud-rules'

## Key endpoints

| Method | Path | Description |
| --- | --- | --- |
| POST | /#X-Amz-Target=KinesisAnalytics_20150814.CreateApplication | Create a streaming SQL application |
| POST | /#X-Amz-Target=KinesisAnalytics_20150814.StartApplication | Start an application |
| POST | /#X-Amz-Target=KinesisAnalytics_20150814.StopApplication | Stop a running application |
| POST | /#X-Amz-Target=KinesisAnalytics_20150814.AddApplicationInput | Configure an input stream |
| POST | /#X-Amz-Target=KinesisAnalytics_20150814.AddApplicationOutput | Configure an output destination |
| POST | /#X-Amz-Target=KinesisAnalytics_20150814.DiscoverInputSchema | Auto-discover the schema of a stream |

## Key resources

- **Applications** — Create, describe, list, update, and delete streaming SQL applications
- **Inputs** — Configure input streams from Kinesis Data Streams or Firehose
- **Outputs** — Configure output destinations such as Firehose or Lambda
- **Reference Data** — Attach S3-based lookup tables for SQL joins
- **Lifecycle Controls** — Start and stop applications and manage logging

## Why Jentic

- **Setup:** Wiring the Kinesis Analytics API by hand means building AWS Signature Version 4 signing, selecting the right regional host from kinesisanalytics.{region}.amazonaws.com, setting the X-Amz-Target header on every call, and handling AWS throttling and retries yourself. Through Jentic you install once, import Amazon Kinesis Analytics from the API Directory, store the AWS access key and secret once, and your agent calls it.
- **Permission scoping:** Kinesis Analytics is an X-Amz-Target RPC API where the application name and configuration travel in the request body, so limit the agent to the operations it needs, such as DescribeApplication or DiscoverInputSchema. You choose the operations it may call, so destructive ones like DeleteApplication or StopApplication are not included unless you add them.
- **Credential handling:** Your AWS access key and secret for Kinesis Analytics are stored once, encrypted, by your own Jentic One instance and signed with SigV4 at execution time. They never enter the agent's prompt, logs, or context.
- **Discovery method:** Agents search Jentic by intent such as 'create a streaming sql application over a kinesis stream' or 'start a kinesis analytics application', and Jentic returns the matching operation with its input schema so the agent calls the right endpoint without reading the AWS reference.

## Related APIs

- **Managed Streaming for Kafka** — Managed Apache Kafka clusters
- **AWS Lambda** — Serverless function execution
- **Amazon EventBridge** — Serverless event bus
- **Amazon CloudWatch Logs** — Centralised log storage and search

## FAQ

### Why is there no official OpenAPI spec for Amazon Kinesis Analytics?

AWS does not publish an OpenAPI specification. Jentic generates and maintains this spec so that AI agents and developers can call Amazon Kinesis Analytics via structured tooling. It is validated against the live API and kept up to date. Get started with Jentic One, the self-hosted execution layer.

### What authentication does the Kinesis Analytics API use?

Kinesis Analytics uses AWS Signature Version 4 (SigV4) HMAC request signing. Each call must be signed with an access key, secret key, and optional session token scoped to the kinesisanalytics IAM service. Through Jentic, these credentials sit in the encrypted vault and signing happens at execution time.

### Can I run streaming SQL with the Kinesis Analytics API?

Yes. CreateApplication accepts an ApplicationCode field containing your SQL, plus input and output configurations that wire the application to Kinesis Data Streams, Firehose, or Lambda. The service handles parsing, scheduling, and scaling automatically.

### How do I start a streaming application through Jentic?

Search Jentic for 'start kinesis analytics application', load the StartApplication schema, submit the application name and an InputConfiguration with the InputId and starting position, and Jentic will sign and execute the call.

### What are the rate limits for the Kinesis Analytics API?

Per-region quotas apply, including a default cap on applications per account and TPS limits on control plane operations such as CreateApplication and DescribeApplication. Check the Kinesis Analytics service quotas in the AWS console for current values.

### Can the Kinesis Analytics API discover an input schema automatically?

Yes. DiscoverInputSchema samples records from a Kinesis Data Stream or Firehose using a supplied IAM role and returns the inferred record format and column list. Use this before configuring AddApplicationInput so the schema is correct on the first attempt.

### How does Kinesis Analytics differ from Kinesis Data Analytics for Apache Flink?

This API covers the v1 SQL-based service. AWS also offers a separate Kinesis Data Analytics for Apache Flink service for Java, Scala, and Python applications. Pick the SQL service for simple windowed transforms; pick Flink for stateful processing and custom code.

### Can I limit what my agent is allowed to do with the Kinesis Analytics API?

Yes. Because you run Jentic One yourself, your own rules decide which Kinesis Analytics operations and AWS credentials the agent can use. Since this is an X-Amz-Target RPC API where the application name and configuration travel in the request body, you can restrict the agent to only the operations it needs, such as DescribeApplication or DiscoverInputSchema. Destructive operations like DeleteApplication or StopApplication are excluded unless you explicitly add them.