AWS kinesisanalytics documentation change
Summary
Updated terminology from 'AWS CloudFormation' to 'CloudFormation' throughout the document for consistency
Security assessment
Changes are purely terminological updates (removing 'AWS' prefix from CloudFormation references). No security configurations, vulnerabilities, or security features are modified or added. The updates don't impact authentication, permissions, data protection, or other security aspects.
Diff
diff --git a/kinesisanalytics/latest/dev/migrating-to-kda-studio-overview.md b/kinesisanalytics/latest/dev/migrating-to-kda-studio-overview.md index 955eaf417..4b329a3a5 100644 --- a//kinesisanalytics/latest/dev/migrating-to-kda-studio-overview.md +++ b//kinesisanalytics/latest/dev/migrating-to-kda-studio-overview.md @@ -1326 +1326 @@ In the following exercise, you will change your data flow to use Amazon Managed -First we share a typical KDA-SQL architecture, before showing how you can replace this using Amazon Managed Service for Apache Flink Studio and Amazon Kinesis Data Streams. Alternatively you can launch the AWS CloudFormation template [here](https://github.com/aws-samples/amazon-kinesis-data-analytics-examples/blob/master/Converting-KDASQL-KDAStudio/environmentStackCfn/KdaStudioStack.template.yaml): +First we share a typical KDA-SQL architecture, before showing how you can replace this using Amazon Managed Service for Apache Flink Studio and Amazon Kinesis Data Streams. Alternatively you can launch the CloudFormation template [here](https://github.com/aws-samples/amazon-kinesis-data-analytics-examples/blob/master/Converting-KDASQL-KDAStudio/environmentStackCfn/KdaStudioStack.template.yaml): @@ -1338 +1338 @@ Amazon Kinesis Data Analytics-SQL is set up to ingest data from the Amazon Kines -In this case, you use Amazon Kinesis Data Generator. Amazon Kinesis Data Generator allows you to send test data to your Amazon Kinesis Data Streams or Amazon Kinesis Data Firehose delivery streams. To get started, follow the instructions [here](https://awslabs.github.io/amazon-kinesis-data-generator/web/help.html). Use the AWS CloudFormation template [here](https://github.com/aws-samples/amazon-kinesis-data-analytics-examples/blob/master/Converting-KDASQL-KDAStudio/environmentStackCfn/KdaStudioStack.template.yaml) in place of the one provided in the [instructions:](https://awslabs.github.io/amazon-kinesis-data-generator/web/help.html). +In this case, you use Amazon Kinesis Data Generator. Amazon Kinesis Data Generator allows you to send test data to your Amazon Kinesis Data Streams or Amazon Kinesis Data Firehose delivery streams. To get started, follow the instructions [here](https://awslabs.github.io/amazon-kinesis-data-generator/web/help.html). Use the CloudFormation template [here](https://github.com/aws-samples/amazon-kinesis-data-analytics-examples/blob/master/Converting-KDASQL-KDAStudio/environmentStackCfn/KdaStudioStack.template.yaml) in place of the one provided in the [instructions:](https://awslabs.github.io/amazon-kinesis-data-generator/web/help.html). @@ -1340 +1340 @@ In this case, you use Amazon Kinesis Data Generator. Amazon Kinesis Data Generat -Once you run the AWS CloudFormation template, the output section will provide the Amazon Kinesis Data Generator url. Log in to the portal using the Cognito user id and password you set up [here](https://awslabs.github.io/amazon-kinesis-data-generator/web/help.html). Select the Region and the target stream name. For current state, choose the Amazon Kinesis Data Firehose Delivery streams. For the new state, choose the Amazon Kinesis Data Firehose Streams name. You can create multiple templates, depending on your requirements, and test the template using the **Test template** button before sending it to the target stream. +Once you run the CloudFormation template, the output section will provide the Amazon Kinesis Data Generator url. Log in to the portal using the Cognito user id and password you set up [here](https://awslabs.github.io/amazon-kinesis-data-generator/web/help.html). Select the Region and the target stream name. For current state, choose the Amazon Kinesis Data Firehose Delivery streams. For the new state, choose the Amazon Kinesis Data Firehose Streams name. You can create multiple templates, depending on your requirements, and test the template using the **Test template** button before sending it to the target stream. @@ -1559 +1559 @@ Here is what the contents looks like: -You can use the [AWS CloudFormation template](https://github.com/aws-samples/amazon-kinesis-data-analytics-examples/blob/master/Converting-KDASQL-KDAStudio/environmentStackCfn/KdaStudioStack.template.yaml) to create the infrastructure. +You can use the [CloudFormation template](https://github.com/aws-samples/amazon-kinesis-data-analytics-examples/blob/master/Converting-KDASQL-KDAStudio/environmentStackCfn/KdaStudioStack.template.yaml) to create the infrastructure. @@ -1561 +1561 @@ You can use the [AWS CloudFormation template](https://github.com/aws-samples/ama -AWS CloudFormation will create the following resources in your AWS account: +CloudFormation will create the following resources in your AWS account: @@ -1576 +1576 @@ AWS CloudFormation will create the following resources in your AWS account: -Import the notebook and change the Amazon S3 bucket name with the new Amazon S3 bucket created by AWS CloudFormation. +Import the notebook and change the Amazon S3 bucket name with the new Amazon S3 bucket created by CloudFormation. @@ -1636 +1636 @@ To follow this guide and interact with your streaming data, you will use an AWS -Download the AWS CloudFormation template [here](https://github.com/aws-samples/amazon-kinesis-data-analytics-examples/blob/master/kda-udf-sample/cfn/kda-flink-udf.yml). +Download the CloudFormation template [here](https://github.com/aws-samples/amazon-kinesis-data-analytics-examples/blob/master/kda-udf-sample/cfn/kda-flink-udf.yml). @@ -1638 +1638 @@ Download the AWS CloudFormation template [here](https://github.com/aws-samples/a -###### Create the AWS CloudFormation stack +###### Create the CloudFormation stack @@ -1655 +1655 @@ Download the AWS CloudFormation template [here](https://github.com/aws-samples/a -The AWS CloudFormation stack may take 10 to 15 minutes to launch depending on the Region you are launching in. Once you see `CREATE_COMPLETE` status for the entire stack, you are ready to continue. +The CloudFormation stack may take 10 to 15 minutes to launch depending on the Region you are launching in. Once you see `CREATE_COMPLETE` status for the entire stack, you are ready to continue. @@ -1686 +1686 @@ Apache Zeppelin provides your Studio notebooks with a complete suite of analytic - 6. Import the `Data Producer` Zeppelin Notebook. Make sure to modify input `STREAM_NAME` and `REGION` in the notebook code. The input stream name can be found in the [AWS CloudFormation stack output](https://github.com/aws-samples/amazon-kinesis-data-analytics-examples/blob/master/kda-udf-sample/cfn/kda-flink-udf.yml). + 6. Import the `Data Producer` Zeppelin Notebook. Make sure to modify input `STREAM_NAME` and `REGION` in the notebook code. The input stream name can be found in the [CloudFormation stack output](https://github.com/aws-samples/amazon-kinesis-data-analytics-examples/blob/master/kda-udf-sample/cfn/kda-flink-udf.yml). @@ -1789 +1789 @@ Now that you have tested your notebook code interactively, you will deploy the c - 2. Under **Destination for code in Amazon S3** , choose the Amazon S3 bucket that was created by the [AWS CloudFormation scripts](https://github.com/aws-samples/amazon-kinesis-data-analytics-examples/blob/master/kda-udf-sample/cfn/kda-flink-udf.yml). The process may take a few minutes. + 2. Under **Destination for code in Amazon S3** , choose the Amazon S3 bucket that was created by the [CloudFormation scripts](https://github.com/aws-samples/amazon-kinesis-data-analytics-examples/blob/master/kda-udf-sample/cfn/kda-flink-udf.yml). The process may take a few minutes. @@ -1814 +1814 @@ For more information on deploying applications with durable state and limits, se -Optionally, you can now [uninstall the AWS CloudFormation stack](https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/cfn-console-delete-stack.html). This will remove all the services which you set up in previously. +Optionally, you can now [uninstall the CloudFormation stack](https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/cfn-console-delete-stack.html). This will remove all the services which you set up in previously.