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kinesis-firehose

Data Ingestion to Amazon OpenSearch Serverless using Kinesis Data Firehose

opensearch-serverless-firehose-arch

This is an Amazon OpenSearch Serverless project for CDK development with Python.

The cdk.json file tells the CDK Toolkit how to execute your app.

This project is set up like a standard Python project. The initialization process also creates a virtualenv within this project, stored under the .venv directory. To create the virtualenv it assumes that there is a python3 (or python for Windows) executable in your path with access to the venv package. If for any reason the automatic creation of the virtualenv fails, you can create the virtualenv manually.

To manually create a virtualenv on MacOS and Linux:

$ python3 -m venv .venv

After the init process completes and the virtualenv is created, you can use the following step to activate your virtualenv.

$ source .venv/bin/activate

If you are a Windows platform, you would activate the virtualenv like this:

% .venv\Scripts\activate.bat

Once the virtualenv is activated, you can install the required dependencies.

(.venv) $ pip install -r requirements.txt

Deploy

Before to synthesize the CloudFormation template for this code, you should update cdk.context.json file.

For example,

{
  "firehose": {
    "buffer_size_in_mbs": 100,
    "buffer_interval_in_seconds": 300,
    "opensearch_index_name": "access-logs"
  },
  "opensearch_iam_user": {
    "user_name": "opss-user",
    "initial_password": "PassW0rd!"
  },
  "collection_name": "log-analysis"
}

Now you are ready to synthesize the CloudFormation template for this code.

(.venv) $ export CDK_DEFAULT_ACCOUNT=$(aws sts get-caller-identity --query Account --output text)
(.venv) $ export CDK_DEFAULT_REGION=$(curl -s 169.254.169.254/latest/dynamic/instance-identity/document | jq -r .region)
(.venv) $ cdk synth --all

Use cdk deploy command to create the stack shown above.

(.venv) $ cdk deploy --all

To add additional dependencies, for example other CDK libraries, just add them to your setup.py file and rerun the pip install -r requirements.txt command.

A note about Service-Linked Role

Some cluster configurations (e.g VPC access) require the existence of the AWSServiceRoleForAmazonOpenSearchServerless Service-Linked Role.

When performing such operations via the AWS Console, this SLR is created automatically when needed. However, this is not the behavior when using CloudFormation. If an SLR(Service-Linked Role) is needed, but doesn’t exist, you will encounter a failure message simlar to:

Before you can proceed, you must enable a service-linked role to give Amazon OpenSearch Service...

To resolve this, you need to create the SLR. We recommend using the AWS CLI:

aws iam create-service-linked-role --aws-service-name observability.aoss.amazonaws.com

ℹ️ For more information, see here.

Clean Up

Delete the CloudFormation stack by running the below command.

(.venv) $ cdk destroy --force --all

Useful commands

  • cdk ls list all stacks in the app
  • cdk synth emits the synthesized CloudFormation template
  • cdk deploy deploy this stack to your default AWS account/region
  • cdk diff compare deployed stack with current state
  • cdk docs open CDK documentation

Enjoy!

Run Tests

Send data to Kinesis Data Firehose using Direct PUT

  1. Install python packages thare are required for the script to generate fake access logs

    (.venv) $ cat requirements-dev.txt
    boto3==1.26.38
    botocore==1.29.38
    mimesis==7.0.0
    (.venv) $ python install -r requirements-dev.txt
    
  2. Run the script to send data to the Firehose.

    (.venv) $ python tests/gen_fake_data.py --stream-name your-kinesis-firehose-stream-name --max-count 1000
    

Login to AWS Web console with the OpenSearch IAM User

To access Amazon OpenSearch Serverless data-plane APIs and OpenSearch Dashboards from the browser, you need to login to AWS Web console with the IAM User that is created.

You can find the IAM User name and initial password in the cdk.context.json file.

  1. Sign into the Amazon Web console at https://console.aws.amazon.com/ aws_sign_in_as_iam_user
  2. Change the password. aws_iam_user_change_password
  3. Check if successfuly logined.
    For example: opss-user login into the N. Virgina (us-east-1) region. aws_login_as_iam_user

View incoming data in OpenSearch

After a couple of minutes, you will have enough data in your OpenSearch cluster for the next step. You can use OpenSearch dashboard to visualize or retrieve the data.

  1. Navigate to OpenSearch collection in AWS console, and click on the OpenSearch Dashboards URL
  2. If prompted to add data, select Explore on my own. 02-aos-explore-on-my-own
  3. To start using your data, you need to create a Search Pattern. From the OpenSearch menu, click on Stack Management under Management. 03-aos-stack-menu
  4. On the left menu, click on Index Patterns, and then click on Create index patterns. 04-aos-search-patterns-create
  5. For Index pattern name, type access-logs-*. You should see a green prompt stating that "Your index pattern matches ... source". Click on Next step. 05-aos-index-pattern-next
  6. In the next screen, Under Time Field, select timestamp. Then click on Create index pattern. 06-aos-search-patterns-create-last
  7. Now, let's take a look at some of the data records. Open the OpenSearch menu and click on Discover under OpenSearch Dashboards. 07-aos-discover-menu
  8. You can see a handful of your incoming data. You can search and filter using OpenSearch Dashboard Language here if you want. 08-aos-discover-search

References