1. Full-text Search Capabilities for NLP Models with AWS Elasticsearch


    To build a solution for full-text search capabilities for NLP (Natural Language Processing) models with AWS Elasticsearch, we will be using the aws.elasticsearch.Domain resource. This resource allows us to create and configure an Amazon Elasticsearch Domain, where Elasticsearch is a popular search engine that supports full-text search and is commonly used for log analytics, full-text search, and operational intelligence use cases.

    In this scenario, we want to have an Elasticsearch domain set up to receive data (such as text data from NLP models), index this data, and make it searchable. We might also want to configure a VPC (Virtual Private Cloud) so that the Elasticsearch domain resides within our own virtual network, offering better security and network performance.

    The program below does the following:

    1. Sets up an Elasticsearch domain with encryption, node-to-node encryption, and also configures it to operate within a VPC.
    2. Adds an access policy to the domain to control which users or services can access the Elasticsearch domain.
    3. Outputs the endpoint of the Elasticsearch domain, which is the URL through which you can interact with the Elasticsearch API to perform search queries or manage the domain.

    Here is how to do it with Pulumi in Python:

    import pulumi import pulumi_aws as aws # Create an AWS Elasticsearch domain. es_domain = aws.elasticsearch.Domain("nlp-search-domain", domain_name="nlp-search-domain", elasticsearch_version="7.9", # Specify the Elasticsearch version. cluster_config=aws.elasticsearch.DomainClusterConfigArgs( instance_type="r4.large.elasticsearch" # Choose an instance type based on your needs. ), ebs_options=aws.elasticsearch.DomainEbsOptionsArgs( ebs_enabled=True, volume_size=10, # Set the volume size (in GB); adjust as necessary. ), node_to_node_encryption=aws.elasticsearch.DomainNodeToNodeEncryptionArgs( enabled=True # Encrypt data between nodes for additional security. ), encrypt_at_rest=aws.elasticsearch.DomainEncryptAtRestArgs( enabled=True, # Encrypt data at rest for additional security. ), vpc_options=aws.elasticsearch.DomainVpcOptionsArgs( security_group_ids=[], # Specify security group IDs. subnet_ids=[] # Specify subnet IDs. ), access_policies="""{ "Version": "2012-10-17", "Statement": [ { "Action": "es:*", "Principal": "*", "Effect": "Allow", "Resource": "*" } ] }""" # Define access policies in IAM policy JSON format; adjust as necessary. ) # Export the endpoint URL of the Elasticsearch domain. pulumi.export("es_endpoint", es_domain.endpoint)

    When you run this program using Pulumi, it will provision the necessary resources in your AWS account. Be sure to have the AWS CLI configured with the correct access keys and region before running a Pulumi program. You can replace the placeholder values in security_group_ids and subnet_ids with your actual VPC configurations to suit your network security requirements.

    The IAM policy defined in access_policies for the Elasticsearch domain is wide open in this example, which means anyone can access the domain. You should replace the wildcard principal ("Principal": "*") with the actual IAM role or user that should have access to the domain. It is crucial to handle this carefully to ensure the security of your data.

    Finally, the endpoint of the Elasticsearch domain is exported. It gives you a URL which can be used to interact with your Elasticsearch cluster to index and search data. Ensure that you handle this URL securely, as it provides direct access to your Elasticsearch environment.