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Implementing an Elasticsearch Backed Search Microservice

In this lab, we will create a Lambda function which will connect the provided web interface to an Elasticsearch domain to provide search functionality. **Note:** This lab can have extended launch times (10 to 30 minutes).

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Path Info

Clock icon Advanced
Clock icon 1h 30m
Clock icon Apr 20, 2021

Contact sales

By filling out this form and clicking submit, you acknowledge our privacy policy.

Table of Contents

  1. Challenge

    Investigate the Lab Environment

    With the provided information, log in to the AWS web console and look around at the provided resources. You should find:

    • An Elasticsearch domain
    • A Franken_Search Lambda function
    • An S3 bucket containing the files for the Frankenwords site
    • An API Gateway configured to trigger the Franken_Search Lambda function
  2. Challenge

    Update the Lambda Function

    Update the Franken_Search function to forward an appropriately formatted query to the provided Elasticsearch domain and return a JSON string with the required information.

    The JSON object, which is expected by the frontend site, should be structured as follows:

        "total_hits": integer,
        "chapter_count": integer,
        "total_score": float,
        "hits": [
                "location": string,
                "score": float
  3. Challenge

    Test Frankenwords!

    Test the Frankenwords site to ensure functionality, and learn how often words and phrases are used in Mary Shelley's Frankenstein!

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