Amazon Kendra is a highly accurate and simple-to-use intelligent search service powered by machine learning (ML). Amazon Kendra offers a suite of data source connectors to simplify the process of ingesting and indexing your content, wherever it resides.
Valuable data in organizations is stored in both structured and unstructured repositories. An enterprise search solution should be able to pull together data across several structured and unstructured repositories to index and search on.
One such data repository is ServiceNow. As the foundation for all digital workflows, the ServiceNow Platform® connects people, functions, and systems across your organization. As data accumulates over time, a lot of critical information is stored in service catalogs, knowledge articles, and incidents including attachments for each entry.
We’re excited to announce that we have updated the ServiceNow connector for Amazon Kendra to add even more capabilities. In this version (V2), you can now crawl knowledge articles, service catalog documents, and incidents, and also bring in identity/ACL information to make your searches more granular. The connector also supports ServiceNow versions of Tokyo, Rome, San Diego, and others, and two sync modes: Full Sync mode, which does forced full syncs, and New, Modified, and Deleted mode, which does incremental syncs.
With Amazon Kendra, you can configure multiple data sources to provide a central place to index and search across your document repository. For our solution, we demonstrate how to index a ServiceNow repository using the Amazon Kendra connector for ServiceNow. The solution consists of the following steps:
To try out the Amazon Kendra connector for ServiceNow, you need the following:
Before we set up the ServiceNow data source, we need a few details about your ServiceNow repository. Let’s gather those in advance.
The session token is valid for up to 30 minutes. You have to generate a new session token each time you index the content, or you can configure Access Token Lifespan with a longer time.
To store your ServiceNow credentials in Secrets Manager, compete the following steps:
To configure the Amazon Kendra connector, complete the following steps:
Now that you have ingested the content from your ServiceNow account into your Amazon Kendra index, you can test some queries.
Go to your index and choose Search indexed content. Enter a sample search query and test out your search results (your query will vary based on the contents of your account).
The ServiceNow connector also optionally crawls local identity information from ServiceNow. For users, it sets the user email ID as principal. For groups, it sets the group ID as principal. If you turn off identity crawling, then you need to upload the user and group mapping to the principal store using the PutPrincipalMapping API. To filter search results by users or groups, complete the following steps:
This brings you a filtered set of results based on your criteria.
Congratulations! You have successfully used Amazon Kendra to surface answers and insights based on the content indexed from your ServiceNow account.
It is good practice to clean up (delete) any resources you no longer want to use. Cleaning up AWS resources prevents your account from incurring any further charges.
With the ServiceNow connector for Amazon Kendra, organizations can tap into the repository of information stored in their account securely using intelligent search powered by Amazon Kendra.
In this post, we introduced you to the basics, but there are many additional features that we didn’t cover. For example:
To learn about these possibilities and more, refer to the Amazon Kendra Developer Guide.
Senthil Ramachandran is an Enterprise Solutions Architect at AWS, supporting customers in the US North East. He is primarily focused on Cloud adoption and Digital Transformation in Financial Services Industry. Senthil’s area of interest is AI, especially Deep Learning and Machine Learning. He focuses on application automations with continuous learning and improving human enterprise experience. Senthil enjoys watching Autosport, Soccer and spending time with his family.
Ashish Lagwankar is a Senior Enterprise Solutions Architect at AWS. His core interests include AI/ML, serverless, and container technologies. Ashish is based in the Boston, MA, area and enjoys reading, outdoors, and spending time with his family.