Hi, Adrian, and welcome back.
Now, in today's video, we are going to discuss about Amazon Kendra.
So at a high level overview, Amazon Kendra is a search service that enables us to search for structured
as well as unstructured data using the natural language processing and advanced search algorithms.
So this can be better explained with this diagram.
We're on the right hand side.
There are certain data sources you have S3 bucket, you have Microsoft, OneDrive, you have Confluence,
and in the middle you have Amazon.
Kendra That has the ability to go ahead and search for the documents that are part of these data sources
as an example.
Now user, when they have some requirement or when they have some question or a query, instead of directly
searching for the documentations that are part of these data sources, user can send the query to the
Kendra, and Kendra can in turn search for the data from these data sources and return back the response
immediately to the user.
So you can say this is something like a Google for your enterprise where it can search for the documents
and it can return the appropriate results.
So let's go ahead and have a quick demo.
Now for today's demo, I already have Kendra configured and as part of that data source, what I have
done, I have added a S3 bucket along with Kendra.
Now this is three bucket contains certain documentation related to the easy to service, Lambda Service
and others, and we'll be adding some queries and we'll look into how Kendra retrieves the results.
So let's go ahead and search for some of the index contents.
And within the query I'll say what is easy to I'll press enter and you see Kendra responded back with
the appropriate result of what is Amazon EC to now note that these results that are coming, they are
coming from the PDF that was uploaded at the S3 bucket level.
All right.
This is one important thing to note.
Now, one more thing that Kendra offers is sought by you have sort by relevance created date data source
and various others.
So this is also very helpful.
So let's try a few more things.
Let's say create new am I if I press enter again.
The appropriate result came on how you can create a EBS backed Linux Army.
Great.
So I hope with this at a high level overview, you understood the basics of Kendra.
Now, before we conclude, a few important things that I wanted to show you specifically related to
the data sources.
So whenever we create an index, then really we can add data source.
And this is one of the great benefits of Kendra is that it supports a wide variety of data source.
For example, FSCS is their RDX is their confidence again is quite popular in the organisations.
Amazon S3 you have GitHub, Google Drive, Slack.
JIRA is also very popular.
One drive is there and so on, so it can search for all of the data that are part of the supported data
sources and can return the appropriate results.
So that's the high level overview and with this will conclude today's video.