Video Transcript (English)

Welcome back! Now that you’ve deployed your first cluster, let’s explore more about Atlas and see what it can do.

In this video, we will walk through some of the most useful out-of-the-box features that can be accessed via the Atlas UI.

We’ll start by loading a sample dataset. Then, we’ll explore some advanced features Atlas provides and how to access them in the UI.

Starting where we left off, we see the option to load a sample dataset on the project overview page, let’s go ahead and select it.

The dataset can take a few minutes to load.

Once the data is loaded, we can examine it by selecting the collections tab or "Browse Collections.".

We’re redirected to the dashboard within the Collections page. On the left side we can view the different databases and collections available in this cluster, as well as sample documents for the selected collection

The Find bar lets us query for specific documents. For example, we can search for a document in the accounts collection if we have the account_id.

Let’s search for the account_id of 794875.

As you can see, our searched document is the only one shown in the results.Nice!

The Atlas UI allows us to perform CRUD operations, build aggregation pipelines, and create search indexes which allow you to use Atlas Search and Atlas Vector Search. We will cover these features in more detail in later units.

If you prefer working in a command line environment, you can also use the command line tools tab for guided assistance on how to get started. Under this tab there are also tools to help with connecting your application to the cluster, as well as importing and exporting data.

Before moving on, let’s highlight a few more operational management features available on dedicated-tier clusters.

Under the metrics tab, there are a few key metrics that indicate the health of the cluster.

With an M10 and above cluster, we can get even more insights by using the Real-Time Performance Panel. This panel offers a wider breadth of metrics including current network traffic, query execution and performance, database operations on the machines hosting your MongoDB clusters, and hardware statistics about the hosts.

Similarly, the Performance Advisor looks at the health of the cluster and provides guidance on how to improve performance. For example it identifies potential pain points and their solutions.

There’s also the Online Archive. As the name suggests, this tool optimizes storage in our cluster but allows us to query for infrequently accessed data.

And there you have it! We have created an Atlas account, deployed our first cluster, loaded sample data, and explored that data in the Atlas UI.

We also know about some helpful features that come with a dedicated cluster, including the Real-Time Performance Panel, the Performance Advisor, and Online Archive.

You’re now ready to dive into all things MongoDB. Until next time, keep learning!