In this video, you’ll see how to set up Amazon Timestream data-source plugins for Amazon Managed Grafana.
With this integration, you can visually analyze Timestream metrics,
implement a single-pane-of-glass solution for Timestream data,
and reduce overhead associated with setting up a visualization environment.
To get started, let’s navigate to Amazon Timestream.
Amazon Timestream is a high-performance, serverless time series database service.
With Timestream, you can easily store and analyze sensor data for IoT applications,
metrics for DevOps use cases,
and telemetry for application monitoring scenarios such as clickstream data analysis.
Let’s create a database.
We can create a standard database with custom configuration or create a sample database and populate it with sample data.
We’ll create a sample database.
This sample dataset contains IoT sensor data from several truck fleets.
We can see the database we just created here.
Next, let’s return to the AWS Management Console and navigate to Amazon Managed Grafana.
With Amazon Managed Grafana, you can query, visualize, and understand your metrics no matter where they’re stored.
Let’s create a workspace.
A workspace is a logically isolated Grafana server that can integrate with data sources.
Let’s give this workspace a unique name.
Note that at least one authentication method must be enabled to log into this workspace.
We’ll AWS Single Sign-On (SSO).
We can choose service managed or customer managed as the permission type.
The customer managed permission type requires us to manually create an AWS Identity and Access Management (IAM) role.
We’ll choose the service managed permission type,
so AWS will automatically provision the permissions based on the services we choose.
Next, we can select data sources.
This will create an IAM role that enables Amazon Managed Grafana to access those resources in the current account.
For our purposes, we’ll select Amazon Timestream.
Now we’ll review the settings and create the workspace.
The workspace is created.
Next, we’ll define the users and groups that are allowed access to the Grafana dashboard.
As you can see, no users are assigned to this workspace.
Let’s assign one.
For the purposes of this example, we’ve already created a user called “grafana admin.”
Let’s assign this user to the Grafana workspace we just created.
By default, this user has viewer permissions.
Let’s make the user an admin.
As an admin this user can now log in, set up data source configuration,
and create dashboards in Grafana.
Now let’s go to the Grafana dashboard to sign in as the user we added.
We are now in the Grafana dashboard as a user with admin privileges.
Let’s add our Timestream database as a data source.
For our purposes, we’ll use the workspace IAM role as the authentication provider.
For the default region, we’ll select us-east-1.
Now we can select the database we created in Amazon Timesteam.
We can also select the sample table we included.
Next, let’s create a custom dashboard.
We’ll add an empty panel.
Let’s select “table” as the visualization type.
This dashboard is populated by specifying queries on the Amazon Timestream data source specified.
Let’s enter a query.
Our query generated a table.
Let’s give it a title.
Now we’ll apply our changes.
Additional panels can be added to the dashboard as needed.
For now, let’s save it.
We’ll give it a name.
As you can see, a separate IoT dashboard has already been created using the sample data we included.
Let’s take a look.
This dashboard has a title, a gauge, a pie chart, and a couple of tables.
The data is IoT sensor data from several truck fleets.
As you can see, data continually updates.
This dashboard can be used to streamline fleet management and identify cost optimization opportunities,
such as reduction in fuel consumption.
You’ve just seen how to set up Amazon Timestream data-source plugins for Amazon Managed Grafana.
You can learn more about this topic in the description and links for this video.
Thanks for watching. Now it’s your turn to try.