Overview

GraphOS provides us with observability tools to monitor the health and performance of our supergraph. These tools help surface patterns in how our supergraph gets used, which helps us continue to improve it.

In this lesson, we will:

• Explore the operation and field metrics provided by GraphOS
• Set up client awareness to indicate which operations were sent by which client

Sending (fake) traffic to the supergraph

We're still in tutorial-land, so there isn't any real production traffic going to our supergraph. Unless you actually went ahead and shared your API with others, in which case, good for you!

Let's go ahead and get some numbers in here so we can walk through what it might look like if we did have more traffic.

The Code Sandbox below contains a script that takes a supergraph URL and sends requests to it over a period of time. We'll use it to send fake traffic to our supergraph.

Go ahead and enter your URL (you can find that at the top of your supergraph's README page). Then press the button to trigger the script!

Now we're ready to dive into our supergraph metrics!

Operation metrics

Let's head back to Studio, where our supergraph metrics live. First, let's check out Operations.

This gives us an overview of operation request rates, service time, and error percentages, including specific operations for each of these that might be worth drilling deeper into.

We recommend that clients clearly name each GraphQL operation they send to the supergraph, so we can easily view them in our metrics.

We can also filter to select a particular operation to see more specific details about its usage, as well as its signature, which is the shape of the query. We can see the number of requests that have been made and how long each request takes over time.

Field metrics

Next, let's check out field metrics. Head over to the Fields page.

Beside each field, we'll see the number of requesting operations, which is the number of operations in a given period that have included that particular field.

And once again we can dive deeper. Click the metrics button for the field to navigate to a detailed view.

We can use both operation and field metrics to monitor the health and usage of our supergraph's types and fields and determine where we can start to improve, based on how they're performing and how our clients are using them.

Client awareness

Client awareness is another powerful feature of GraphOS. Over on the Clients page we can check out how each of our clients is using our supergraph, such as which operations they're requesting the most, any issues they're running into and which fields they're using. Having access to client-specific metrics is cool because it gives us a heads up on when to deprecate or optimize certain fields.

For both operations and field metrics, you can also see client usage information when you dig into a specific operation or field.

To enable client awareness, clients should send two specific HTTP headers in their requests: apollographql-client-name and apollographql-client-version.

We recommend encouraging all downstream clients to include those client-specific headers with every request. This information will show up on GraphOS so we can see exactly where requests are coming from.

Practice

Key takeaways

• Operation metrics provide an overview of operation request rates, service time, and error percentages within a given time period or for a specific operation.
• Field metrics include the requesting operations metric, which lists the number of operations in a given period that have included the particular field.
• To set up client-aware metrics in GraphOS, incoming requests should include one of these headers: apollographql-client-name and apollographql-client-version.

Up next

We're now equipped with helpful observability tools to give us a peek into our supergraph as more and more clients start using it. Speaking of clients, let's take advantage of a cool feature from our cloud router to improve the client querying experience.