10. Observability with Apollo Studio
8m

Overview

The Airlock team has successfully implemented its newest feature (Project Galactic Coordinates), which has evolved and expanded the capabilities of the Airlock . They've also made sure to maintain the graph by adding new and removing unused . Let's explore how we can continue to keep track of the graph's health and performance.

In this lesson, we will:

  • Explore insights through the and metrics provided by
  • Learn how to interpret metrics for executions and referencing s

Metrics in Apollo Studio

Apollo Studio provides us with observability tools to track the health and performance of our . These tools help surface patterns in how our graph gets used, which helps us identify ways to continue improving our graph.

We can find these metrics under the Insights page in Studio.

Operation metrics

The Operations tab is selected by default in the Insights page. It gives us an overview of request rates, service time, and error percentages, including specific operations for each of these that might be worth drilling deeper into.

https://studio.apollographql.com

Insights page in Studio, showing Operations tab

We recommend that clients clearly name each they send to the graph, because these are the you'll see in your Studio metrics.

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

It looks like one of Airlock's highest-requested is GetListing. We can click on the to see more detailed insights.

https://studio.apollographql.com

Operations page filter for a specific operation in Studio

Field usage

Apollo Studio also gives us insight into the usage metrics of our 's . We can navigate to this page by clicking the Fields tab inside the Insights page.

https://studio.apollographql.com

Fields page in Studio

We can use the dropdowns on the top-right side of the page to filter metrics based on a custom time range.

Let's take a closer look at the Listing.overallRating as an example. In the Usage section, we can see exactly which include the Listing.overallRating :

https://studio.apollographql.com

Fields page details for a specific field in Studio

https://studio.apollographql.com

Fields page details for a specific field in Studio

With a larger time period filter, we can see two new columns: requests and executions.

https://studio.apollographql.com

Fields page details for a specific field in Studio

usage metrics fall under two categories: field requests and field executions.

  • Field requests represent how many were sent by clients over a given time period that included the .
  • Field executions represent how many times your servers have executed the for the over a given time period.

Note: The values for executions and referencing can differ significantly. You can find out the possible reasons by reading the Apollo docs on field usage metrics.

Using insights

We can use these metrics to monitor the health and usage of our 's types and . This helps us answer questions like:

  • Are there some that don't get any use at all? Are there deprecated fields from long ago that aren't being used but are still in the schema? Maybe it's time to remove these from the to keep our schema clean and useful.
  • Are we planning on making a significant change to a ? Which clients and would be affected? We'll need to make sure they're looped into any changes we make.

As our evolves, these are good questions to keep in mind, and Apollo Studio will always be there to help answer them!

Practice

If you needed to know how many times a field has been resolved, which metric would you use?
If you needed to know how many operations have included a field, which metric would you use?
Which of the following operation metrics does GraphOS provide?

Key takeaways

  • metrics provide an overview of operation request rates, service time, and error percentages within a given time period or for a specific operation.
  • metrics include field requests (how many were sent that included that field) and field executions (how many times the for the field has been executed).

Congratulations 🎉

Well done, you've reached the end! In this course, we learned all about how to work with an existing in production. We saw how to incorporate and graph into a CI/CD workflow so we can ship new features with confidence. We also explored different types of errors we might encounter from build checks and checks. Finally, we looked at how to use Apollo Studio to discover metrics on our client operations and usage.

See you in the next series!

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