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+---
+title: Proven Schema Designs and Best Practices - Part 1
+description: From a GraphQL Conf 2025 talk -- proven schema design approaches and patterns.
+date: 2025-10-06
+authors: [jdolle]
+tags: [graphql]
+---
+
+GraphQL provides many benefits over other query languages. Federation builds on top of this
+foundation to provide even more flexibility and power. But even with all that GraphQL has to offer,
+API design remains difficult.
+
+Over time, we've developed some proven design philosophies and patterns for easier schema
+migrations, exposing errors, and avoiding ambiguous or misleading type names.
+
+## Schema Design Goals and Solutions
+
+As you design your schema, keep in mind that:
+
+> You can and should future proof your schemas as much as possible, but it’s okay for the schema not
+> to be perfect. Products change, requirements change. There will be chaos. But if we can tend to
+> our schemas, we can encourage them to grow and evolve organically -- much like a garden.
+
+To better tend to our schemas, we can design with some goals in mind, follow some battle tested
+patterns, and approach type creation methodically.
+
+### Flexible
+
+The first goal is for your schema to be easy to change over time. As I mentioned before, entropy is
+a constant.
+
+And if you anticipate and prepare for change then you can more easily adapt your schema to fit the
+needs of your consumers.
+
+---
+
+![Flexible](./flexible-01.jpg)
+
+It may be unintuitive, but keeping your field arguments concise and inflexible is one way to help
+keep your schema as a whole more flexible.
+
+So don’t overload your arguments or an input type with a bunch of optional ways of doing things. By
+keeping fields more focused, we limit the impact that any one change can have. And if we do need to
+break things, the blast radius to your API consumers is much smaller.
+
+---
+
+![Flexible](./flexible-02.jpg)
+
+Overloading arguments can also hurt performance by requiring your resolver to do many more things
+before returning.
+
+So it’s best to keep your mutations focused on a specific task.
+
+---
+
+![Flexible](./flexible-03.jpg)
+
+Here we have two examples of User types, but on the left is only what your consumer NEEDS, and on
+the right maybe is everything you know about a user. It should be obvious that the left is much
+easier to maintain.
+
+Unnecessary fields often go unused or worse, they may cause technical debt because the format of the
+data ends up needing changes because it doesn't fit with the new requirements.
+
+---
+
+![Flexible](./flexible-04.jpg)
+
+Tooling such as Hive Console can also help. We offer a feature called “Conditional Breaking Changes”
+that checks usage data on breaking changes. And if the portion of the schema that broke isn’t used,
+then the change is allowed. Otherwise the change is still flagged as breaking.
+
+This lets you safely migrate your schema and eliminates the need to manually check usage when making
+breaking changes.
+
+### Accessible & Efficient
+
+Another goal is that traversing the graph should be quick – with as few hops as reasonably possible.
+
+This makes the API more client friendly and reduces strain on your system from too many lookups or
+connections.
+
+---
+
+![Accessible](./accessible-01.jpg)
+
+A proven way of doing this is by using a common “Node” interface for every entity type. But so long
+as you expose a way to access related types, then that's what's important.
+
+---
+
+![Accessible](./accessible-02.jpg)
+
+Another way to make your API more accessible is to better support partial results.
+
+Returning partial data can dramatically improve a user’s experience for example if your system has a
+partial outage. Keeping root query fields nullable ensures any one field can’t break the entire
+client operation.
+
+---
+
+### Safe & Secure
+
+To have a secure schema means to avoid leaking sensitive information, but also not being vulnerable
+to attacks. One major vulnerability of vanilla GraphQL is Denial of Service attacks.
+
+There’s no substitution for setting reasonable request timeouts. But tooling that restricts the size
+of requests or that rate limits requests are also necessary for preventing DoS attacks
+
+---
+
+![Secure](./secure-01.jpg)
+
+GraphQL Armor is a popular tool that has been integrated into most server implementations. It allows
+you to restrict operations with a number of configuration options.
+
+---
+
+![Secure](./secure-02.jpg)
+
+There’s also a few ways of designing your schema to limit attacks by limiting response sizes.
+
+This schema shows the Relay Pagination Spec. Using pagination limits the amount load from any one
+field. There are also other pagination specs that are equality suited.
+
+Pagination is important to reduce the potential for DDOS attacks and to increase responsiveness of
+your API, regardless of rate limiting or other protections.
+
+However, if you know your data is guaranteed to have a small upper bound, then you can get away with
+a simple array. Pagination adds a lot of complexity which is nice to avoid it if you can.
+
+---
+
+![Secure](./secure-03.jpg)
+
+Also don’t place Binary Files or other large response fields in the Schema. Leverage CDNs and other
+purpose built solutions meant for dealing with these files.
+
+---
+
+### Interactive
+
+Another goal is for the schema to expose clear ways to interact with it. This may seem obvious, but
+many times edge cases such as errors are forgotten or ignored.
+
+---
+
+![Interactive](./interactive-01.jpg)
+
+Placing your expected errors in the schema is incredibly valuable for consumers of your API. This
+lets your API’s consumers know what can go wrong and potentially how to fix the issues.
+
+This is sometimes called “typed errors” or “errors as data” or sometimes “expected errors”. But
+whatever you call it, be sure to add meaningful fields to your errors so that clients can show
+helpful information to users instead of a generic “Something went wrong” message.
+
+However, don't move every possible intermittent failure into your schema. These errors are
+potentially numerous and are meaningless to the API consumer. Those should be thrown and masked in
+production to avoid leaking potentially sensitive information and to avoid forcing clients to handle
+these cases.
+
+---
+
+![Interactive](./interactive-02.jpg)
+
+There are a few convenient ways to expose an error type in you schema. The first is to return a
+union of your success results and error results. This adds the minimal number of types to your
+schema, but relies on convention to separate the types. The other is to create a response type that
+has fields indicating whether or not the request was successful or errored.
+
+One is convention and the other is codified, but otherwise there isn't much difference. Both are
+good.
+
+---
+
+### Consistent
+
+Consistency is promoted by using patterns. And patterns make it easier for your team to develop
+because they know “how things are done”. This applies to both developing and consuming the schema.
+If everything is slightly different then it’s much harder to navigate because nothing is intuitive.
+
+---
+
+![Consistent](./consistent-01.jpg)
+
+Consistency comes from implementing all of these things all the time. Tools like linters can help --
+particularly when implementing linting rules in a Schema Registry so that every schema is consistent
+with one another.
+
+---
+
+### Descriptive & Unambiguous
+
+The last goal is to be descriptive and unambiguous. This means that our entities are accurately
+reflected in the schema using a shared language. Shared language is the common set of terms that are
+used to describe a thing such that there's no confusion about its identity. Simply put, shared
+language is what everybody calls something.
+
+There are a number of approaches that can be used to group fields and determine your shared
+language. In part 2 of this article, we'll look at a few approaches and how they can be used to
+create a descriptive and unambiguous schema.
+
+---
+
+_This had been adapted from a talk given at GraphQL Conf 2025. A link will be added when the video
+is made available to the public on the
+[@GraphQLFoundation](https://www.youtube.com/@GraphQLFoundation) Youtube channel._
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