API governance should help developers move faster, not slow them down. Yet in many organizations, governance still depends on manual reviews, scattered documentation and rules that are easy to forget. That does not scale when your API ecosystem keeps growing. Automated API governance changes that.
Why API governance is hard to execute
Most organizations already have API standards. They define naming conventions, security requirements, documentation rules and design guidelines. On paper, that looks like governance.
In practice, execution is harder. Developers need to know where the rules are documented. Reviewers need to check whether they are applied correctly. Teams need to interpret standards in the same way. And as the number of APIs grows, manual governance quickly becomes inconsistent.
That creates a gap between what organizations agree on and what teams actually build.
The risk of growing API complexity
APIs create value by connecting systems, exposing data, supporting digital services and enabling partner ecosystems. But without clear governance, that value can turn into complexity.
- Inconsistent API design
- Poor documentation quality
- Duplicate implementation patterns
- Security and compliance gaps
- More technical debt
- Slower developer onboarding
- Higher maintenance costs
Automated API governance helps close that gap. Not by replacing architecture or expertise, but by making agreed standards easier to apply.
What should you automate?
Not every governance decision should be automated. Automation works best for rules that are objective, repeatable and easy to validate.
- Is a required description present?
- Does the naming follow the agreed convention?
- Are standard response codes included?
- Is the API description structured correctly?
- Are mandatory metadata fields available?
- Are specific OpenAPI features used consistently?
These implementation-related decisions can often be checked automatically before an API moves further through the development process. That gives developers fast feedback and reduces the need for manual review.
What should stay human?
Some decisions require architectural thinking and business context.
- Which operations should this API support?
- Which parameters are needed?
- Which endpoints should be exposed?
- Is the API design intuitive?
- Does the API support the business process correctly?
- Is the security model appropriate for the use case?
These are design decisions. Automation can support them, but it should not replace human judgement. Good governance combines automated checks with expert guidance where context matters.
Let’s setup some automated rules
Note: Throughout this example we’ll be using the Pet Store 3.1.0 specification example. Usually, we’re not too keen on using this example since it’s hardly representative of API descriptions you’ll encounter in real-life projects. Since we’re looking at implementing tooling to an API description and not the description itself, we’re fine using this.
We’ll be using npm and Spectral to create two custom rules we’ll apply to the Pet Store specification. Assuming you haven’t worked with Spectral before we’ll start with a global install so we can use the CLI on our local machine.
Reference spectral documentation for CICD integration or other setups.
After installing we can start writing a custom rule. In our working directory we only have our `petstore.openapi.yml` API specification.
Running the `spectral lint` command will clarify we need to provide a ruleset to apply.
Let’s create a custom ruleset called `object-policies.spectral.json` in which we’ll define our custom rule.
The goal of this rule is to enforce developers to include a `description` property for all schemas they define.
Important! Take into consideration the intent of the policy within the development process. Why should a developer be enforced to add a property as this is a seemingly added technical constraint.
Our rationale here is to enforce a description to be present because we want to make sure a functional description is added. Because we want to ensure our API descriptions will be easily understood by external developers.
Part of writing the rule is to determine the severity. This can strongly impact the development process depending on how and where the linting is done.
Decide together with all related teams what is important enough to halt the pipeline and what should be considered a warning or hint.
To apply the rule, we’ve written to the specification we execute `spectral lint petstore.openapi.yml --ruleset object-policies.spectral.json`.
For this example, I’ve decided to create a dedicated file to contain all policies related to object validation. When you simply create a file called “.spectral.json”, Spectral will automatically apply these rule without the explicit “--ruleset” flag.
Let’s add an additional rule. Our goal is to improve the readability of the API description with the emphasis of having a clear description for Schema Components.
Now we validate if the description property is present, we’ll check if our agreed upon template is used to formulate the functional description.
We use a built-in function to apply a Regex to the content of the description property of each available Schema.
The intention of this validation rule is to give warnings to developers that their Schema description is lacking a functional description template that recommend to use to achieve consistent definitions that are more likely to be understood by external developers.
If we run the linter again, we’ll see the new finding listed as a warning within the result. That’s it! There are many tools to choose from, each with their own quirks, positives and negatives. As well as a million different rules you could import, write and implement.
Start small and scale from there
You do not need to automate every governance policy from day one. Start with one rule that is important, easy to understand and easy to automate. Test it with a pilot team. Learn from the feedback. Then expand.
Over time, your organization can build automated checks for documentation, naming, security, versioning, metadata and lifecycle management. The goal is not to create more control. The goal is to make good API development easier.
API governance should enable, not restrict
The best API governance does not sit at the end of the process as a manual gate. It is embedded into the development workflow. Developers get fast feedback. Reviewers spend less time on small checks. Architecture teams can focus on decisions that require real expertise.
That is how governance becomes scalable. For larger organizations, this often evolves into a Center of Enablement: a dedicated team that creates standards, builds reusable assets, supports automation and coaches development teams.
Its role is not to police developers. Its role is to remove barriers and help teams maximize API value.
Final thoughts: automate what helps
API governance is hard because it sits at the intersection of technology, people and process. There is no universal model that works for every organization. But one principle applies almost everywhere: governance should make good API development easier.
Automation helps by turning standards into fast, repeatable feedback. Clear rules. Automated checks. Better consistency. Less friction. That is how API governance becomes an enabler of speed, quality and scale.
Want to improve API governance without slowing down development?
AppyThings helps organizations design and implement practical API governance models that support developers, reduce complexity and improve API quality at scale.
From maturity assessments and governance frameworks to automated policy enforcement and developer enablement, our experts help you turn API governance into a strategic capability.
Ready to make API governance work for your teams? Talk to our experts.
