MuleSoft API Gateway: The Expert Best Practices

MuleSoft API Gateway is a critical component of the MuleSoft Anypoint Platform that provides a secure, scalable, and efficient way to manage, enforce, and monitor APIs. It was introduced as part of the Anypoint Platform in 2014. The functionality of the API Gateway focuses on API design, management, and runtime control, providing policy enforcement and security tools. It acts as a front-line security layer between API consumers and backend services, protecting APIs from unauthorized access, malicious threats, and overuse. 

The screenshot below depicts MuleSoft Universal API management capabilities at a high level.

This article explores the best practices of the MuleSoft API Gateway based on industry experience and feedback from MuleSoft experts.

Core components of MuleSoft API Gateway

API Proxy is an intermediary between API consumers and backend services, enabling traffic control and policy enforcement:

• Policies: Configurable rules are applied to APIs for authentication, traffic control, and logging tasks.
• Analytics: Tracks API usage and performance for optimization and troubleshooting.
• Secure Token Service (STS): Provides token issuance and validation to support secure API interactions.
• API Manager: A central console for managing APIs and applying policies via the Anypoint Platform.

The screenshot below depicts the API Gateway present in the Mulesoft ecosystem.

Enforce security policies

Use the gateway to add policies like OAuth 2.0 (at the experience layer), Client ID enforcement (at the experience and process layers), or IP whitelisting (at the experience layer). For context, the API layers, experience, process, and system, represent increasing levels of abstraction, with the experience layer focused on external consumption, the process layer on internal orchestration, and the system layer on direct backend interaction. 

For example, only authorized users should be able to access customer data APIs. This helps protect sensitive data and ensure that only trusted users access our systems.

The screenshot below depicts adding a Client ID enforcement policy in the Mulesoft Anypoint Platform at the API Manager level.

Example Client ID enforcement configuration

The snippet above shows the Client ID enforcement policy, which we can configure in API Manager specifically for an application. While exposing our API to the outside world with multiple clients, we can create specific client credentials (client ID and client secret) and share them with consumers. The benefit will be that our API will be secured, and all unwanted traffic will call the actual API.

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Use caching

Enable caching in the gateway to store frequently accessed data, such as product details or configurations, which avoids repeated backend calls. Caching should be carefully applied at different layers. Caching helps by reducing the load on backend systems and speeding up responses. Note, however, that implementing caching in the real-time system API can be risky because we might miss the latest records.

Choosing the right caching scope based on our specific use case is essential: per API, user, or global. For example, caching per API can improve response times for frequently accessed data, while caching per user ensures that personalized content, such as specific user information, is loaded quickly. Global caching helps reduce the load on backend systems, but it might not work well for data that changes frequently.

The screenshot below depicts adding an HTTP Caching policy in Mulesoft’s Anypoint Platform.

Caching is a very efficient technique in the API world, as each API hit comes with a cost and response time. If we get a similar request multiple times daily, we can use caching, which stores the input and the corresponding output. If the same request ID, for example, is received in the request, instead of calling the actual endpoint, it will get the response from the cache (object store is used in Mulesoft to store the results) and return it to the consumer.

Potential pitfalls of caching and how to mitigate them

Caching can be very effective, but there are some potential pitfalls, like serving stale data or overusing cache, which can lead to unnecessary memory usage—setting appropriate expiration times and updating the cache when the underlying data changes is essential to avoid stale data. Overuse of cache can be managed by caching only the most frequently accessed or resource-intensive data and by implementing cache policies to ensure that the cache doesn’t grow too large.

Implement rate limiting

Configure rate-limiting policies in the gateway to restrict the number of API calls a client can make in a specific time, such as 100 requests per minute. This prevents API abuse and stops backend systems from overloading.

To set up rate limiting, we can apply limits per client, user, or IP address. For example, we might restrict an API key to 100 requests per minute, allow an authenticated user 50 requests per hour, or restrict an IP address to 200 requests per day. These settings can be configured in our API gateway to ensure proper traffic control and prevent abuse.

When rate limits are exceeded, it's essential to handle this gracefully by returning the appropriate HTTP status code, such as 429 (Too Many Requests), to inform the client that they’ve hit the limit. We should also include a Retry-After header, which tells the client how long they must wait before making another request. This approach helps manage overuse while maintaining a smooth user experience. For example, we could return a 429 status with a Retry-After header set to 60 seconds.

The screenshot below depicts adding a rate-limiting policy in the Mulesoft Anypoint Platform at the API Manager level.

Implementing a rate-limiting policy is crucial for ensuring optimal API performance and security. This policy restricts client or application requests to an API within a defined time window, helping prevent system overloads and resource depletion. 

Organizations can use rate-limiting policies to effectively manage traffic spikes, safeguard backend systems from abuse, and maintain consistent API reliability. These policies often combine with other best practices like implementing throttling, authentication, and API monitoring to create a robust and secure API ecosystem. Additionally, rate limiting promotes fair resource usage among clients, ensuring better scalability and user experience.

Standardize API naming

Create clear and consistent names, like /v1/orders, for APIs exposed via the gateway. This will help developers and consumers understand the purpose and version of APIs.

The screenshot below depicts API naming standards we can use while designing the RAML in the API design center.

Standardizing API naming is key to keeping things clear and consistent across our APIs. It helps developers quickly understand what an API does by looking at its name, making it easier to use and share with others. Using clear and simple names that follow a set pattern saves time when searching for or working with APIs. It avoids confusion, speeds up onboarding for new team members, and gives our API catalog a more professional and organized look. It’s a small step that makes a big difference in making our APIs easy to manage and use.

The screenshot below shows how to use CurieTech AI's Repo Code Lens Agent, an AI tool that help to identify API names and flow names in selected repositories or for all repositories.

As highlighted above, one of the CurieTech AI  products, the Single Repo Code lens, takes input as repository location and branch. Then, the user can ask any question, like, “To list all the flow names in the project" As a result, all flow names that fall under the given repository location and branch will be listed.

The screenshot below shows how to use CurieTech AI's Multi Repo Code Lens Agent, an AI tool that takes input as a branch and works across multiple repos.

Enable API monitoring

Enable monitoring tools in the gateway to track traffic, response times, and errors. If an API’s response time increases, we can quickly identify the root cause.

We can add key metrics for monitoring, such as tracking response times for speed, error rates for reliability, traffic patterns for usage trends, and uptime for API availability to ensure performance and user satisfaction. We can also configure alerts to notify teams of anomalies like high response times, error spikes, or downtime, enabling proactive issue resolution and SLA compliance.

The screenshot below depicts the analytics Anypoint Monitoring provides in the Anypoint Platform.  

Enabling API monitoring is important to keep our APIs running smoothly and securely. It helps us track how our APIs are performing, spot any issues, and fix them quickly before they impact users. With proper monitoring, we can keep an eye on response times, error rates, and usage patterns, which makes it easier to maintain a reliable experience for everyone using our APIs. It also helps identify potential security threats or unusual activities. Monitoring ensures our APIs stay healthy and deliver consistent value to our business and users.

Use versioning

Expose different versions (e.g., v1, v2) of APIs through the gateway. For example, older clients can use /v1/customers, while newer clients use /v2/customers with additional fields. This supports backward compatibility without breaking older integrations.

The screenshot below depicts the configuration of API AutoDiscovery in Mulesoft Anypoint Studio.

API auto-discovery in MuleSoft makes it easy to manage APIs, especially when dealing with multiple versions. Let’s say we have two API versions: v1 and v2. By assigning a unique auto-discovery ID to each version, we can link them directly to the API Manager. This allows us to apply different policies, like rate limiting or security rules, to each version separately.

For example, stricter rate limits on v1 can be set to encourage users to switch to v2, which offers better features. Autodiscovery also lets us monitor traffic and track how each version is used, all from a single dashboard. It keeps everything organized, saves us from manually managing multiple versions, and ensures that we can keep things running smoothly while rolling out updates.

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We can also use an AI tool like CurieTech AI  to generate configuration snippets and the DataWeave transformations required to assign unique Auto Discovery IDs for different API versions, saving our time and effort. For example, while deploying v1 and v2, CurieTech AI can assist in quickly creating and validating the necessary configurations.

We must explicitly mention in the prompt to change v1 and v2 in the CurieTech AI—Code Enhancer agent. Then, it will create code changes and configurations related to v1 and v2.

The screenshot below shows how to use CurieTech AI's Code Enhancer Agent.  We prompt it to create a property file in YAML that maintains two versions of API and configure the auto-discovery with the v2 version.

As we can see below, it has created a YAML file maintaining both the API versions and changed the Auto-discovery configuration with the v2 version -

This ensures that both versions are correctly linked to API Manager, where we can apply different policies or track usage. By automating such repetitive and technical tasks, CurieTech AI makes it easier to manage multiple API versions efficiently, allowing us to focus on delivering improvements and ensuring a smooth experience for our users.

The screenshot below depicts the API published in Anypoint Exchange.

When we use API auto-discovery in conjunction with Anypoint Exchange, as shown above, the auto-discovery ID we assign to each API version helps link the deployed instance of the API with the API Manager. This allows us to manage and enforce policies for each version, monitor usage, and track performance—just as we would in Exchange, but with a more integrated runtime view.

So, while Anypoint Exchange is where the API versions are stored and shared, API instances and autodiscovery work together to ensure that each version is properly managed, monitored, and governed in the live environment. This integration provides a seamless experience for managing APIs across the development and runtime stages.

Automate deployment

Use tools like Jenkins/Azure DevOps to deploy gateway configurations automatically across environments like Dev, QA, and Prod. This saves time, reduces manual errors, and ensures consistency.

The screenshot below depicts the Azure DevOps dashboard where we can create the pipeline to automate deployments.

Automating deployment ensures consistency and efficiency in our API lifecycle management. As shown above, integrating tools like Azure DevOps into our workflow allows us to streamline the deployment of APIs across different environments without manual intervention. A CI/CD pipeline automatically builds, tests, and deploys our APIs to the development, staging, and production stages.

For example, when we push changes to the your code repository, the Azure DevOps pipeline can trigger a series of automated steps, including compiling the code, running tests, and deploying the API to the Anypoint Platform. This reduces the chances of human error and speeds up the delivery process. Automated deployments ensure that every change is consistently tested and deployed, improving the speed and reliability of our API updates. This is especially beneficial when managing multiple API versions and environments, ensuring a smooth and predictable deployment process every time.

Log and audit API activity

Enable logging in the gateway to capture data about who accessed the API and when. Logs can help trace the issue if unauthorized access occurs. This practice aids in debugging and ensures compliance with regulations.

We can safely log only necessary details, such as user IDs, timestamps, and API request/response metadata. To prevent exposure, avoid logging sensitive data like passwords, personal identifiers (PII), and financial information. For compliance with regulations like GDPR or CCPA, mask sensitive fields in logs (e.g., using DataWeave or custom logging policies). Encrypt log files to secure data at rest.

The screenshot below depicts the logs in the Mulesoft Anypoint Platform at the Runtime Manager level.

Some AI tools, like CurieTech AI Agent, can help add/update logs in Mulesoft flows with INFO/DEBUG mode and avoid sensitive data in the loggers. Avoiding sensitive and unwanted information helps reduce the log buffer size as much as possible since Mulesoft has a 200 MB log size limit in Cloudhub, irrespective of the Mulesoft license purchased.

The screenshot below depicts the logs in the Mulesoft Anypoint Platform at the Monitoring level.

The screenshot above shows the Anypoint Monitoring dashboard provided by Mulesoft on the Anypoint Platform Account (which typically requires a separate license or subscription but is included with Anypoint Platform's Titanium subscription). It is a powerful tool that helps us monitor the performance and health of our APIs and integrations in real time. By integrating Anypoint Monitoring into our workflow, we can automatically collect metrics like response times, error rates, and throughput, allowing us to detect issues early and ensure that our APIs run smoothly.

For example, with Anypoint Monitoring, we can set up alerts to notify us whenever an API's performance drops below a certain threshold or when error rates spike. This proactive approach helps us address problems before they affect users. It also provides valuable insights into traffic patterns and API usage, which can help us optimize performance and plan for future scaling. Overall, Anypoint Monitoring ensures that our APIs are reliable, efficient, and always available to our users.

Apply global policies

Define reusable policies, such as security headers or throttling, and apply them to all APIs through the gateway. This approach reduces effort and ensures that all APIs are consistently protected.

The screenshot below depicts the creation of automated policies in the Mulesoft Anypoint Platform at the API Manager level.

As shown above, applying global policies is essential for maintaining consistent security, governance, and performance across all our APIs. With MuleSoft, we can define and use global policies at the API Gateway level, ensuring that every API deployed within our environment follows the same rules, regardless of its version or lifecycle stage.

For example, we can apply security policies like OAuth2, API Key Validation, or Rate Limiting globally to ensure that every API is protected similarly. This simplifies management by avoiding configuring these policies individually for each API. Additionally, global policies help maintain uniformity and enforce best practices across our API ecosystem, improving compliance, security, and overall efficiency. Applying these policies ensures that our APIs are consistently governed, reducing the risk of errors or gaps in security.

Optimize backend connections

Set connection pooling and retries for backend systems in the gateway. For instance, if a database call fails, the gateway can retry it without impacting the client. This results in reduced latency and reliable communication with backend systems.

The screenshot below depicts the database configuration for advanced settings in the Mulesoft Anypoint Studio to optimize connectivity.

This practice is essential for improving the performance and scalability of our APIs. By efficiently managing how our APIs connect to backend systems, we can reduce latency, increase throughput, and ensure stable performance even during high-traffic periods.

One way to optimize these connections is by using connection pooling, as shown in the screenshot above. Connection pooling allows us to reuse database or service connections instead of creating new ones for each request. This reduces the overhead of repeatedly opening and closing connections, leading to faster response times and lower resource usage. By configuring connection pooling correctly, we can ensure that backend resources are used efficiently, improving overall system performance and reliability. This is especially important when dealing with high-volume API calls or integrating with external services that require frequent communication.

An AI tool like CurieTech AI can easily add these configurations, which saves a lot of time and is highly accurate compared to manual configurations.

Below is one of the CurieTech AI products - Code Enhancer

Here, we need to provide the project repository. In the description, we must mention what changes we want CurieTech AI to perform on the existing code, such as “I have a global config file and an HTTP listener configuration in that. Can we please replace all the hardcoding with property names”?

As shown below, the tool prompts for adding two new property YAML files and an update in the global-config file -

Once we approve, it will generate an updated XML file and two newly created property YAML files.

Automate API transformations

Transformation policies are used at the gateway to modify request or response payloads. Creating DataWeave scripts for these transformations can be time-consuming and error-prone.

CurieTech AI analyzes our payload structures (e.g., JSON, XML, CSV) and automatically generates DataWeave scripts tailored to our requirements. It also suggests corrections or optimizations, ensuring our scripts are efficient and follow best practices.

The screenshot below depicts the CurieTech AI, which auto-creates the DWL expression based on the input and output provided.

Here is the generated DWL expression by the CurieTech AI:

When applying multiple transformation policies at the API Gateway (e.g., format conversion, field masking), CurieTech AI can auto-generate these scripts, saving significant time. This lets developers focus on high-level logic rather than manually writing and debugging code.

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Conclusion

The MuleSoft API Gateway is a cornerstone of the Anypoint Platform, enabling secure, efficient, and scalable API management. By following best practices, we ensure our APIs remain robust, scalable, and easy to manage. These practices simplify API management while protecting our systems and enhancing user experiences. When implemented, these practices make the MuleSoft API Gateway a powerful tool for delivering secure, high-performance, reliable integrations essential for businesses working in MuleSoft-related environments.