API reliability and performance: turning challenges into solutions

API reliability is about much more than uptime. It’s about knowing you can rely on an API to deliver in line with your expectations no matter how much you throw at it.

An unreliable API can be a liability for the API provider’s business and for the businesses of all the clients who rely on that API as part of their service delivery. That’s why we’re looking at API reliability and performance today, diving into how to turn the challenge of delivering a reliable API into a powerful performance your clients can trust.

What is API reliability?

API reliability refers to how consistent and available your API is and how likely it is to respond quickly to requests. A reliable API is predictable, well documented and has low latency while guaranteeing maximum uptime.

Reliability means delivering this even when your API is under pressure, whether from growing client numbers, significant spikes in usage or an event such as a distributed denial of service (DDoS) attack. This is essential to providing the API quality your clients can trust.

The benefits of reliable APIs

Reliable APIs bring benefits to providers and their clients. For providers, reliable internal APIs with an API gateway for microservices are often essential to smooth operations. In contrast, external API reliability supports a strong reputation, client growth and a better bottom line.

For clients using the API, reliability means peace of mind, as they can rely on the API quality to support the high availability and reliability of their services. This is important irrespective of which API management architectural and deployment pattern the client may use – API reliability is fundamental to all such considerations.

Measuring reliability

Measuring API reliability means defining key indicators for API performance and reliability and then implementing processes, structures and testing to ensure those indicators are met.

This encompasses measuring uptime, consistency, latency and other performance indicators. It also means tracking any downtime and outage events.

Best practices for ensuring API reliability

One of the benefits of Tyk is the all-in-one nature of its API management solution. Implementing a range of best practices designed to support maximum API reliability is easy. Let’s look at some of those best practices now.

Implement rate limiting and throttling

Rate limiting and throttling ensure your API doesn’t get overwhelmed by requests. You can use it flexibly based on your needs and those of your clients. With Tyk’s open source API gateway, for example, you can apply an API-level global rate limit, a key-level global rate limit and a key-level per-API rate limit.

By implementing rate limiting and throttling, you can grow your own business and watch your clients grow theirs, all without impacting the reliability and performance of your API. Using load balancing to distribute incoming API traffic across multiple services or instances can also help.

Set up rate monitoring and alerts to ensure you can spot and address any anomalies and issues in real time before they impact your API consumers.

Ensure consistent and well-defined API contracts

By clearly defining your API endpoints, request/response formats and HTTP methods, you can deliver a consistent and versioned API contract, which is fundamental to avoiding breaking changes. With versioning, cleaning communicates your policies to your clients and includes version information in your API’s URL to allow for backward compatibility.

Deliver zero downtime releases

Rolling out changes means carefully considering their potential impact on reliability long before you push them live. Releases need to be fine-tuned so as not to impact the user experience regarding reliability or performance. You also need to be able to roll them back painlessly (if necessary), again with no notable impact.

Remove single points of failure

In any system, a single point of failure is a major risk in terms of reliability. To provide APIs, it is essential to mitigate against any element of your architecture where an outage could bring everything tumbling down. Examples of this include using:

  • Diversified cloud storage
  • Multiple data centres spread across different regions.

Implement caching

For frequently accessed data, you can implement caching to reduce server load. Using content delivery networks (CDNs) to distribute content closer to users can also support reliability and performance through faster access.

Create a security-first culture

A robust approach to security, from solid authentication and authorisation mechanisms and role-based access control to defending against attacks on your API, means you’ll do all you can to ensure that a security incident doesn’t jeopardise your API’s reliability. Use input validation and output encoding as defence mechanisms to ensure robust API reliability even during SQL injection or cross-site scripting XSS attacks.

Use an API gateway

Using an API gateway can significantly enhance reliability and performance by centralising your APIs’ management, security and routing. Most gateways are designed to offer multiple features for reliability and scalability (amongst other things).

API management and reliability checklist

Ensuring reliability means keeping it in mind as you configure your API management solution and processes. A reliability checklist can help keep you focused, including items such as:

  • Securely connect your API management solution to your backend using OAuth 2.0 authorisation, mTLS, IP filtering on your backend or whatever best suits your requirements.
  • Securely expose APIs to third parties, ensuring each has its credentials.
  • Implement quotas, rate limits, throttling, load balancing and response caching.
  • Create a disaster recovery plan that includes ensuring reliability and performance during various scenarios, with key responsibilities and roles clearly defined. Undertake scenario testing, including restoration from backup, as part of the process.
  • Use multiple data centres and regions, with a strategy in place for ensuring reliability if one of them goes down.

Configuration recommendations for ensuring API reliability

Configuring your API management can do much to ensure API reliability. Examples include considering whether to configure rate limiting at the API global level, key global level or key per-API level, implementing response caching and the various best practices we’ve detailed above.

How do you test the reliability of an API?

Regular API reliability testing is essential to maintaining confidence in your API’s ongoing performance. Several API testing types can help you with this, so let’s quickly run through some of the most helpful. Remember that automation can help embed your API reliability testing, but human oversight is also always helpful.

Functional testing

Functional API testing is all about ensuring your API behaves as it should. It incorporates testing that the API contract is defined appropriately, that the component elements (response status and time, code, message, etc.) all work as expected and that the API will stand up to different scenarios.

Once you’ve tested that your API is functioning as expected with your test data, it’s time to test how it handles negative testing, feeding in unsuitable request types, incorrect parameters and so on.

Integration testing

No man is an island – and nor is an API. As such, you need to ensure your API plays nicely with others. This is where integration testing comes in. Use it to test your API communication and exchange data as intended with other APIs, services, etc.

Security testing

Clearly, security testing is not one of the API testing types you should take lightly. Poor security can leave your API open to attacks and your business open to data theft. It can also impact API reliability and performance. As such, test everything from authentication and authorisation processes to encryption, using penetration and fuzz testing regularly to ensure your API security remains robust.

Performance testing

Load testing, stress testing, and scalability testing (also called spike testing) are all key to understanding and ensuring the reliable performance of your API in different conditions.

API documentation testing

It’s essential to keep your documentation up to date, so check regularly that it reflects the behaviour of your API. If it doesn’t, update it to ensure it remains up-to-date and comprehensive.

Regression testing

Sometimes, things don’t work out as you expect them to. That’s why including regression testing in your API reliability testing processes is essential. Run regression testing each time you change your API to ensure you have kept everything intact in all the excitement of rolling out new functionality and features.

Reliability testing

While the above tests support API reliability, you can also undertake specific reliability testing. This is about ensuring the API delivers consistent test results before and after integrations with other services, before and after significant and sustained increases in consumption and so on.

Support for API reliability

Want to know more about ensuring API reliability? Then contact Tyk for a chat.