API Monitoring: Metrics, Tips & Best PracticesBlank

Why are APIs central to modern software development?

APIs have become the backbone of modern software, enabling communication between microservices, cloud services, and third-party platforms. But this critical role also makes them a source of fragility: a single failed API call can disrupt transactions, slow applications, or cause outages.

That’s why API monitoring best practices are essential. Monitoring ensures APIs remain reliable, available, and performant. It also gives DevOps and SRE teams the visibility to detect issues before they impact users. In this guide, we’ll explore API types, key metrics, best practices, debugging strategies, and how to select the right monitoring tools.

What are the main types of APIs?

An API is a set of functions or procedures that govern the access points for a given system, service, or application. Currently, the two main competing approaches that offer extensibility to APIs for creating web services are the Simple Object Access Protocol (SOAP) and Representational State Transfer (REST). GraphQL has become a popular alternative to REST in recent years for specific use cases. There are also a few lesser-used alternatives.

SOAP API

SOAP APIs are strictly based on XML and HTTP protocols. Sending a SOAP request is like using an envelope to send a message. SOAP APIs incur extra overhead and bandwidth overhead, and require more work on both the client and server ends. That said, like envelopes, SOAP provides more stringent security than REST.

REST API

If SOAP is like an envelope, REST is more like a lightweight postcard. REST APIs are considered the gold standard for scalability and are highly compatible with microservice architecture.

REST APIs are high-performing (especially over HTTP2), time-tested, and support many data formats. REST APIs also decouple the client and server, ensuring independent evolution. However, building a true REST API is difficult because it requires a disciplined adherence to the Uniform Interface constraint. Many organizations trade off the long-term benefits of a truly RESTful API for HTTP APIs that offer similar benefits but adhere to REST constraints more loosely.

Cloud providers like AWS offer services such as API Gateway that help other vendors create REST API endpoints.

HTTP API

As mentioned earlier, HTTP APIs can be very similar to REST APIs. HTTP APIs are ranked by the Richardson Maturity Model based on their compliance with REST constraints. In reality, most APIs fall somewhere in this category.

GraphQL API

GraphQL APIs are contract-driven and come with introspection out of the box. Building an API with GraphQL is much easier than building a true REST API, which requires extensive knowledge of HTTP to build intelligently.

Their downside, however, is that they do not scale well and require tight coupling between the client and server. GraphQL queries become more expensive to parse and execute as they get bigger — and they also lack certain concepts native to HTTP, such as content and language negotiation.

What is API monitoring, and why is it important?

API monitoring is the process of continuously checking for both the availability of your endpoints and the validity of their data exchanges. While monitoring your APIs, you also gain visibility into how they perform (e.g., time to respond to requests from various locations or to increasingly complex queries).

You monitor APIs to detect failed or slow application transactions before your end users report the problem.

Ensure multi-step transactions are successful

Nowadays, web applications rely on APIs that provide abstraction layers between the microservices that make up your application, as well as third-party services to embed additional functionality that enriches user experience. This architecture leads to dependency on complex multi-step transactions and third-party API integrations.

For example, if a third-party search widget on your e-commerce site fails, your customers will be unable to browse through your store. If the APIs connecting to the payment gateways fail, you lose both customers and revenue. Therefore, monitoring and controlling your API is crucial to ensure success in every step of the transaction in your application.

Validate the returned data and handle errors

API monitoring helps measure the reliability of transactions. Software that lets you monitor APIs can detect and alert on errors, warnings, and failed API authentications to ensure secure data exchange.

Identify bugs, changed endpoints in third-party API integrations

Almost all SaaS vendors provide their customers with APIs that can be leveraged to manage configuration, data, and outputs. The schema versions of these API endpoints are updated over time as the SaaS platforms evolve. Therefore, the APIs should be tested regularly to ensure your application code doesn’t fail when a new schema version is released.

As mentioned earlier, third-party API integrations eliminate the need for duplicate data entry by fetching externally managed information. However, bugs that cause timeouts, latency in API calls, errors, and downtimes for API endpoints dependent on third-party API integrations can degrade internal API’s overall performance. These problems can be easily identified through API monitoring.

How does API monitoring improve performance and resilience?

API monitoring enables evaluation of API performance from multiple perspectives (e.g., DevOps, QA, development). A DevOps perspective might focus on the scalability of query performance, while a QA perspective might examine the actual data exchanged to validate the structure and expected results. In this way, API monitoring can inform many initiatives across the organization, making it an efficient optimization tool.

What are the best practices for API monitoring?

1. Why go beyond API availability checks?

API availability or uptime is a gold standard in API monitoring. At the same time, monitoring availability alone is not sufficient for API transactions that involve data exchange. In other words, you have to test various verbs, such as Create, Read, Update, and Delete (CRUD), against all application resources exposed via the API to ensure they are operational.

Using synthetic monitoring tools with multi-step API monitors is one way to improve API availability and data reliability. Just remember, synthetic monitoring uses only a predefined set of API calls. Therefore, real-world traffic can differ from the inputs used in synthetic monitoring.

2. Why monitor API dependencies?

There can be other internal and/or external APIs that depend on the input or output of your application’s APIs. Even though you have implemented an API monitoring strategy, other APIs may or may not have one. Therefore, you should also monitor the behavior of the third-party APIs your application depends on.

3. How can CI/CD integration strengthen API monitoring?

The CI/CD and DevOps movement encourages continuous and automated testing. You can define a clear API monitoring strategy for every stage of the CI/CD pipeline, with routine monitoring at regular intervals. This cycle will enhance the API performance of your prototype at every stage of your code release process.

4. Why is strong alerting functionality critical?

Tools that only visualize metrics force engineers to constantly watch dashboards to catch and debug API errors. That’s why strong alerting should be a top priority when you choose an API monitoring tool.

Which metrics should you monitor for APIs?

Availability or uptime

API availability, or uptime, is usually expressed as a percentage, such as 99.9% or 99.99%. You can also express the same concept as total annual downtime, averaged over the year.

CPU and memory usage

High CPU usage and memory usage of the API host server are signs of an overloaded virtual machine, container, or API gateway node. This would slow your API performance.

You can measure CPU usage across a cluster that hosts your application’s API code, as well as the number of processes waiting to run, also known as CPU load or run-queue size. Memory can be measured simply as the percentage of available memory in use.

API consumption

API Consumption is measured in requests per minute, requests per second, or queries per second. You can batch multiple API calls into a single call using a flexible pagination scheme to reduce API consumption.

Note that synthetic monitoring isn’t meant to measure the consumption rate, since it emulates individual transactions rather than monitoring the aggregated volume. The telemetry instrumentation to measure and report the consumption rate is typically engineered into the API’s design at the onset or monitored with an Application Performance Monitoring (APM) tool.

Response time

Response time is a tricky metric to measure with third-party APIs because recording latency may be an aggregation of both slow endpoints and network latency. The best approach to monitoring the latency is to use an API monitoring tool that can separately report the network latency and the API response time.

The size of the payload (the JSON file posted to or retrieved from the API) has a large impact on the latency. This is why synthetic API monitoring should be performed with both small and large payloads.

Error rate

Error rates (such as errors per minute and error codes) give you granular details for tracking down problems in individual APIs. For example, error codes in the 400-500 range indicate issues with APIs or web service providers.

However, there can also be faulty APIs responding with a 200 OK status that was not designed using the correct HTTP status code. Synthetic monitoring tools can compare the result of a test with an expected value to confirm the accuracy of the API response, beyond the status code.

Unique API consumers

Unique API consumers metric provides insights on the overall growth and health of new customer acquisitions based on the monthly active users count. A sudden drop in consumers during peak operating hours is interpreted as a symptom of an underlying application platform problem.

How can teams debug API issues effectively?

Check/compare responses

The easiest and first method for tracking down API problems is to check the HTTP status code. A 400 Bad Request means an API request with invalid syntax that you probably have to review for typos.

401 requests often indicate invalid or missing authentication credentials, which can be resolved with proper authentication, such as an OAuth token. Other common mistakes include forgetting the space in a prefix or adding the required colon after a username, even if there is no password.

Authorization: Basic base64_encode(exampleUser:)

In a scenario where the intent is to check the API’s availability only, it would be acceptable to “assert” (or accept) a 401 code since. This is because, even though “401 unauthorized” was received, the API was still available.

Check/compare headers

Checking the API response code and applying the corresponding debugging method can sometimes fail to resolve API errors. In those cases, check and compare HTTP headers for additional information. Some APIs accept requests that don’t contain Accept for Content-Type information. However, many require this to be specified.

JSON parsing

JSON schemas are used to document API endpoints. JSON parsing tools can be used to debug API endpoints. These tools let you create tests for API endpoints and validate syntax.

How should you choose the right API monitoring tool?

Prioritize tools integrable into your CI/CD pipeline

As discussed above, API monitoring can be integrated into the test automation process in your CI/CD pipeline. Therefore, the tool you select to monitor and control APIs should be able to integrate with your CI server (e.g., Jenkins or GitHub).

Never trade-in API privacy

Some tools use third-party SaaS platforms that require you to open certain ports on your firewall to monitor internal APIs that are not publicly reachable. These, in turn, expose a security risk. That’s why it is so important to choose the right API monitoring solution, taking into consideration the API type you want to monitor and control. Tools that can access your private APIs from inside your firewall are best suited for this use case.

Tools combining both API testing and monitoring win ahead

API testing followed by API monitoring creates a comprehensive end-to-end API performance evaluation process for applications. That’s why it is to your advantage to use a tool that provides both testing and monitoring capabilities. With such a solution, your team has a 360-degree view of API quality and performance on a single screen.

What’s the bottom line on API monitoring and testing?

APIs are not just connectors; they’re critical to business operations and user experience. To keep them resilient, teams must monitor more than uptime. They need to track availability, response time, error rates, throughput, and usage, while testing for reliability across dependencies and architectures.

By adopting the best practices discussed in this guide, including integrating monitoring with CI/CD, validating functional uptime, and combining synthetic and real-user monitoring, organizations can move from reactive firefighting to proactive resilience.

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