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—and 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.
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What are the main types of APIs?
An API is a set of functions or procedures that governs the access points for a given system, service, or application. Currently, the two main competing approaches offering extensibility to APIs for creating web services are Simple Object Access Protocol (SOAP) and Representational State Transfer (REST). GraphQL has become a popular alternative to REST in the past few 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 consume extra overhead and more bandwidth, and require more work on both the client and server ends. That said, like envelopes, SOAP encloses more stringent security compared to 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 micro-service 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 REST API for HTTP APIs that have similar benefits but adhere to REST constraints more liberally.
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 for how compliant they are 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 very easy in comparison to true REST APIs, which require 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 get more expensive to parse and execute plans for as they get bigger--and they also lack certain concepts native to HTTP, such as content and language negotiation.
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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 your APIs operate in terms of performance (e.g., time to respond to a request made from various locations or to queries of increasing complexity).
You monitor APIs to detect a failed or slow application transaction before your end-users report the problem.
Ensure Multi-Step Transactions Are Successful
Nowadays, web applications rely on APIs that form abstraction layers between the micro-services that make up your application, as well as third-party services to embed additional functionality that will enrich 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 on a regular basis to ensure that 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 information that is externally managed. 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. Luckily, these problems can easily be identified with API monitoring.
How does API monitoring improve performance and resilience?
API monitoring allows API performance evaluation from multiple perspectives (e.g., DevOps, QA, development). A DevOps perspective might focus on the scalability of the performance load of a query or many queries, while a QA perspective might examine the literal data exchanged to validate the structure and expected results. In this way, API monitoring can be used to inform many initiatives across the organization, making for an efficient optimization tool.
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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 enough for API transactions involving data exchange. In other words, you have to test various verbs such as Create, Read, Update, and Delete (CRUD) services against all of the application resources that are exposed via the API to ensure that they are operational.
Using synthetic monitoring tools with multi-step API monitors is one way you can improve API availability with data reliability. Just remember, synthetic monitoring uses only a predefined set of API calls. Therefore, real-world traffic can be different from the inputs in synthetic monitoring.
2.Why monitor API dependencies?
There can be other internal and/ or external APIs dependent upon the input or output of your own application’s APIs. Even though it is true that 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 on which your application depends.
3. How can CI/CD integration strengthen API monitoring?
CI/CD and DevOps movement encourage continuous testing and AUTOMATED testing. You can define a clear API monitoring strategy for every stage of the CI/CD pipeline and routine monitoring at regular time 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 with only metric visualization need constant human-intervened monitoring to know if anything went wrong to handle and debug API errors. Thus, a tool with a strong alerting capability should be a priority when selecting an API monitoring tool.
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Which metrics should you monitor for APIs?
Availability or uptime
API availability or uptime is a percentage measurement that is often represented as 99.9% or 99.99%. Sometimes, the same is calculated as downtime-per-year as an overall average.
CPU and memory usage
High CPU usage and memory usage of the API host server is a sign 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 which is also known as CPU load or run-queue-size. Memory can be simply measured as a percentage of available memory that is in use.
API consumption
API Consumption measures as requests-per-minute, requests-per-second, or queries-per-second. You can batch multiple API calls into a single API call with a flexible pagination scheme to lower the API consumption.
Note that synthetic monitoring isn’t meant to measure the consumption rate, since it emulates individual transactions instead of monitoring the aggregated volume of transactions. 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 the recording latency may be an aggregation of both problematic slow endpoints and the network itself. 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 (like errors-per-minute and error codes) give you granular details in tracking down problems in individual APIs. For example, error codes in the 400 to 500 range imply problematic APIs or web service providers.
However, there can also be faulty APIs responding with an 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 monthly active users count. A sudden drop of 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 the first method for tracking down problems with APIs 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 have invalid or missing authentication credentials that can often be resolved with a 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, it means that the API was 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.
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How should you choose the right API monitoring tool?
Prioritize tools integrable into your CI/CD pipeline
As discussed above, API monitoring is integrable into the test automation process on your CI/CD pipeline. Therefore, the tool you select to use to monitor and control APIs should be able to integrate with your CI server (e.g., Jenkins or Github integration).
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 able to exercise your private APIs from inside your firewall are best suitable 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 can provide both testing and monitoring functionality. With such a solution, your team has a 360-degree view of API quality and performance on a single screen.
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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 best practices—such as integrating monitoring with CI/CD, validating functional uptime, and combining synthetic and real-user monitoring—organizations can move from reactive firefighting to proactive resilience.
Catchpoint IPM delivers visibility across the entire Internet Stack—DNS, CDN, APIs, and user experience—helping teams troubleshoot faster and maintain the reliability today’s digital systems demand.
FAQs
What is API monitoring and why is it important?
API monitoring is the process of continuously checking APIs for availability, performance, and accuracy. It helps detect slowdowns or failures before they impact users. Learn more in our guide to critical requirements for modern API monitoring.
What metrics should be tracked when monitoring APIs?
Key metrics include availability, response time, error rate, throughput, CPU and memory usage, and unique consumers. Tracking these ensures APIs remain reliable and performant. Explore real-world examples in our web API monitoring case study.
How do synthetic monitoring and real user monitoring (RUM) complement each other?
Synthetic monitoring simulates user transactions to proactively detect issues, while RUM captures live user experiences. Together, they provide a complete picture of API performance.
How can API monitoring be integrated into CI/CD pipelines?
By shifting monitoring left, teams can validate endpoints during development and automate the creation of monitors as new code is deployed. This prevents blind spots and ensures APIs are tested before reaching production. See more in Mastering API monitoring for digital resilience.
What’s the difference between API monitoring and API testing?
API testing validates functionality during development. API monitoring runs continuously in production to track performance and reliability over time. Together, they provide a full lifecycle approach to API resilience.
