Application Programming Interfaces (APIs) are now used by the majority of software development teams to simplify communication between otherwise unconnected components from different platforms. This has fuelled a much larger API economy, which has had a massive influence on the performance of modern-day apps, influencing the end-user experience and overall application evaluation.
It is critical to include the API monitoring step in the API lifecycle to ensure that your APIs are working as planned. Dedicated API monitoring may assist you in determining how your internal or third-party APIs may be malfunctioning, allowing your team to discover and resolve issues much more rapidly.
In reality, with good API monitoring in place, you should be able to detect errors before they do harm and correct them before they affect any users at all, so they are unaware. Thus, continuous API monitoring can aid in maintaining high uptime and low outage rates across all services and applications.
In this post, we'll go through the industry best practices for API monitoring, such as which metrics to prioritize and how to troubleshoot when an issue arises.
First, let's learn more about API monitoring.
What is API Monitoring
API monitoring is the practice of continually verifying the availability of API endpoints as well as the correctness of the transactions that occur there. Furthermore, by monitoring your APIs, you may gain insight into how your APIs are doing in terms of response time to requests, queries of varying complexity, and so on.
Why we should monitor APIs
In the most basic terms, API monitoring helps to detect the failed or slow API transactions before the end-user reports them. However, here are some of the other benefits of API monitoring:
Ensure multi-step API transactions are successful
APIs are used in modern web applications to create an abstraction layer between the micro-services that comprise the program. This architecture makes reliance on complicated multi-step API interactions and third-party integrations necessary.
For example, if a payment gateway integration on your e-commerce application fails, you will lose both consumers and income; hence, monitoring these APIs for any issues will save you from the mess and assure success at each step of the transaction within your application.
Validate response data and handle errors
API monitoring may be used to assess the dependability of API transactions. It can assist you in detecting and sending notifications when faults, warnings, or failed authentications occur to guarantee a safe data flow.
Identify Changed endpoints, and bugs from the third-party integrations
Almost all SaaS providers provide APIs available to developers, which may be used to handle setups, data, and outputs. As the organization expands, these API endpoints' schema versions are updated to reflect the changes. As a result, when these endpoints are used in an application, they must be verified on a frequent basis to guarantee that the code does not fail when a new schema is released.
API timeouts, latency in API calls, failures, and downtimes for API endpoints that rely on third-party integrations can all significantly decrease application performance. API monitoring, fortunately, may assist us in identifying and resolving these issues in real-time, functioning as an efficient and effective optimization tool across services in an organization or project.
What Key API Metrics Should You Monitor
Availability or Uptime
API uptime or availability is measured in percentages or, in certain cases, as downtime-per-year as an overall average.
CPU and memory usage
The API host server's high CPU or memory use may indicate an overload on the virtual machine, container, or API gateway node, which delays API performance.
CPU utilization throughout a cluster that hosts the CPU load or the API code, as well as the number of processes waiting to execute, may be monitored. The memory may be quantified simply as a proportion of accessible memory in use.
API Consumption
API consumption is measured in terms of requests per minute, requests per second, or queries per second.
API Response Time
Response Time, as the name implies, is a measurement of the time it takes for an API endpoint to provide a response. It is a difficult indicator to monitor when using third-party APIs since latency might be the result of both extremely sluggish endpoints and a network problem.
Error rate
The error rate is a measure that represents the number of errors per minute or second to provide precise insights in tracking down issues in particular API endpoints. Tracking HTTP status codes between 400 and 500, for example, might indicate endpoint issues.
Unique API Consumers
Unique API consumers is an API measure that assists the team in gaining insight into the overall growth and retention of new client acquisitions based on the number of monthly active users.
A rapid decline in these figures during peak operation hours may indicate an issue with the application platform.
Best practices for API Monitoring
Here are some key principles to keep in mind when going to monitor your APIs:
- Regularly monitor your application services for their availability with active probing. This helps you generate the uptime and response time data.
- Always set up conditions or checks on the returned data to validate that the response content is as you expected and trigger warnings or alerts accordingly.
- Always hit and check your production endpoints with the same security level as your end-users to get reliable results.
- When it comes to latency, always look at the statistical spread and not just the average to form an opinion.
- Always set up alerts for failures and issues, for example - Slack alerts, emails, etc.
- Always double-check 4xx errors, it is often ignored as a problem at the client side whereas, with APIs, it could be a problem with the security gone wrong or validation checks misconfigured.
Conclusion
API monitoring may appear to be a daunting task and is frequently viewed as a nice-to-have but not critical step in API development; however, in this article, we learned how proper and consistent API monitoring can lead to significantly improved API performance, error handling, and user experience and satisfaction.