API Analytics – An Overview
Application Programming Interfaces (usually shortened to APIs) have become the de-facto standard for supercharging the capabilities of modern applications with cutting-edge technology. And, API analytics and monitoring allow you to assess the performance of your API products and escalate their consumption.
This article talks about how to use API monitoring and analytics to enhance the visibility into the performance of your APIs, and increase their adoption.
What is API analytics and monitoring?
Even though both analytics and monitoring entail gauging the performance of APIs based on the data derived from their traffic, the two topics are largely different—though they may sync up in some use cases. For example, an API management platform may concentrate on providing analytics dashboards and disregard monitoring tools, and vice versa.
Generally, monitoring involves maintaining a real-time surveillance over API performance data and keeping abreast of its proper functioning. It addresses the present concerns that may impair the health of the API—just like a heart rate monitor would let the user know whether they are currently having a heart attack or everything is working fine.
On the other hand, analytics entails the analysis subjected to the API data to derive useful insights, usually retrospectively but, at times, in near real-time. Analytics is less focused on the present conditions—rather than a heart rate monitor notifying a user of a heart attack, a doctor analyses the patient’s dietary habits, activity data, and other factors before making a conclusion.
While one concept is concerned with in-the-moment performance metrics, the other deals with deriving retrospective insights that may increase usability and consumption.
Nonetheless, although analytics and monitoring are different concepts, it is essential to regard them as a spectrum. For example, API monitoring tools can be used to collect data that augment the insights extracted from analytics.
Why use API analytics and monitoring?
Analytics and monitoring are essential in assisting enterprises to maintain the health of their APIs. Without these performance monitors, it can be difficult to optimize the value and deliverability of Application Programming Interfaces.
Here are some benefits of performing API analysis and monitoring:
- Assess and improve performance
- Enhance the developer experience
- Proactively manage risks
- Make informed business decisions
Let’s now talk about each of the benefits.
- Assessing and improving performance
Monitoring and analyzing API data is a great way to gain end-to-end visibility of its performance and usage metrics. With actionable data, an API service degradation can be detected and solved quickly; otherwise, it could lead to revenue losses, reputational damages, and customer dissatisfaction.
Performing API analysis can assist in answering some common questions, such as:
- Where does most of my API traffic come from?
- When does API response time peak? Plummet?
- Who are the top developers consuming my API?
- Which are the most popular API endpoints?
- What is the trend of my API traffic over time?
Getting answers to such questions can assist in troubleshooting issues and enhancing the quality of your API.
- Enhancing the developer experience
Monitoring and analytics are where aspirations and assumptions meet user behavior—and where fresh, renewed iterations are produced. Performing web API health monitoring helps in understanding and getting rid of sources of user friction. If developers find your API difficult to use, they’ll move to a competitor’s product quickly.
Leveraging API analytics assists in creating better relationships with developers and enhancing its consumption. With active developer engagement, you’ll take the guesswork out of monitoring APIs and supercharge the functionalities of your product through promptly correcting discovered anomalies.
Getting the most out of your API takes more than just creating and launching it. If you analyze its data and constantly update the API documentation, you can greatly boost the developer experience.
- Proactively managing risks
Monitoring API calls can help enterprises to stay on the right path and avoid disasters. With instant and comprehensive visibility into the functioning of APIs, you can maintain their peak performance and protect them from malicious bots or threats.
Using API monitoring tools can assist in proactive decision-making, which can avert the risks often associated with poor performance. Regrettably, most enterprises have several APIs that they do not care to monitor. As a result, these unmonitored APIs tend to be prone to security leaks, errors, and other performance issues.
If developers realize that hackers can break into your API product, they’ll shy from implementing it. However, with sufficient data about the behavior of your API, you can identify sudden unmerited surge in traffic or other anomalies, and seal the loopholes before hackers discover them.
- Making informed business decisions
Slicing and dicing your API data can assist in making well-grounded business decisions. If you track and analyze the consumption and usage of your published APIs, making decisions based on valuable insights will be much easier. With data-driven business choices, you can adapt quickly to market and customer changes and ensure the longevity of your APIs.
For example, analytics can help you to know the APIs that are not performing well, the developers bringing the most value in traffic, and revenues accrued from monetization efforts. This way, you can have sound reasons to make changes that align with your business goals.
What type of data is collected and analyzed?
A typical API analytics software can capture and analyze a wide range of performance metrics.
Here is a description of some of them:
- Response time—the total amount of time (usually in milliseconds) it takes for an API to receive a request from a client and send the response back to the client.
- Request latency—the total amount of time (usually in milliseconds) it takes for an API to process incoming requests. Latency analysis usually assesses the delay period experienced from the time a request reaches an API to the time the request is dispatched to the target service.
- Request size—the size of the request payload (usually in bytes) that the API receives.
- Response size—the size of the response payload (usually in bytes) that the API returns.
- Target errors—the error responses got from the target service. This metric is useful in assessing the target performance.
- Popularity score—the extent of popularity of an API service among developers.
- Call success rate—the percentage of successful API requests.
API monitoring and analytics use cases
The possible use cases for REST API monitoring and analysis are numerous. Continually gathering, assessing, and visualizing data can ensure everyone at the workplace is productive.
Here are the key user groups:
- The API team—the API team, which may consist of API developers, product managers, and API evangelists will need deeper visibility into the API’s adoption rate, API’s popularity, and other metrics. This way, they can diagnose problems and implement improvements quickly.
- App developers—by sharing metrics and insights with external developers who leverage APIs, enterprises can assist them in building quality applications. Such data can help developers to assess the performance of their apps and make useful adjustments.
- Operations team—operations administrators, who are usually responsible for ensuring API peak performance and availability, will need to assess API traffic patterns and proactively make backend improvements or other changes to avert security threats.
- Business stakeholders—they will need to know whether API investments are worthwhile and whether their future pursuits will yield a good return on investment (ROI).
Functions of an API analytics platform
Here are the main functions of a typical API analytics platform:
- Data collection—this component deals with collecting and aggregating data. In this process, data, events, and other metrics surrounding your API product are intercepted and stored, allowing you to assess and extract valuable insights from them. You can also import external datasets to enhance the quality of your data analysis.
- Analyzing and processing—this component allows you to carry out detailed drilling on your data. This way, you can identify useful trends buried within your dataset and take the performance of your API program to the next level.
- Interactive visualization—this component provides valuable analytics and reports to assist you in visualizing how your API is performing. Furthermore, you can drill down into specific insights and actions and gather the information you need.
Furthermore, most API management platforms come with a set of predefined dashboards that you can use to gain a deeper visibility into the analytics data.
Here is a description of some of them:
- Proxy management dashboard—the API proxy performance dashboard assists you to scrutinize the API proxy processing times and traffic patterns. With this dashboard, you can measure the API traffic, the total number of successful requests, the total number of unsuccessful requests, average response time, and more.
- Cache performance dashboard—this dashboard assists you to visualize the value of your API cache as pertaining to reduced latency and lowered load backend servers. With this dashboard, you can measure the cache performance of your APIs and discover any anomalies in their functionalities.
- Error code analysis dashboard—this dashboard visualizes the error rates of your APIs. It uses the response codes and the target response codes to compute any errors experienced.
- Target performance dashboard—this dashboard lets you view the performance metrics of the API proxy backend targets. It also visualizes their traffic patterns, number of errors and successes, and more.
- Latency analysis dashboard—this dashboard can showcase the latency problems with your APIs. With this dashboard, you can measure the total response time, response processing latency, and more.
Setting KPIs for APIs
Setting good key performance indicators (KPIs) are invaluable for the success of any API analytics effort. Although they are mostly used in a company setup to assess the success of achieving business objectives, KPIs can also be applied to APIs to assist API providers to evaluate whether their efforts are worthwhile.
API-centric KPIs can help enterprises in having a tangible frame of reference for evaluating the performance of APIs. Consequently, they can improve API quality, value, and adoption.
Importantly, when choosing KPIs for APIs, you should consider how they’ll assist in adding value to your business. If such KPIs are selected in isolation, without combining them with business-level KPIs, then you may only focus on simple IT-level metrics, such as the number of APIs produced or the number of API calls made. While such metrics are important, they may make you overlook the bigger opportunities.
Therefore, when setting KPIs for your API strategy, you should ensure they are helpful to your business strategy. For example, if your API is created to drive revenues to your enterprise, then you should measure API revenue as your KPI.
You may be wondering: are the performance-related “KPIs”, such as request latency and target errors, valid KPIs? Unfortunately, this appears to be an issue of semantics in which varied opinions reign.
Whereas some people consider performance metrics to be the very definition of KPIs, most people hold the opinion that KPIs should only be used for measuring business metrics. In other words, although performance statistics are vital—and should also be measured—they are not necessarily key performance indicators.
While each API is distinct with unique use cases and business goals, here are some of the common KPI targets that you can measure:
- Direct revenues—this KPI target can be used to track the revenues from the sale of products and services that are enabled by the APIs. If you realize that your efforts are not meeting the set API monetization objectives, you can institute measures to improve your collected revenues.
- Time To First Hello World (TTFHW)—apart from measuring the health of your API, TTFHW is an important KPI for measuring the overall developer experience. Just as the name suggests, TTFHW measures the time it takes for developers to interact with your API product and make their first successful request. The ease and speed that developers require to get up and running with your API is critical to determining its consumption.
- Number of partners—this KPI is useful in supercharging partner outreach, enhancing consumption, and showcasing achievements to existing business units. For example, if your API is intended to increase awareness about your company, the number of partners can be a useful metric to track.
- Growth of traffic—this target can be useful in measuring the growth of APIs and improving their adoption. If this KPI is coupled with other related metrics, it can assist in driving the value of APIs. Your API product should not just be performing properly, but it should be growing month over month. Unlike a metric like the number of requests per minute, API usage growth should be analyzed in longer time intervals, such as month-over-month, to discover real trends.
Example of an API analytics tool
There is a wide range of API tooling you can use to manage your APIs and analyze their adoption metrics. A popular example is the Amazon API Gateway, which is an AWS managed service that provides comprehensive resources for building, deploying, monitoring, and securing APIs.
Here is a diagram of the Amazon API Gateway architecture:
Apart from providing several other features for managing APIs, the Amazon API Gateway also offers tools for monitoring and checking the performance of APIs.
Here is a description of some of its analytics tools:
- Amazon CloudWatch alarms—this is an automatic tool that allows you to monitor a single metric over a specified time period and send a notification whenever the defined threshold is reached. For example, you can use it to measure the latency metrics and gauge the responsiveness of your API requests.
- AWS X-ray—this is an automatic service that collects data about your API requests and produces an intuitive graph that shows latency spikes and other issues that may affect the health of your API.
- Amazon API Gateway dashboard—you can also manually configure the features of the API Gateway dashboard to show some statistics about the performance of your API. For example, some of the statistics you can show include the number of API calls, cache hit, cache miss, and integration latency.
Setting up API analytics and monitoring can improve the consumption of your API service. With analysis and monitoring tools, you can create easy-to-use and secure APIs, provide outstanding developer experience, and optimize the business value of your APIs.
API analytics provide end-to-end visibility into the management of API programs. This way, enterprises can collect the essential statistics to make informed decisions and take the adoption of their APIs to the next level.
About Rakuten RapidAPI Enterprise Hub
Rakuten RapidAPI provides a world-class enterprise API marketplace that comes with comprehensive analytics and monitoring capabilities to help you in making the most of your APIs. It offers a rich set of features that let enterprises gain control over the management of APIs.
With the Rakuten RapidAPI Enterprise Hub, you can get detailed analytics about the performance of your APIs, unlock the business value of data, and deliver robust applications.