In a world where APIs serve as the glue that melds together disparate applications or parts of applications, API performance problems can quickly make an application unusable and undercut user experience.
Although APIs have existed for decades, the widespread adoption of microservices architectures, containers, serverless computing, IoT smart devices and other next-generation technologies have made APIs much more important. Modern applications rely extensively on APIs to facilitate internal and external communications.
The large-scale embrace of APIs has not only changed the way applications are written and deployed. It has also created new imperatives for maintaining software quality.
This is why DevOps teams are now adding another category of monitoring – API monitoring – to their toolsets. While conventional monitoring tools will not disappear, monitoring tool sets that lack the ability to discover API performance and reliability issues leave a critical blind spot in the vision of DevOps teams.
What is API Monitoring?
API monitoring delivers several critical types of visibility into application performance and quality by supporting several types of use cases:
■ Uptime monitoring: API monitoring tools detect APIs that stop responding, or respond intermittently.
■ Performance monitoring: APIs that are available but are responding slowly to requests can cause the applications that they support to perform slowly too.
■ Data validation: When an API sends or receives the wrong data, significant application problems can result. API monitoring tools that support data validation help to prevent this problem.
■ SLA satisfaction: Because APIs play vital roles in connecting applications to third-party resources, SLAs may require certain levels of API performance to be maintained. API monitoring tools can help to meet SLA requirements.
The Right Toolset for Building an API Monitoring Practice
Once an organization has made the decision to adopt API monitoring tools, it must decide which specific types of API monitoring (synthetic and real-user) to deploy in different scenarios.
This is an important issue because synthetic monitoring and real-user monitoring cater to distinct types of use cases.
Synthetic monitoring is your first line of defense against API issues. It allows you to achieve an outside-in view by continuously monitoring uptime, performance and data integrity of your API from an end-user perspective whether or not your customers are accessing the API at that time. It also enables you to achieve a global view of API performance by leveraging servers around the world to act as end-users so you can ensure your customers in other geographies aren't experiencing app issues caused by APIs.
Real-user monitoring involves testing software in real-world environments, with "live" users.
While real-user monitoring provides more detailed and accurate insight into software behavior and user interactions, performing such monitoring on every application is not practical. To perform real-user testing and monitoring of APIs, DevOps teams must set up real-world environments and trigger API actions in response to actual user behavior.
While the investment of time and resources required to perform real-user monitoring is not practical in all situations, it is often worth the effort for testing and monitoring mission-critical APIs. Real-user monitoring can also be paired with APM tools to help quickly identify the root cause of an API performance issue by homing in on the particular environment variables that have triggered the failure.
A Comprehensive API Monitoring Strategy
Because synthetic monitoring and real-user monitoring cater to different use cases, it’s best to factor both into your monitoring strategy. An API monitoring tool set that supports only one or the other will lack either the monitoring breadth provided by synthetic monitoring or the depth delivered by real-user monitoring.
To learn more about building a API Monitoring practice, read the complimentary guide: Building an API Monitoring Practice for Modern Apps, Containers and Microservices