Published: 29 November 2023
Contributors: Chrystal R. China, Michael Goodwin
API monitoring is the process of observing the performance, availability, and functionality of enterprise application programming interfaces (APIs).
More specifically, API monitoring involves assessing in-production API responses to ensure that they meet an organization’s performance benchmarks, and alerting the appropriate parties when things go awry. With companies moving increasingly toward digitized IT infrastructures, frictionless connectivity between parties and systems is paramount. This is where APIs enter the picture.
APIs serve as the building blocks of most mobile and web applications, and the data orchestration hub for the various processes, protocols, and apps that comprise most IT ecosystems. They facilitate communication between apps—and between apps and clients—enabling seamless integration of various services.
More than 75% of businesses report having 26 APIs (on average) per app deployed.1 And more than one-third report that all their apps use APIs, a figure that is expected to grow to more than 50% in the coming years.1
As such, API performance is a real concern for most companies. If not managed properly, compromised or outdated APIs can significantly impact the user experience and overall functionality of applications, as well as the business bottom line. Vigilant API monitoring practices can help businesses promptly address API performance and functionality issues before they become disruptive (or even catastrophic).
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Today’s APIs can facilitate complex system, app, and microservice integration processes, but even the most advanced APIs require teams to implement rigorous monitoring practices. Fortunately, there are numerous API monitoring strategies that can help secure the long-term efficiency and effectiveness of enterprise APIs.
Uptime monitoring pings an API endpoint (that is, the locus of API data exchanges) at regular intervals to make sure it's accessible and responsive (that is, “up”). If the API doesn't respond or takes too long to respond, the system sends an alert.
API metrics for uptime monitoring include availability percentage (the proportion of time an API is accessible) and downtime duration (the length of time an API is inaccessible). It's not uncommon for service level agreements (SLAs) to specify required uptime percentages, often mandating about 99.9 percent ("three nines") uptime or higher.
Performance monitoring quantifies how quickly and reliably an API responds to requests, and helps identify inefficiencies, network issues and server overloads. Performance is typically measured by metrics like response time (how long an API takes to process and respond to requests or calls), latency (the time it takes to transmit a request from the sender to the recipient) and throughput (the number of requests processed per unit of time). Performance monitoring can also track error rates, which indicate the percentage of requests that lead to errors.
Synthetic monitoring is a process that mimics the path that a user might take when using an app. It uses scripts to simulate user scenarios, device types and geographical location, among other elements, to tell teams how well an app is performing.
Like synthetic monitoring, RUM allows teams to see detailed app performance and functionality data. However, instead of monitoring the experiences of simulated users, it observes the real experiences of real users, providing full-stack observability for the user experience and facilitating more fine-grained decision making.
Validation monitoring assesses whether an API behaves as expected by sending test scripts to verify correct API responses, data formats and status codes, and that system calls return the appropriate data. Validation monitoring is useful for identifying issues with multi-step processes or the underlying logic or data processing of an API.
Approximately 35% of businesses have had at least one API security incident in the last year, and more than half report facing multiple incidents.1 Because APIs expose data to the outside world, they are among the likeliest targets for cyberattacks.
Security monitoring focuses on securing APIs against malicious attacks from bad actors by implementing practices like tracking unsuccessful login attempts, scanning for anomalies in API call patterns and checking for data breaches. Security monitoring often involves the use of encryption, validation, and authentication protocols (e.g., OAuth 2.0, API keys, JSON schema validation, and so on) to make sure that only authorized users can access API data. These systems also ensure secure data transmission between front-end and back-end systems, protecting against cyberthreats like hacks, data theft and DDoS attacks.
Apps like Slack and other apps and web services are typically dependent on both managed and third-party APIs, which can create data transmission issues. Integration monitoring addresses such issues by testing the interactions between an API and the other apps and systems that it communicates with, ensuring that all parts of a system work together as expected and identifying issues at the interfaces between systems. This type of monitoring is especially useful for working within a microservices architecture, where multiple independent services interact through APIs.
APIs, especially those operating in the medical and financial industries, often transmit sensitive user and company data, which increases the need for compliance monitoring processes.
Compliance monitoring ensures that an API adheres to relevant privacy standards (like HIPAA), industry-specific standards (like PCI DSS for payment processing), and even internal company standards. Teams can track data handling practices, encryption standards and access control mechanisms, among other processes to maintain legal compliance and client trust.
APIs evolve over time, adding new features, retiring old ones and changing how certain functions work. When these changes occur, it's important to monitor the transition so that applications relying on the API aren’t negatively impacted by updates. Versioning monitoring allows teams to track API changes over time, typically by reviewing each new version release.
Versioning monitoring might involve comparing functionality between versions, tracking adoption rates of a new API version, monitoring error rates related to retired features, and tracking API usage across versions of an app. This type of monitoring is helpful for identifying issues that arise during API structure or functionality changes and can inform future changes to the API.
Regardless of the approach, teams should prioritize real-time monitoring to get instant feedback about application performance and resolve issues before they create service outages for users and partners. As an added benefit, real-time monitoring is often visualized through dashboards and status pages that can provide immediate insights and automate system alerts, both crucial processes for managing high-availability or critical workflows.
APIs are the glue that holds modern application architectures and automation workflows together, so keeping them in top shape can make an IT infrastructure faster and more agile. To implement an effective and comprehensive API monitoring process, DevOps and security teams can:
Before setting up any monitoring protocols, teams should establish clear goals. That means defining KPIs for aspects like availability, response time, throughput, and error rates. Naturally, KPIs should align with broader organizational goals and consumer needs.
Given the vastness of some API networks, relying on API monitoring tools is a no-brainer. Advanced API data observability platforms (like Postman, Datadog and IBM Instana Observability) can automate and streamline the monitoring process, by using features like HTTP keyword checks and DNS server monitoring. When evaluating monitoring services, consider their features, ease of use, tech stack compatibility and cost to ensure a good fit.
This process varies depending on the monitoring tools, but generally, it involves three key tasks: setting up endpoints, defining API tests and scheduling monitoring.
Setting up endpoints requires teams to provide the URL of the API endpoint, the HTTP response code, and any required headers or parameters so that the monitoring tool will know where and how to run test scripts. As the phrase suggests, defining tests is the process of configuring the tests and monitoring tools run to validate API performance. Setting a monitoring schedule simply requires the team to decide how frequently the tool runs the chosen tests.
Alerts are a critical part of any monitoring system, providing instant notifications of system issues and enabling teams to address issues before they impact users. Most monitoring tools allow users to configure alerts based on various conditions, like when the API response time exceeds a certain threshold or when some errors occur within a given time frame.
APIs evolve, so it’s important to regularly review API performance data and insights to make sure that monitoring protocols are still relevant. Look for trends and patterns in historical data that might indicate underlying issues. For example, if an API's response time is consistently high during certain hours, it might indicate a need for more resources during those times.
IBM Instana democratizes observability by providing a solution that anyone and everyone can use to get the data they want with the context they need. Purpose-built for cloud native yet technology-agnostic, the platform automatically and continuously provides high fidelity data—one-second granularity and end-to-end traces—with the context of logical and physical dependencies across mobile, web, applications, and infrastructure.
API monitoring with IBM Instana Observability enables you to ensure the availability, reliability, and performance of your APIs for a seamless digital experience.
IBM named a Leader in the 2023 Gartner Report: Critical Capabilities for API Management.
REST APIs provide a flexible, lightweight way to integrate applications. They have emerged as the most common method for connecting components in microservices architectures.
Application modernization refers primarily to transforming monolithic legacy applications into cloud applications built on microservices architecture.