As software development has evolved from “source code,” more and more code has moved into and behind Application Programming Interfaces (APIs). This move to API-based code has reduced the capability of engineers to observe an application's behavior holistically, muddying the waters and making it harder to understand how an application’s components interact.
APIs have broken traditional maintenance, software management, and even the software development lifecycle. Significant effort is needed to manage the chaos introduced by this shift to APIs, and the novel ways in which they fail.
API Observability is the future of API development as it addresses many problems related to API consistency, reliability, and the capability to quickly iterate on new API features. When you design for full-stack observability, you get everything you need to find issues and catch breaking changes before they can cause harm.
In this post, we’ll explore the concept of API observability, and why it is critical to reclaiming development efficiency and managing a successful and stable application.
Consistent APIs in the Software Sprawl
Evolving software complexity requires an intricate network of services that interact in meaningful ways. This has exposed many holes in the existing industry toolchains and practices, which more often than not are designed to manage the development and operation of a single application. This means that without a dedicated effort, existing toolchains and practices are not sufficient to guarantee production readiness and reliability of an application.
The increased complexity of background behavior reduces the observable aspects of the system, requiring more complicated toolchains just to report on their own status, let alone the state of the application as a whole. Creating consistent APIs becomes a group ownership task as a result, with the growing network of services making maintaining API standards and patterns significantly more challenging due to the highly collaborative nature of the work involved.
Moving from Source Code to API-Based Code
Code used to exist in single, monolithic code bases. But the growth of applications and their need to scale has led to an increased focus on microservices and APIs that drive development. Where solutions were once centrally located within a single repository, even a small change in this kind of environment can now end up touching multiple services that work together to create an API response.
Increased architectural complexity means that it’s never been harder to get the full picture of your application and stay ahead of failures. As application monoliths are broken down into more focused services, the scope of knowledge needed to grasp the full picture of application behavior becomes unmanageable.
The Diminishing Commitment to Testing
As applications grow, verifying their behavior becomes more challenging, as increasingly complex architectures and interactions lead to increasingly complex tests. The run environments required for modern API-driven applications require orchestrating dozens of services to operate in concert. This ultimately means that the traditional approach of “testing intended behavior before pushing to production” most likely is far too expensive and simply not tenable when building a cohesive API.
The tendency in this situation would be to shift the tests left, introducing them earlier in the software development lifecycle. However, this takes up valuable engineering time and significant resources that are needed to both generate and maintain the automated test suite as the product evolves. Endless dependencies make tests harder to write, resulting in a test suite filled with brittle, flaky, and outdated tests.
As a result, many organizations have moved toward variations of testing application behaviors in production and production-like environments, with or without QA support. Ultimately, this will lead to fragile software, as complex tests require dedicated effort to implement and maintain.
The Visibility Problem
Figuring out that there’s a problem with your system starts with being able to observe the components that drive it. In turn, understanding how its components interact, and what their behavior patterns are, drives resolution time and results in higher-quality software.
This observability is critical in understanding your system, but as its complexity grows, the sheer number of components involved means that a simple metrics dashboard just won’t cut it.
The common practice to get around this focuses on building custom metrics representative of desired system behavior, with associated build and analysis pipelines to drive data accuracy and observability. This delivers great visibility into metrics aligned with company success, but it gives you little information about how the information came to be. With a complex microservice-based system, the dashboards that monitor application behavior and performance can be as complex—if not more so—than the database analytics built around company KPIs.
Achieving full visibility of your system is critical, as the behavior of your application will alert you to imminent failures before they manifest, giving you the crucial reaction time needed to tackle any issue head-on.
Improving Observability Is the Key
API changes can very easily become overwhelming to track and govern. As organizations scale, simple headcount increases mean that the development team will quickly begin producing work at such a rate that no one can manage to keep abreast with the product as a whole.
To manage this, you need a proper observability framework that provides the context needed to get a full understanding of API behavior. This helps engineering organizations better manage and maintain the APIs that are critical to their business.
What Exactly Is API Observability?
API observability is the ability to understand system behavior and investigate the interactions between an application's components. It provides comprehensive and actionable insights on top of monitored application data, enabling faster API iteration, more confident change management, and production readiness.
Benefits of API Observability
API observability improves the development environment as a whole. It touches every aspect of an organization, from improving engineering velocity and enforcing development hygiene all the way to providing a proven and dependable way out of testing. API observability allows you to build and iterate upon APIs more quickly, providing a deeper understanding that allows you to move faster.
API observability ultimately provides you with complete system context and confidence in production, giving you visibility into how the system is actually behaving (as opposed to how we try to predict it will behave when we write automated tests against it). It focuses on modeling API behavior in a way that allows for visibility into production data flows. Having a clear picture of how data moves through your system lets you be proactive in change management, building a comprehensive picture of system activity and how it evolves over time.
API observability enables a stronger focus on data-driven testing, letting you focus resources where they are needed instead of wasting effort on a blanket “build-test-deploy” approach. Relying on integration testing instead of shifting testing to match the evolution of the product is an outdated mode of thinking. Tests built around the actual data flows of your application are a lot faster to implement, reducing the resource cost of verifying your API’s behavior.
How API Observability Differs from API Monitoring
API monitoring and observability can monitor application program interfaces (APIs) to provide data on their availability, performance, and usage; you can also use both to track an API’s business value. Monitoring focuses on navigating logs and traces, making the real-time status of the system observable. This is similar to tracking a string of clues in a mystery, leading to a conclusion that needs to be hypothesized, investigated, and implemented by developers. Tools in support of this approach are not built to grasp the larger picture of API behavior, but instead focus on operational insights and real-time performance.
The data collected via monitoring enables you to expand beyond this model and build a truly predictive engine, but there needs to be a way to aggregate and correlate the data and make it actionable. By building abstractions on top of logs and metrics, you can model application behavior more accurately.
API observability focuses on defining and building abstractions on top of logs, metrics, and traces, reducing the number of dimensions involved when analyzing application behavior and performance in a search of potential issues. You won’t get every trace you want in this system, but you won’t actually need them in order to understand and manage how your system is behaving. As such, it’s better for moving more quickly and keeping an eye on how system behavior evolves. With an abstracted model of the system, you can easily correlate detect changes to logical behavior automatically, without needing to troubleshoot the issue or a specific data flow.
This can be done in all environments, not just production, and provides added observability that helps drive issue detection and resolution.
Using Tools Like Seekret to Bridge the Gap
Traditional API monitoring isn't enough for today's API-driven software. What if we could achieve API observability without needing to navigate logs and traces, moving away from testing in production? Seekret offers a powerful mission control for developers that makes APIs easier to understand, manage, and maintain.
With Seekret, engineering leaders and development teams can observe APIs as a model and catch breaking changes early. Seekret provides the first mission control for your API ecosystem, letting you build a model-based view of your application that helps manage your API lifecycle and identify issues before they become truly damaging.
Want to discuss more about why you should switch to API Observability to gain deep insights into your APIs? Schedule a 1:1 meeting with me and we'll dive right into it!