As APIs play a crucial role in connecting modern cloud applications, monitoring their availability and performance is a must if you want to provide a top-notch experience. A good API monitoring tool will help you build reliable APIs by identifying and resolving the issues before they reach your users. If you’re interested in such a solution, look no further. In this article, we reviewed some of the best API monitoring tools and services available today, both open source and commercial.
Cribl’s interface is Super Neato: Reactive, beautiful, and easy to use. But sometimes you need to access settings and configurations programmatically. The good news is that interactive API docs are baked into your Cribl instance. The better news is that everything that happens in the GUI is making API calls. With your browser’s developer mode, you can easily take a peak behind the curtain to see exactly how the API was called and what the payload looked like.
A spicy article hit my inbox the other day. It came with a bold claim — “API testing is better than UI testing”. Absolutes like “A is better than B” rarely hold in the software world. “It depends” is the answer to most tech questions for a reason. Let’s compare API and UI testing and discuss why one isn’t better than the other. The frenemies are “just different”, and always will be. And that’s a good thing.
A couple of weeks ago, I wrote about The Art of True Chargebacks and how VMware Tanzu CloudHealth makes simple work of the cost reallocation of cloud expenses. In addition to being a refresher on cost reallocation with Tanzu CloudHealth, it was also shared as a kickoff of our newly released cutting-edge Cost Reallocation API. This officially available API revolutionizes the seamless automation of chargeback reallocation across diverse geographies, brands, business units (BUs), and product lines.
Whether you're a business that relies on Amazon reviews and seller feedback or planning a much-needed holiday through your favorite travel comparison site, everyday activities like these wouldn't be impossible without APIs. An integral part of app development, API technology is interwoven into a rich tapestry of popular applications that companies and consumers use daily. Without them, there would be no smartphones, social media, or instant messaging.
Continuous integration (CI) is the process of integrating changes from multiple contributors to create a single software project. A key component for a smooth CI pipeline is testing. Tests prove that the code does exactly what it says on the tin and that it’s safe to merge the code into the central repository. Tests also anticipate edge cases and ensure that the code handles such cases in a deterministic manner.
Today’s modern applications are made up of thousands of loosely connected private and publicly exposed APIs, each serving a specific function. This dynamic API landscape, in combination with the decentralized nature of microservice development, can be overwhelmingly challenging to manage—let alone govern or secure adequately. API sprawl is often created as a result, leading to fragmented or nonexistent internal API documentation, knowledge bases, and toolsets.
As your applications grow, your teams may be faced with managing a complex, expanding mesh of potentially thousands of loosely connected APIs—each one a new point of failure that can be difficult to track and patch. API sprawl comes naturally in rapidly expanding, distributed applications, and the difficulty of maintaining centralized knowledge and toolsets for your APIs creates friction when teams need to leverage APIs they don’t own.
When it comes to building and delivering modern web applications, the importance of continuous integration cannot be overemphasized. With the rapid pace of software development, ensuring that every change in your codebase is thoroughly tested and seamlessly integrated into your project is essential for maintaining a robust and dependable application.
In today’s world of relentless data growth, security-relevant logs represent a small snapshot of an organization’s overall environment. Teams are beset with a variety of data types, including performance metrics and traces, asset configuration and state, audit logs, and much more. On top of that, teams are expected to scan all of this to compare against industry best practices and join this data with logs and metrics for added context.
