Systems | Development | Analytics | API | Testing

We live in an API-driven economy, where Application Programming Interfaces (APIs) are increasingly being used to open new revenue channels, accelerate time to market and democratize data. Enterprises are constantly striving to build faster, more reliable and easier to use APIs. They understand that every time an API is down, unresponsive or slow enterprises run the risk of losing customers, damaging company reputation and losing revenue. At the same time, API security breaches are at an all-time high.

Fintech is one of the fastest-growing mobile app categories in the U.S. To stand a chance as a fintech startup, you need to make sure that your fintech app delivers a top-notch experience. Read about the three main things you need to do to get there!

Fully managed ELT, DataOps and more trends that will change the way we use data this year.

I struggled with two aspects of software development as a junior engineer: structuring large codebases and writing testable code. Test-driven development is such a common technique that is often taken for granted, but it's not always clear how code can be made fully testable. I remember reading examples where an author would cleanly unit test a function, and in principle, it made sense. But real code doesn't look like those examples.

Metered Billing has finally arrived in Moesif and we are super excited to be rolling out this latest feature. We have worked hard to deliver a smooth and simple way to monetize your APIs by allowing usage that is tracked in Moesif to be metered and billed by your favorite billing providers. Moesif can calculate and send usage data to a billing provider so your customers can be billed accurately, based on their usage.

Kafka is a ubiquitous component of a modern data platform. It has acted as the buffer, landing zone, and pipeline to integrate your data to drive analytics, or maybe surface after a few hops to a business service. More recently, though, it has become the backbone for new digital services with consumer-facing applications that process live off the stream. As such, Kafka is being adopted by dozens, (if not hundreds) of software and data engineering teams in your organization.

Analysis-ready data models are built using sequences of transformations. Here's an example using Fivetran’s data model for Salesforce.