Systems | Development | Analytics | API | Testing

Many API developers and companies struggle to find ways to easily set up systems to monetize their APIs. Some are simple but not customizable, some are complex and require massive engineering effort to actually get it all running. To make things easier, Moesif created a feature a few months ago called Billing Meters which gives massive customizability but with a minimal amount of code and engineering effort.

API load testing, which identifies how stable your APIs are under different workloads, is a crucial part of performance testing. In this guide you will learn what is API load testing, when to perform load testing, and more. One growing pain of increasing iterative development and shortening release cycles is a growing inability to detect and fix inefficient code – whether in the CI/CD pipeline or in production.

Nearly a year ago, we launched N|Solid SaaS, and although there are still a few months to go before our anniversary, we wanted to share the top 10 features ofN|Solid that make us proud every day of what we have built.

DBTA recently hosted a roundtable webinar with four industry experts on “Unlocking the Value of Cloud Data and Analytics.” Moderated by Stephen Faig, Research Director, Unisphere Research and DBTA, the webinar featured presentations from Progress, Ahana, Reltio, and Unravel. You can see the full 1-hour webinar “Unlocking the Value of Cloud Data and Analytics” below. Here’s a quick recap of what each presentation covered.

I was chatting with Sanjeev Mohan, Principal and Founder of SanjMo Consulting and former Research Vice President at Gartner, about how the emergence of DataOps is changing people’s idea of what “data observability” means. Not in any semantic sense or a definitional war of words, but in terms of what data teams need to stay on top of an increasingly complex modern data stack.

Barr-C, the Barr Group’s coding standard, aims to reduce bugs in embedded software, as well as introduce stylistic guidelines to improve maintainability and portability. Here, we explain what is Barr-C, how developers can detect bugs in firmware written in C with BARR-C:1018, and how it can be coupled with guidelines from MISRA.

Conventional databases are no longer the appropriate solution in a world where data volume is growing every second. Many modern businesses are adopting big data technologies like data lakes to counter data volume and velocity. Data lake infrastructures such as Apache Hadoop are designed to handle data in large capacities. These infrastructures offer benefits such as data replication for enhanced protection and multi-node computing for faster data processing.

The data pipeline is at the heart of your company’s operations. It allows you to take control of your raw data and use it to generate revenue-driving insights. However, managing all the different types of data pipeline operations (data extractions, transformations, loading into databases, orchestration, monitoring, and more) can be a little daunting. Here, we present the 7 best data pipeline tools of 2022, with pros, cons, and who they are most suitable for. 1. Keboola 2. Stitch 3. Segment 4.

Is repetitive and menial work impeding your data scientists, analysts, and engineers from delivering their best work? Consider automating your data analytics to free their hands from routine tasks so they can dedicate their time to doing more meaningful, creative work that requires human attention. In this blog we are going to talk about: Now let’s dive in.

The XML data format has been around since 1996. It was first envisioned as a lingua franca (bridging language) for data to be serialized and read into completely disparate systems (with different programming languages, operating systems, and even hardware). It has been wildly successful in that goal. In software, though, 26 years is like a lifetime — and in hardware, it's an eternity.