Systems | Development | Analytics | API | Testing

It’s not enough to just test our code's happy path (in other words, the error-free path we hope our users will take). To be really confident our code can’t be abused, either accidentally or on purpose, we must actively attack it to try and find ways of breaking it. If we don’t do this, someone else will, and they probably won’t be as friendly.

Imagine building a system where you want to validate if the logic implemented would fit in when the entire system is built, but for that, you would have to build the entire architecture (well, a lot of resources are spent). Now imagine a way where you can simulate the versions of real objects or components. This is where Data Mock comes into play!

When integrating Snowflake, you have four main options to choose from, each suited to specific needs.

It helps you make better decisions. Don’t get me wrong, saving 12~ hours every month is great. But the biggest value is the ability to gather stakeholders around the data, to help them see what performance was, what changed, and what to do next. That’s where the magic happens. You’re not just saving time. You’re focusing on improving key metrics together. Great reports help you find opportunities to improve, or address downward trends before they get worse.

With the advent of generative AI and large language models (LLMs), enterprises are racing to unlock as much business value as possible from their data assets, including apps and models. Unfortunately, these data assets are often locked away in silos across multiple cloud service providers and solutions, as well as across different partner, customer and vendor ecosystems.

Using a JSON mock allows you to avoid using fake data or simulating interactions, resulting in better final output and stronger data flows. Today, we’re going to dive into the process of creating a mock API using JSON data and tools like JSON-server. This guide will help you understand the basics of this process and get started quickly with your own mock API, allowing you to speed up development and testing without relying on a live backend.

While Elixir provides built-in libraries (like HTTPoison) for making HTTP requests, the Tesla library has gained popularity due to its simplicity, ease of use, and extensibility. Tesla offers a clean and composable way to define requests, handle responses, and customize client behavior. Even so, whenever you're working with external APIs, errors are inevitable. Network issues, server downtime, rate limiting, and unexpected responses can all lead to errors in your application.

In the alphabet of mobile app development, it’s always been our honor to be so close to BrowserStack, so when the opportunity arose to officially partner up to improve your mobile DevOps experience: it was a no-brainer. We’re partnering to offer our customers access to best-in-class mobile-first CI/CD and automated mobile device testing, including an incredible free product offer.

Blockchains enable individuals and organizations to record and verify transactions as part of a secure, transparent, and decentralized system. They form the basis of most cryptocurrencies, and are used as the foundation of many other applications—smart contracts, supply chain management, and digital identity verification, to name but a few.

Python’s subprocess module stands as one of the most powerful tools in a developer’s toolkit. The module lets you spawn new processes, connect to their input/output/error pipes, and get return codes. Think of the subprocess module as your bridge between Python scripts and system commands, replacing older modules like os.system and os.spawn and providing a better, unified way to handle external processes.