Systems | Development | Analytics | API | Testing

Product-led growth hinges on delivering exceptional user experiences. If you build a great product with valuable features, users are bound to come and stick to your services. But companies often neglect the role of APIs. Modern software relies heavily on APIs for integrations, automation, and data exchange. Not to mention, for API or API-first products, APIs drive the most crucial pieces of success goals. A poorly performing API creates friction, frustrates users, and impedes growth.

Security Operations Centers (SOCs) are the backbone of organizational cybersecurity, responsible for detecting, investigating, and responding to threats in real-time. Yet, the increasing complexity and volume of cyber threats present significant challenges. SOC teams often grapple with alert fatigue, skill shortages, and time-consuming processes.

Digital transformation is no longer optional—it’s essential for staying competitive, driving value, and meeting evolving customer expectations. As Brian Solis puts it, “Digital transformation is to change the way you compete, how you create value, and how you can use digital tools and technology to be relevant as the world continues to evolve.” Organizations worldwide are taking this to heart, with spending on digital transformation expected to hit $3.9 trillion by 2027.

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.