APIs have become the backbone of our digital world, with surveys showing that over 70% of developers plan to increase API usage year-over-year. They power everything from mobile apps and SaaS integrations to IoT devices and partner platforms, enabling businesses to deliver seamless services and experiences to customers. As organizations grow, however, so does the complexity of their API ecosystem.
If you’re feeling intimidated about creating your first automated web test with Ghost Inspector, we’ve got you covered! In this article, we show you how easy it is to build and automate web tests with Ghost Inspector. We’ll break down creating your first Ghost Inspector test in just four simple steps. Once you’ve learned the basic steps for how to build a web test, you’ll be able to test complex processes easily, even with zero coding know-how. Ready? Let’s jump in.
We recently had the pleasure of chatting with Dots Oyebolu on the podcast, where we talked about marketing metrics that matter (LTV, ACV, revenue), his two-dimensional marketing framework of combining Go-to-Market Motions (inbound, outbound, partnerships, community, PLG) with Marketing Approaches (brand awareness, demand generation, performance marketing), and why all three marketing approaches need to work together.
In this demo, we’ll show you how to create a custom Data Metric Function (DMF), associate it with your tables for continuous data quality monitoring, and query the results from a centralized table. Watch to learn how built-in monitoring helps you track critical data objects, identify quality issues, and take quick action to ensure reliable, high-integrity data across your organization.
Join Danielle Forier, Software Quality Assurance Analyst, as she shares the journey of how her QA team transformed their testing strategy by integrating functional and performance testing. Discover how reusable scripts and the right tools helped them achieve seamless workflows, greater efficiency, and the scalability needed to manage a growing and complex product portfolio.
Many organizations run Apache Kafka clusters in private Azure networks to meet stringent security, compliance, and operational requirements. However, securely replicating data across clusters without exposing traffic to the public internet has traditionally been complex, requiring self-managed mirroring solutions with significant operational overhead.
LLM Data Gateways are specialized tools that prepare and secure data for AI systems, ensuring better performance, compliance, and cost efficiency. They act as a bridge between raw data and large language models (LLMs), solving common challenges in AI like poor data quality and security risks.
Ruby and Rails are great tools that allow you to create complex web applications quickly. Well, some kinds of complex web applications. While they excel at traditional, monolithic, server-rendered applications, they fail to excel at delivering real-time or distributed services. This is why it's so handy for Rubyists to learn a programming language like Go. Go is designed to write lightweight services that handle lots of inbound connections.