Systems | Development | Analytics | API | Testing
Modern Software Development For Today's Systems & Applications
Delivering scalable, serverless APIs with SmartBear and AWS
Amazon API Gateway and AWS Lambda are widely used for deploying and running scalable APIs or applications in the cloud. While they offer powerful capabilities for deploying and scaling APIs, designing the API or maintaining visibility into performance and reliability can be challenging without the right tools in place.
From Strategy to Execution: Driving API Maturity with API Hub
Defining an API strategy is important—but its execution is what separates high-performing teams. APIs play a central role in delivering connected, high-quality digital experiences. But turning strategy into execution—at scale—remains a challenge for many organizations.
Amplify and Automate Your API Testing with ReadyAPI and TestEngine
In today’s fast-paced world of software development, the pressure to deliver high-quality releases quickly is stronger than ever. Teams are pushing code changes to production multiple times a day, and expectations around stability, security, and performance haven’t gone down—in fact, they’ve gone up. Manual testing simply can’t keep up with the speed and complexity of modern deployment cycles.
From Flaky to Reliable: How QMetry Keeps Your Pipeline Clean
Not every failure is a bug and not every bug is what it seems. Sometimes, a test fails without warning. No code changes, no environment issues, just a red mark where there should be green. You rerun it, and it passes. These are flaky tests. And they do more than create noise. They drain team time, stall releases, and make it harder to trust automation at all. Left unchecked, they quietly become one of the most expensive problems in testing.
What is an API first approach?
APIs already account for 71% of all internet traffic, but here's what most companies are missing: AI is about to become the biggest API consumer ever. As generative AI transforms how we interact with software, agentic workflows will perform automated, API-heavy interactions on our behalf. Companies that embrace an API-first approach now will dominate tomorrow's AI economy. In this video Frank Kilcommins, Principal API Technical Evangelist at SmartBear, explains what it means for a software development organization to be API-first.
Long live the human tester: QA in a post-AI world
This article originally appeared on DevPro Journal. We’re sharing it here for our audience who may have missed it. QA’s job has always been simple: find the bugs before your customers do. There was a time when that meant checking every corner of an application by hand, clicking through countless possible user scenarios. Today, with software moving faster and expectations higher, a tiny slip can cost your business. Testing that’s quick, precise, and thorough has never been more critical.
SmartBear Honors Dominik Krichbaum of ING Germany with 2025 Quality Champion Award
Quality Champion Award celebrates the leaders behind exceptional software quality and extraordinary user experiences it enables.
Why API-First Matters in an AI-Driven World
APIs have long been the backbone of modern software systems, architectures, and businesses. They now dominate the web, accounting for 71% of all internet traffic. Generative AI is accelerating this trend especially as we pivot our interaction with common web-based capabilities, like “search” in favour of AI-enriched variants. More AI leads to more APIs, and with that, APIs act as an important mechanism to move data into and out of AI applications, AI agents, and Large Language Models (LLMs).
Embed Quality to Ensure Regulatory Compliance in FinTech Solutions
This article originally appeared on Software Testing News. We’re sharing it here for our audience who may have missed it. An overlooked API can expose customer data, trigger multi-million-dollar fines, and sink a FinTech product launch. And now, the FinTech industry is at a crossroads, driven by innovation yet bounded by intensifying regulatory demands.
Modern apps broke observability. Here's how we fix it.
This article originally appeared on DevPro Journal. We’re sharing it here for our audience who may have missed it. For years, APM tools were everyone’s go-to solution for understanding how software behaved in production. And for a time, they worked, because architecture was simpler. Developers owned the backend, the frontend, and the data layer. Everything lived inside a monolith. If something went wrong, they could trace it through their codebase and fix it.
From Hours to Seconds: How QMetry Uses AI to Redefine Test Case Creation
Testing has evolved far beyond scattered spreadsheets and disconnected tools. Yet even with modern platforms in place, teams still run into bottlenecks, especially when fundamental tasks like test case creation are handled manually. It involves combing through acceptance criteria, writing out each step, and reviewing everything for gaps. Repeating that across multiple user stories quickly drains time and slows progress – it’s repetitive, time-intensive, and prone to inconsistency.