Systems | Development | Analytics | API | Testing

Since the release of the Defense Innovation Board (DIB)'s Software Acquisition and Practices (SWAP) report in 2019, the Department of Defense (DoD) has focused on adopting and recommending DevSecOps best practices for aerospace and defense development and software acquisition, as detailed in the DoD's 2024 State of DevSecOps report.

Software is now the front door of your business, and when it fails, revenue and trust are on the line. Yet quality assurance is still too often treated as a cost center instead of a growth driver. The AI mandate is raising the stakes: boards expect faster delivery through AI and low-code, but that speed creates more complexity to test. Most QA teams still rely on manual processes, leaving quality as the bottleneck.

The AI mandate is real. Boards and executives are demanding that software organizations move faster, embrace AI, and deliver without breaking trust. Development velocity is accelerating at machine speed, but testing has not kept up. The question every QA leader faces today is simple: will quality keep pace, or will it become the bottleneck? This is where the shift from automation to AI-native testing comes in.

When you write a Selenium test, every interaction depends on one crucial step: identifying the right element. Whether it's a button, input field, dropdown, or link, Selenium must find it before it can click, type, or select. This is where element locators come in. These strategies help your Python scripts pinpoint specific pieces of the page, just like a user would. In this guide, you'll learn exactly how to find element in Selenium with Python confidently and consistently.

Databases are the spine of most any app we use today, from a banking app to an online shopping site. Good application is hidden under cover of the user interface, in the basement, in the room where the data is stored, processed and fetched. Database testing is vital for that very reason. It makes data accurate, secure and trustworthy, which in turn keeps apps stable and businesses running smoothly.

In January this year, financial institutions across the EU were faced with a clear mandate – the Digital Operational Resilience Act (DORA): to ensure digital resilience, maintain service continuity and strengthen oversight of Information and Communication Technology (ICT) partners.

When AI projects derail, it’s rarely because the model was weak. More often, failure comes from using MCP in the wrong way—forcing it to act as a universal API, data pipeline, or real-time engine instead of what it truly is: an orchestration and intelligence layer. Recently, Nate B.

We are thrilled to announce that Confluent Cloud for Government is now available on the FedRAMP Marketplace with FedRAMP 20x Low authorization, allowing both private and public sector customers to leverage our cloud-native data streaming platform to power their mission-critical applications. This milestone marks the successful completion of Phase One of our FedRAMP 20x Pilot program.

IT leaders have long believed that integration is the best way to connect a chaotic enterprise technology landscape. However, that approach is falling short. It's not powerful enough to manage the complexity, which has only increased with the introduction of AI. What’s needed now is an overarching, holistic view of people, data, processes, and AI—a view that’s made possible with end-to-end process orchestration.

If you’re leading a product team, working on Software Development for Startups, or scaling an enterprise IT roadmap in 2025, you’ve probably felt it. The pressure to move fast, stay secure, and deliver innovation without blowing your budget is very real. But here’s the catch: you’re not just shipping late without a strategy. You’re risking technical debt, security gaps, and missed market opportunities.