Operations | Monitoring | ITSM | DevOps | Cloud

The question "what do you use for AI agent infrastructure?" has become one of the most searched queries in the DevOps and platform engineering space. And for good reason: the global AI agent market is projected to grow from $5.1 billion in 2024 to $47.1 billion by 2030, representing a compound annual growth rate of nearly 45%. With 85% of enterprises expected to implement AI agents by the end of 2025, getting the infrastructure right has never been more critical.

APIs are the connective tissue of the modern digital world. They power our mobile apps, enable microservices to communicate, and connect us to third-party data. But this central role also makes them a prime target for attackers. While we build powerful functionalities, it's often the simplest oversights in authentication that leave the front door wide open.

The rapid evolution of digital health solutions demands robust approaches to application development that prioritize both security and regulatory adherence. Secure & Compliant Healthcare App Development Services encompass a comprehensive framework designed to safeguard sensitive patient information, ensure privacy, and meet stringent industry standards. By integrating best practices in software engineering, risk management, and regulatory compliance, healthcare providers and technology partners can deliver reliable, scalable, and user-centric applications.

Does your team spend more time fighting with its software than getting work done? It's a common frustration: forcing your company's unique, proven processes to fit inside the rigid boxes of off-the-shelf software. You're left juggling spreadsheets, manual workarounds, and disconnected systems that slow down growth and create operational headaches.

For the team that's down in the trenches untangling legacy code, writing unit tests, and just trying to come up with sensible variable names, it's easy to lose sight of the other end of the process, where code meets customer. You test, you deploy, nothing breaks, and you move on. However, it's just as important to keep an eye on code quality in production, and how it's experienced. Experience, though, is hard to quantify. What do you measure? How do you measure it? How do you improve it? And why do you care? We lay out answers in this post.