Operations | Monitoring | ITSM | DevOps | Cloud

There is a strong push for adopting Kubernetes’ base Agentic Framework, given the adoption for containers and the similarities between containers and agents ( agents are stateful though).

Monitoring systems have become absolutely critical for modern businesses, and understanding the fundamentals of application monitoring is key to success. But when it comes to serverless monitoring, the game gets even trickier. Serverless architectures, while offering incredible flexibility and cost advantages, present unique monitoring challenges that traditional approaches simply can't handle.

Monitoring your Kubernetes clusters is critical for maintaining reliable applications. But with so many metrics to track and tools to choose from, setting up effective monitoring can feel overwhelming. The Cloud Native Computing Foundation (CNCF) highlights record Kubernetes adoption, underscoring the growing need for robust monitoring solutions. Search for "Kubernetes monitoring" and you'll find a sea of contradicting information, countless tools, and complex setups.

Delivering reliable software is like trying to hit a moving target. As a DevOps professional, you're constantly balancing speed and stability, all while user expectations grow and technology landscapes shift. Without proper feedback mechanisms, you're essentially flying blind. The good news? DevOps feedback loops provide the visibility and insights needed to navigate this complex environment. They are the fundamental building blocks that enable continuous improvement in software delivery and operations.

Companies running Kubernetes workloads often discover significant and unexpected waste or underutilized resources in their compute environment. Smart organizations implement a host of FinOps activities to mitigate this waste and the cost it incurs: … and the list goes on. But these are infrastructure-level optimizations that don’t address waste within an application.

Cloud Pathfinder simplifies cloud troubleshooting by visually mapping connectivity paths between cloud endpoints and integrating the power of AI, identifying where and why traffic is being blocked. By analyzing cloud configuration metadata, it provides instant, actionable insights into routing and security issues — saving engineers hours of manual work.

A well-crafted status page helps you build trust, reduce support tickets, and keep stakeholders informed in real time. But with so many tools available, which one should you choose? We’ve rounded up the top 10 status page tools — from legacy platforms to modern, dev-first options. Let’s dive in!

The pace of software development has changed. With AI coding assistants now embedded into engineering workflows, developers are building faster, shipping sooner, and writing more code than ever before. But as velocity increases, so does the complexity of keeping that code running. When builds fail, developers need answers fast. They need clarity, context, and actionable feedback right where they’re working.

Artificial intelligence (AI) is revolutionizing the way we address real-world challenges, from fraud detection and customer service optimization to groundbreaking healthcare research and treatment. At the core of these advancements lies robust data center infrastructure.

The M365 suite is vast, and the mountains of data that accumulate within each application are huge and ongoing. While data reporting is a necessity, management can feel unwieldy. Luckily, there is an array of reporting software on the market to support this challenge. This blog explores three powerful tools for M365 reporting: SquaredUp, Microsoft 365's native reporting tool, and Power BI.