Operations | Monitoring | ITSM | DevOps | Cloud

Modern software applications are increasingly complex. Microservices, cloud infrastructure, and distributed architectures make it challenging for developers, DevOps engineers, and SREs to maintain high performance and a seamless user experience. Traditional Application Performance Monitoring (APM) provides critical insights into how applications perform, but alone, it often leaves blind spots when it comes to diagnosing issues or understanding the full system behavior.

In the dojo, not every role is about throwing punches. Some roles are about awareness, the unmistakable voice that tells the fighter when to move, where the strike is coming from, and why the opponent matters. That’s the role of the Summary Agent in Sumo Logic Dojo AI. Unlike a traditional agent, it doesn’t launch queries or carry out actions on its own. Its purpose is to narrate, not act. In doing so, it becomes the foundation for every other decision in the dojo.

At Logz.io, we speak with hundreds of companies every month. One thing is consistent across the board: everyone ships logs. But the challenges are equally common: What are the best practices for logging? How do we reduce noise? How should we architect our logs to make them truly useful? The reality is that logs are noisy for everyone. The best time to standardize your logging practices is when you write your first line of code—though that rarely happens. The second-best time is now.

We are proud to announce that Elastic has been named a finalist by the Technology & Service Industry Association (TSIA) in the 2025 STAR Awards program for Innovation in Customer Portals that Improve Digital Customer Experience. This award recognizes Elastic’s ability to embrace AI innovations to enhance our digital customer experience.

From ecosystem foundations to future advantage In Part 1: Why partnerships matter for enterprise intelligence, we explored how enterprises are moving from experimentation to scalable impact with agentic AI and how ecosystems make that possible. But naturally, the next question is: Where do we go from here?

The RED method is a streamlined approach for monitoring microservices and other request-driven applications, focusing on three critical metrics: Rate, Errors, and Duration. Originating from the principles established by Google's "Four Golden Signals," the RED monitoring framework offers a pragmatic and user-centric perspective on service assurance and service performance.

The pace of change in AI development has been dizzying. In just a few years, we’ve moved from experimenting with AI, machine learning (ML), retrieval augmented generation (RAG), and agents to asking how these innovations can solve real business problems. Enterprises are no longer impressed by the novelty and possibilities; instead, they expect outcomes.