Operations | Monitoring | ITSM | DevOps | Cloud

How OpenTelemetry can enhance observability in distributed systems: Practical examples

Observability has become one of the fundamental elements of performance and reliability as modern applications move toward cloud-native architectures, microservices, and multi-cloud. Traditional monitoring techniques often fall short in such dynamic, distributed environments. That’s where OpenTelemetry (OTel) , an open-source observability framework comes into picture.

How a HaaS Provider Increased Profits and Efficiency with Collective IQ

Imagine managing a fleet of over 90,000 devices spread across hundreds of clients. Now, add the responsibility of ensuring that every laptop, desktop, or server is always updated, secure, and performing optimally. This is the daily reality for one of the argest Hardware as a Service (HaaS) providers in Brazil, serving over 500 corporate clients with a lean but highly specialized team.

Part 3: Building a Production-Grade Traffic Capture and Replay System

At a previous company, we had over 100 microservices. I’d make what seemed like a simple change to one service and deploy it, only to discover it broke something completely unrelated. A change to the user service would break checkout. An update to notifications would break reporting. We spent more time fixing unexpected bugs than shipping features. The problem was our test scenarios were too simple.

What Is Synthetic Monitoring?

Synthetic Monitoring is a proactive approach to testing a website or web server to ensure that digital services stay available, responsive, and functional at all times. Instead of waiting for real users to encounter a problem, synthetic monitoring uses automated scripts to imitate user interaction, such as visiting pages, submitting forms, or performing transactions from multiple global locations.

Top DevOps Challenges in 2025 and How APM Solves Them

In 2025, DevOps continues to grow and change quickly, helping teams deliver software faster and more securely. But as systems become more complex with microservices, cloud platforms, and AI-driven tools, new challenges arise. Teams now need to balance speed with security, manage too many tools, control rising cloud costs, and still maintain high-quality software. This is where Application Performance Monitoring (APM) becomes essential.

Our Engineering in the Age of AI: 2026 Benchmark Report finds AI is making engineering faster, but not necessarily better

Everyone's talking about how AI is transforming software development. Teams are shipping more code, deploying more frequently, and getting features to market faster than they could a year ago. The productivity gains are real. But we kept hearing a different story from engineering leaders. Yes, velocity is up. But incidents are climbing, resolution times are getting longer, and code review processes are struggling to keep up.

Conquer Complexity, Accelerate Resolution with the AI Troubleshooting Agent in Splunk Observability Cloud

The digital landscape has transformed dramatically, and with it, the demands on our systems have grown exponentially. Traditional monitoring tools struggle to provide sufficient insight into complex, distributed, cloud-native environments. Observability is the answer, moving beyond merely knowing "what" is happening to understanding "why" it's happening, and its impact on user experience and business outcomes.