Operations | Monitoring | ITSM | DevOps | Cloud

In my conversations about managing large, complex networks, one topic is now constant. The issue isn't budgets or new technology; it's about personnel. Specifically, it's the increasing difficulty of finding and retaining skilled professionals. If you are feeling this pressure, you are not alone. The search for technical talent is a universal challenge.

Metrics are fundamental to experimentation for two reasons: They set the basis for evaluating ideas and interventions, and they can suggest where to look next. As such, many teams collect a wide variety of metrics, from application performance data to revenue trends. However, doing so often means manually knitting together data from multiple sources and formats. Even then, data silos can make it challenging to understand the full impact of experimental changes. In this post, we’ll explore.

Debugging JavaScript errors just got easier. Today, we're launching Session Replay for Rollbar, giving you visual context for every error with customizable triggers and the only open-source MCP integration that lets AI analyze your sessions directly in your IDE.

The network has transformed dramatically. Hybrid cloud architectures and AI-powered infrastructure seem to expand in scale and complexity every day. But legacy tools to monitor and observe these networks have not kept up.

“Please enter the code we just sent you.” – most people have seen this message when logging into an online service. Two-Factor Authentication (2FA) is no longer reserved for banks or enterprises. It’s now common in email, social media, and shopping accounts. The idea is simple: in addition to a password, you need a second factor so that attackers can’t break in with just one piece of information. But what methods are actually used – and how secure are they really?

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.