Operations | Monitoring | ITSM | DevOps | Cloud

Managed service providers (MSPs) are strong multitaskers, handling monitoring, documentation, security, infrastructure maintenance, support, and more for each of their clients. So clearly the need for a strong set of MSP tools is one that cannot be overlooked. In the current state of IT, clients expect swift response and seamless service delivery no matter the time of day, meaning, MSPs must invest in a toolkit that will enable them to deliver high-quality service 24/7.

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.

From the beginning, PagerDuty has been built by developers, for developers. Our mission has always been to help development teams build faster and resolve incidents more efficiently by meeting them where they work. Building on PagerDuty’s existing plugin for Spotify for Backstage, we are thrilled to announce the PagerDuty plugin for Spotify Portal for Backstage to continue bringing enterprise-grade incident management into even more developer workflows.

There’s growing unease in the database world regarding delivering at speed, raising the question – just how do we keep up with the pace of change without losing control of the things that matter most? AI is rapidly transforming the mechanics of how code is written, reviewed, and optimized which in-turn, increases the risk of destabilization.

“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.

There’s a striking disconnect happening in software development right now. According to the 2025 Stack Overflow Developer Survey, 84% of developers are using or planning to use AI tools in their workflows. Over half of professional developers are using AI daily. The adoption is real, it’s fast, and it’s accelerating.

Kubernetes began as a tool to help teams keep thousands of microservices running without falling apart. It gave them a way to schedule workloads, recover from failures, and scale services without constant firefighting. Now, AI has brought back the same chaos, only magnified. Training jobs sprawl across GPUs. Inference traffic spikes without warning. Pipelines stretch across clusters, clouds, and compliance boundaries. Left unchecked, it can break both your workload and cloud budget.