Operations | Monitoring | ITSM | DevOps | Cloud

There’s no doubt that managing networks today is a whole different ballgame than it used to be. Complexity is growing, environments are more fragmented, and user expectations have never been higher. One of the biggest challenges for network operations teams? Visibility—or the lack of it. Network operations used to be much simpler. Traffic flowed through your own data center, and you had the visibility and control needed to manage performance and troubleshoot issues.

Whether you’re dealing with IT issues, customer questions, or just trying to keep track of who’s supposed to fix what and when, ticketing tools are the unsung heroes of organized chaos. They help teams stay on top of requests, assign responsibility, (no more “I thought you were going to handle it”) and actually close the loop on problems instead of letting them collect dust in someone’s inbox.

Data plays a critical role in shaping operational decisions. From sensor streams in factories to API response times in cloud environments, organizations rely on time-stamped metrics to understand what’s happening and determine what to do next. But when that data is inaccurate or incomplete, systems make the wrong call. Teams waste time chasing false alerts, miss critical anomalies, and make high-stakes decisions based on flawed assumptions.

We spoke to data professionals from a range of industries about the impact of unreliable database deployments — not just on their systems, but on their workload, time, and well-being. From delayed releases to weekend firefighting, and the fallout for teams and customers, they share the day-to-day pressures they face and the small changes that help make deployments, and life, a little less stressful. What stood out from these conversations?

Recently, Catchpoint expanded our Global Agent Network to over 3,000 agents. In a crowded space, this is by far one of our key differentiators. At the time of writing, no one else boasts 395 providers in 105 countries and 346 cities. As Director of ISP Strategy, I’m not here to pat myself on the back—my real question is: why?

In this blog we are going to address how to use Splunk to monitor security of MCP Servers, a new technology that has been developed by Anthropic and has definitely bridged the use of local applications with Large Language Models (LLMs).

When a container starts consuming excessive memory or becomes unresponsive, you need a way to shut it down. The two primary options — docker stop and docker kill,both terminate containers, but they operate differently and have different implications. The key difference: docker stop sends SIGTERM for a graceful shutdown, then escalates to SIGKILL if the process doesn’t exit in time. docker kill skips straight to SIGKILL, terminating the container immediately.

AI assistants will shape the future of the software supply chain, and today, we’re sharing a glimpse of a powerful idea in motion: Cloudsmith MCP, a proof of concept server that connects large language models (LLMs) like ChatGPT and Claude directly to your software supply chain using the emerging Model Context Protocol (MCP) standard.

As applications grow more complex and user expectations rise, delivering seamless and high-performing experiences to users is non-negotiable. Real User Monitoring (RUM) has emerged as an essential technique that provides developers, DevOps teams, and site reliability engineers with deep visibility into the actual performance of web applications that capture the experiences of real people in real-time.