Operations | Monitoring | ITSM | DevOps | Cloud

AWS Parallel Computing Service (AWS PCS) is a managed service that helps users run and scale their high performance computing (HPC) workloads. AWS PCS uses Slurm, an open source workload manager, for scheduling and orchestrating simulations, which enables users to build their scientific and engineering models in a familiar HPC environment.

The classic thought experiment known as Schrödinger’s Cat imagines a cat that’s simultaneously alive and dead; that is, until someone opens the box. In other words, it’s both alive and dead until the point that we can confirm the truth. Now, swap the cat for software vulnerabilities, and you’ve got a fantastic analogy for what happens in today’s security environment.

We've just launched one of our biggest feature updates yet - Early Outage Detection. This fundamentally changes how IsDown works, transforming it from a reactive monitoring tool into a proactive early warning system.

If you’re in IT operations, you’ve likely faced the disconnect firsthand: your dashboards say everything’s green, but your business stakeholders are asking why the website is slow, the customer portal is timing out, or a regional service is underperforming. Your team is usually on top of issues, such as monitoring infrastructure health, resolving alerts, and keeping systems online. But the business isn’t looking at device uptime.

Downtime is more than an inconvenience these days, nor is it solely a problem for the ITOps team. Since every organization is a digital business, downtime can cost millions of dollars per hour, stall innovation, and erode customer trust. Yet most IT teams are still trapped in reactive mode, scrambling across fragmented tools and drowning in alert fatigue. That model no longer works. The future of IT is about foresight, not firefighting.

As technology scales and data volumes accelerate, organizations face a pressing challenge: how can they modernize data infrastructure without putting daily operations at risk? Data historians, specialized databases that capture and store time-stamped machine and sensor data, have long been the foundation for reliability and compliance. However, they were not designed for the openness and advanced analytics that modern workloads demand.

AI adoption continues to explode, and so do their costs. By mid-2025, enterprise LLM spend had already hit $8.4 billion, more than double the year before. And in a major shift, Anthropic recently overtook OpenAI as the enterprise leader. Their Claude models are now core tools for companies adding generative AI technology into their products and workflows. CloudZero recently announced we are the first cloud cost platform to integrate with Anthropic.