Operations | Monitoring | ITSM | DevOps | Cloud

In today’s interconnected world, a fundamental question plagues every network administrator and SRE: “Is my network running well?” The answer, often elusive, is precisely what Pingmesh aims to provide. By deploying a vast fleet of specialized probe agents, Pingmesh continuously monitors critical network health metrics, including latency, packet loss, jitter, and custom reachability checks, providing an unparalleled view into your network’s performance.

Last week saw several huge milestones for BigPanda. We launched the BigPanda agentic IT operations platform, a sweeping evolution of our product offerings. As part of this launch, we also introduced two new AI solutions, BigPanda AI Detection and Response and BigPanda AI Incident Assistant. These powerful new capabilities bring agentic AI into IT operations, transforming how enterprises automate the manual and time-intensive workflows of ITOps, L1 response, and incident management.

In a world of constant disruption, operational resilience is now mission critical. From cyberattacks and misconfigurations to vendor outages and natural disasters, today’s enterprises are navigating risks that move faster and hit harder than ever before. As we enter 2025, operational resilience has evolved from a best practice to a board-level imperative.

IT operations (ITOps) teams are challenged to keep pace with the rapid pace of digital transformation. As companies use more cloud-based apps, increase agile deployments, and develop new microservices-based applications, their technology stacks become exponentially more complex. This makes life increasingly challenging for the teams responsible for maintaining reliable IT services and infrastructure. Hybrid tech stacks are siloed, complex, and fragmented.

We’ve been in the war rooms. We’ve watched revenue, reputation, and trust erode in real time—not because we lacked telemetry, but because we lacked architecture. Modern enterprise systems fail because their data doesn’t think. Their tooling doesn’t remember. And their automation doesn’t know when to act—or when to stop. The answer is not more monitoring. It’s not dashboards with AI labels.