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LogicMonitor Acquires Catchpoint

LogicMonitor has completed its acquisition of Catchpoint. 

Together, LogicMonitor and Catchpoint are redefining how modern businesses run, ending downtime and eliminating blind spots across the backbone of today’s connected world.

By combining LogicMonitor’s deep infrastructure and AI expertise with Catchpoint’s Internet-level intelligence, the new LogicMonitor platform delivers predictive visibility and control across cloud, code, and the Internet itself. The goal is simple: stop chasing alerts and start staying ahead of them.

“This is a defining moment for LogicMonitor and for enterprise technology,” said Christina Kosmowski, CEO of LogicMonitor. “Until now, IT teams have been juggling point tools that promise insight but deliver noise. That ends today. Together with Catchpoint we are giving customers the power to predict issues, prevent downtime, and finally make their systems as smart as the people who run them.”

Catchpoint spent a decade helping enterprises keep the Internet fast, reliable, and available. LogicMonitor brings the AI scale and infrastructure reach to make that reliability universal. The result is a comprehensive observability platform for the AI-era, one that connects what enterprises own with what they depend on and keeps everything running like it should.

“Catchpoint was founded to make the Internet better for everyone,” said Mehdi Daoudi, CEO and Co-Founder of Catchpoint. “We have helped teams detect issues faster, reduce MTTR, and protect billions of sessions. Now, as part of LogicMonitor, we can do it on a global scale and redefine what performance means in the AI era.”

Once integrated, Catchpoint’s global performance data including synthetic, network, and real-user monitoring will feed directly into Edwin AI, LogicMonitor’s intelligent engine that does more than raise alarms. It explains them. Together, the platform will predict incidents, ultimately automate fixes, and give enterprises the kind of full-stack clarity that makes finger-pointing obsolete.

Here is what customers get out of the deal:

  • Comprehensive insight: Infrastructure, Internet, and user experience data in one place.
  • Predictive performance: AI that spots trouble before it becomes downtime.
  • Simpler operations: Fewer tools, fewer alerts, fewer headaches.
  • Internet-aware reliability: Visibility from the cloud to the last mile.
  • Global scale: Monitoring from thousands of vantage points worldwide.

The transaction closed following customary approvals. LogicMonitor and Catchpoint teams are already integrating capabilities to accelerate AI-driven innovation for customers worldwide. Reactive IT had its moment. LogicMonitor just made it obsolete. 

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LogicMonitor Acquires Catchpoint

LogicMonitor has completed its acquisition of Catchpoint. 

Together, LogicMonitor and Catchpoint are redefining how modern businesses run, ending downtime and eliminating blind spots across the backbone of today’s connected world.

By combining LogicMonitor’s deep infrastructure and AI expertise with Catchpoint’s Internet-level intelligence, the new LogicMonitor platform delivers predictive visibility and control across cloud, code, and the Internet itself. The goal is simple: stop chasing alerts and start staying ahead of them.

“This is a defining moment for LogicMonitor and for enterprise technology,” said Christina Kosmowski, CEO of LogicMonitor. “Until now, IT teams have been juggling point tools that promise insight but deliver noise. That ends today. Together with Catchpoint we are giving customers the power to predict issues, prevent downtime, and finally make their systems as smart as the people who run them.”

Catchpoint spent a decade helping enterprises keep the Internet fast, reliable, and available. LogicMonitor brings the AI scale and infrastructure reach to make that reliability universal. The result is a comprehensive observability platform for the AI-era, one that connects what enterprises own with what they depend on and keeps everything running like it should.

“Catchpoint was founded to make the Internet better for everyone,” said Mehdi Daoudi, CEO and Co-Founder of Catchpoint. “We have helped teams detect issues faster, reduce MTTR, and protect billions of sessions. Now, as part of LogicMonitor, we can do it on a global scale and redefine what performance means in the AI era.”

Once integrated, Catchpoint’s global performance data including synthetic, network, and real-user monitoring will feed directly into Edwin AI, LogicMonitor’s intelligent engine that does more than raise alarms. It explains them. Together, the platform will predict incidents, ultimately automate fixes, and give enterprises the kind of full-stack clarity that makes finger-pointing obsolete.

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  • Comprehensive insight: Infrastructure, Internet, and user experience data in one place.
  • Predictive performance: AI that spots trouble before it becomes downtime.
  • Simpler operations: Fewer tools, fewer alerts, fewer headaches.
  • Internet-aware reliability: Visibility from the cloud to the last mile.
  • Global scale: Monitoring from thousands of vantage points worldwide.

The transaction closed following customary approvals. LogicMonitor and Catchpoint teams are already integrating capabilities to accelerate AI-driven innovation for customers worldwide. Reactive IT had its moment. LogicMonitor just made it obsolete. 

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Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...