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NS1 Releases Pulsar Traffic Analysis Dashboards

NS1 unveiled Traffic Analysis Dashboards for its Pulsar Active Traffic Steering solution.

With real-time metrics about availability, latency, and traffic distribution, these interactive dashboards make it simple and intuitive to monitor and optimize application delivery across multi-cloud, multi-CDN, and edge environments, enabling performance optimization at a global scale.

NS1’s Pulsar Active Traffic Steering makes application delivery in diverse, distributed environments highly observable and consistently performant by collecting and analyzing real user monitoring (RUM) data at a global scale and then taking action to dynamically and automatically steer traffic over DNS or via HTTP decision endpoint for superior application experiences.

Pulsar Traffic Analysis Dashboards provide insights into the data used to make decisions and how Pulsar actioned that data. This provides increased observability and control for administrators, allowing them to intelligently tune their traffic steering policies to optimize for performance, availability, and cost savings.

“Internet and network conditions can change constantly and unpredictably, which makes it difficult to deliver consistent, superior user experiences,” said Sanjay Ramnath, VP of Products at NS1. “Pulsar solves this challenge by acting on real-time data to optimize for performance and cost at scale. Pulsar’s decisions are now displayed along with deep insights in traffic analysis dashboards, improving visibility into network conditions and making Pulsar data more actionable.”

NS1’s Pulsar transforms insights into action by consuming internet, infrastructure, and RUM data and providing a powerful policy engine through patented Filter Chain™ technology. Intuitive dashboards display real-time metrics so network administrators have visibility into the conditions and policies driving Pulsar’s automated decision-making. Through a single-pane-of-glass view, teams can easily filter and drill down into the highly granular data about traffic distribution and output datasets to quickly surface performance trends—like how often Pulsar has prevented downtime—and identify issues for efficient troubleshooting. Armed with this data, administrators can better communicate the value of their program to executive leaders and continue to fine-tune their traffic steering policies to optimize application delivery performance at the edge.

With the recently launched NS1 Connect platform, the company’s unified technology stack provides connectivity for internal and external applications with the same advanced traffic management capabilities independent of where applications are deployed: on-premises, public clouds, private clouds, or hybrid clouds.

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NS1 Releases Pulsar Traffic Analysis Dashboards

NS1 unveiled Traffic Analysis Dashboards for its Pulsar Active Traffic Steering solution.

With real-time metrics about availability, latency, and traffic distribution, these interactive dashboards make it simple and intuitive to monitor and optimize application delivery across multi-cloud, multi-CDN, and edge environments, enabling performance optimization at a global scale.

NS1’s Pulsar Active Traffic Steering makes application delivery in diverse, distributed environments highly observable and consistently performant by collecting and analyzing real user monitoring (RUM) data at a global scale and then taking action to dynamically and automatically steer traffic over DNS or via HTTP decision endpoint for superior application experiences.

Pulsar Traffic Analysis Dashboards provide insights into the data used to make decisions and how Pulsar actioned that data. This provides increased observability and control for administrators, allowing them to intelligently tune their traffic steering policies to optimize for performance, availability, and cost savings.

“Internet and network conditions can change constantly and unpredictably, which makes it difficult to deliver consistent, superior user experiences,” said Sanjay Ramnath, VP of Products at NS1. “Pulsar solves this challenge by acting on real-time data to optimize for performance and cost at scale. Pulsar’s decisions are now displayed along with deep insights in traffic analysis dashboards, improving visibility into network conditions and making Pulsar data more actionable.”

NS1’s Pulsar transforms insights into action by consuming internet, infrastructure, and RUM data and providing a powerful policy engine through patented Filter Chain™ technology. Intuitive dashboards display real-time metrics so network administrators have visibility into the conditions and policies driving Pulsar’s automated decision-making. Through a single-pane-of-glass view, teams can easily filter and drill down into the highly granular data about traffic distribution and output datasets to quickly surface performance trends—like how often Pulsar has prevented downtime—and identify issues for efficient troubleshooting. Armed with this data, administrators can better communicate the value of their program to executive leaders and continue to fine-tune their traffic steering policies to optimize application delivery performance at the edge.

With the recently launched NS1 Connect platform, the company’s unified technology stack provides connectivity for internal and external applications with the same advanced traffic management capabilities independent of where applications are deployed: on-premises, public clouds, private clouds, or hybrid clouds.

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I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

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 ...

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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 ...

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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 ...

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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 ...