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cPacket Integrates with MS Azure Gateway Load Balancer

cPacket Networks announced its integration with Microsoft Azure’s newly launched Gateway Load Balancer (GWLB) service.

As one of Microsoft’s cloud visibility solution partners, cPacket’s cCloud Visibility Suite is deployed in Azure as an agentless bump-in-the-wire solution across leading financial and technology enterprises.

The new point of integration makes it easy to deploy, scale, and manage third-party security or application monitoring virtual appliances at the cloud edge, making it more secure and economical.

As more enterprises, governments, and service providers move to the cloud or expand to multi-cloud, visibility into network traffic is a day-one requirement for good application experience and security monitoring.

“cPacket’s cCloud solution provides deep network intelligence for security delivery, isolating application vs. network issues, and troubleshooting SLA gray areas, enabling smooth sailing pre and post cloud migration,” said Iain Kenney, Sr. Director PLM at cPacket Networks.

cPacket cCloud is among the industry’s leading and most complete multi-cloud visibility solution, including cloud-native packet brokering, packet capture, and service-level indicators (SLI) such as stateful analysis for TCP and real-time UDP/RTP applications, latency monitoring, connection issues, as well as PCAP files for security forensics.

“Through Microsoft Azure Gateway Load Balancer, customers can easily use the virtual appliances they need without additional management overhead, reducing the risk of downtime due to erroneous changes and eliminating single points of failure,” said Narayan Annamalai, Partner PM Manager, Microsoft.

The integrated solution has several benefits for the end-users: reduced risk, service agility, faster deployment of third-party virtual appliances, better scalability, higher availability, and reduced cost and complexity.

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cPacket Integrates with MS Azure Gateway Load Balancer

cPacket Networks announced its integration with Microsoft Azure’s newly launched Gateway Load Balancer (GWLB) service.

As one of Microsoft’s cloud visibility solution partners, cPacket’s cCloud Visibility Suite is deployed in Azure as an agentless bump-in-the-wire solution across leading financial and technology enterprises.

The new point of integration makes it easy to deploy, scale, and manage third-party security or application monitoring virtual appliances at the cloud edge, making it more secure and economical.

As more enterprises, governments, and service providers move to the cloud or expand to multi-cloud, visibility into network traffic is a day-one requirement for good application experience and security monitoring.

“cPacket’s cCloud solution provides deep network intelligence for security delivery, isolating application vs. network issues, and troubleshooting SLA gray areas, enabling smooth sailing pre and post cloud migration,” said Iain Kenney, Sr. Director PLM at cPacket Networks.

cPacket cCloud is among the industry’s leading and most complete multi-cloud visibility solution, including cloud-native packet brokering, packet capture, and service-level indicators (SLI) such as stateful analysis for TCP and real-time UDP/RTP applications, latency monitoring, connection issues, as well as PCAP files for security forensics.

“Through Microsoft Azure Gateway Load Balancer, customers can easily use the virtual appliances they need without additional management overhead, reducing the risk of downtime due to erroneous changes and eliminating single points of failure,” said Narayan Annamalai, Partner PM Manager, Microsoft.

The integrated solution has several benefits for the end-users: reduced risk, service agility, faster deployment of third-party virtual appliances, better scalability, higher availability, and reduced cost and complexity.

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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 ...

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 ...