ManageEngine launched the beta version of OpManager version 12. Available immediately, the beta release brings NetFlow monitoring and configuration management functionality to OpManager. The new add-ons help network admins at large enterprises and data centers analyze their traffic and manage network configurations for changes in addition to performance monitoring.
"Today, network issues extend beyond health and performance to application-specific traffic problems and DDoS-type attacks," said Dev Anand, Director of Product Management at ManageEngine. "Troubleshooting such issues requires capabilities such as real-time network traffic analysis and rapid configuration change detection in addition to the regular network monitoring capabilities. That's what we have done with OpManager by making NetFlow monitoring and configuration management into a single integrated product."
NetFlow monitoring and configuration management were earlier available as downloadable plug-ins to OpManager in previous versions. However, with this new version, customers don’t have to install the plug-ins separately. It comes pre-bundled with OpManager v12. This not only saves time but also provides much-needed correlation between the monitoring data and the traffic and configuration data.
For example, the new OpManager add-ons let a retailer with hundreds of stores nationwide create a map of all stores and display the application traffic on the links between each store and the ERP running at the data center. Deterioration in link quality could affect billing at the given store, resulting in loss of revenue; but typical, legacy network monitoring tools treat those links as one big pipe and alert on overall traffic problems. However, overall link volume may be fine, but the application traffic is not being adequately prioritized and packets get queued. OpManager v12 can prevent revenue loss by identifying deterioration on specific application traffic or specific DSCP QoS code traffic.
Pricing and Availability
The new NetFlow monitoring and configuration management functions are available to use in the beta release of OpManager v12.
The Latest
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 ...