ManageEngine its network performance management and data center monitoring software.
Available today in beta, the new OpManager introduces the industry's most cost-efficiently scalable network management platform to monitor one million interfaces from a single standalone server — for less than $1 million.
The move shatters long-standing price/performance barriers in data center and private cloud monitoring, delivering carrier-grade scalability at commodity prices.
ManageEngine is previewing OpManager support for one million interfaces at Cisco Live 2013, held June 23-27, 2013, in Orlando, Fla. A silver sponsor of the event, ManageEngine is in booth 501.
IT organizations in large enterprises and data centers face a tough decision when it comes to network monitoring. They can spend millions of dollars on a solution that scales to handle up to one million interfaces in a single management console. Meanwhile, IT teams that can’t afford to spend millions on network monitoring can opt for less expensive solutions that don’t scale quite as elegantly. To monitor one million interfaces, these teams are stuck with multiple management consoles and countless polling engines. One way or another, IT teams pay a big price for large-scale network monitoring.
"The new OpManager is breaking new ground in network monitoring," said Dev Anand, director of product management at ManageEngine. "No other vendor is offering truly affordable, carrier-grade scalability. The Big 4 can scale with a single console, but users pay a huge premium for that privilege. Every other vendor just comes up short - except for us. With OpManager, we’re bringing network management scalability to the masses."
OpManager: Cost Effective, Carrier Grade
ManageEngine designed OpManager to make life easier for enterprise and data center admins. With just one advanced scalability engine, the new OpManager can support one million interfaces to let admins expand their monitoring dynamically to suit their proliferating IT. ManageEngine has further streamlined the OpManager solution by minimizing the learning curve and shrinking deployment time to minutes - without assistance.
Anand said, "We listened to our customers closely and studied the market carefully in developing the new OpManager. We didn’t want to introduce the implementation, training costs, and complexities that accompany the Big 4 solutions. And we didn't want to overwhelm admins with the additional hardware, software and maintenance burden that are typically found in less expensive solutions. OpManager blends scalability and affordability to hit the network monitoring sweet spot."
The new OpManager advanced scalability engine that supports one million interfaces is available now in beta.
Related Links:
OpManager customers click here to try it via the beta program
The Latest
Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...
In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ...
Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...
Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...
Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...
The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...
The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...
In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...
AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.
The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...