ManageEngine, a provider of network, systems, security, and applications management software solutions, introduced a Distributed Edition of VQManager, the company’s VoIP quality monitoring software.
The new release incorporates highly-scalable remote probe technologies to support larger, more complex VoIP architectures, enabling larger enterprises to ensure call quality across regional—even global—VoIP deployments.
Around the world, enterprise investment in VoIP is growing again. While the upside to relying on VoIP technology is significant (lower cost, greater control, greater flexibility), the downside for large organizations is the potential complexity of the infrastructure and the management challenge that it creates, particularly in the area of quality of service. While many VoIP component vendors provide some monitoring and management tools, many of these tools are not up to the task of monitoring and managing complex, heterogeneous networks and ensuring high call quality across a large distributed VoIP environment.
"We have designed the distributed edition of VQManager using specifications culled from mid-sized and large enterprises that have expressed a need for better tools to monitor VoIP quality across geographical locations," said Sridhar Iyengar, VP, Product Management at ManageEngine. "The distributed edition of VQManager uses remote network probes that interact with the central server to keep administrators apprised of network conditions and call quality throughout the infrastructure. This makes it much easier to monitor and maintain VoIP services in larger, distributed environments. It's a simple, elegant and cost-effective way to ensure call quality and network health."
VQManager is web-based, real-time VoIP quality monitoring software that can interact with any VoIP equipment that supports SIP, H.323, Cisco SCCP (Skinny) or RTP/RTCP. It aids in troubleshooting VoIP calls for failures and quality deterioration. When VQManager detects a performance threshold violation, it generates an alarm and notifies VoIP system administrators, who can use the software to identify and isolate the root cause of the problem. More than 25 comprehensive built-in and customizable reports help in analyzing and optimizing the VoIP infrastructure.
The flexible central server and remote probe architecture enables VQManager to monitor thousands of calls located across geographically-distributed sites. The central server provides a consolidated view of the data from all sites; it also enables administrators to view data segregated on a site-by-site basis. Reports and alarms can be generated by each site. The site filter provided in the central server web console offers a bird’s-eye view of the VoIP infrastructure within a particular site. Historical reports can also be generated by using the date filter to select a specific timeframe, making further quality trend analysis possible.
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 ...