
Zenoss expanded its Unified Communications monitoring capabilities by announcing a formal partnership with LayerX Technologies and launching UC Insight with Log Analytics, which is powered by LayerX’s AnalytiX software.
Unified Communications is a collection of applications enabling multichannel communications (instant messaging, email, voice and video) to traverse a common network, and provides users with a richly integrated ecosystem where contact and content are seamlessly shared.
With Unified Communications working in concert, business teams are able to collaborate with speed and efficiency. However, when Unified Communications solutions experience issues, organizations often grind to a halt as IT teams seek to restore Instant Messaging capabilities, troubleshoot dropped calls, or repair video conference and VOIP functionalities affected by jitter or other Quality of Service issues.
UC Insight with Log Analytics provides end-to-end monitoring across not only heterogeneous Unified Communications applications and systems, but infrastructure as well, delivering detailed call path analysis and Quality of Service readouts for all UC devices and tools.
“Organizations of all sizes are rapidly adopting Unified Communications platforms to increase team collaboration and productivity,” said Marcus MacNeill, Zenoss VP of Product Management. “UC Insight with Log Analytics offers extensive Quality of Service monitoring that helps our customers stay ahead of issues within their UC environment and uncover trends and patterns to optimize their communications services.”
UC Insight with Log Analytics displays all UC data under a single scalable architecture, correlated against performance thresholds and analyzed to determine anomalistic behavior. By combining this capability with the power of Zenoss Service Dynamics to automate remediation steps, incorporate detailed dashboards, and create reports, Zenoss provides a truly holistic approach to insuring UC environments constantly perform at their peak.
The platform itself is also extremely flexible with the ability to collect and index all types of data including Syslog, Proprietary Logs, Flow, RTCP, SDN Data, CMR/CDR, SQL Queries, SNMP, and more. Utilizing predefined rules and the powerful correlation engine at the heart of UC Insight with Log Analytics, users can extract, correlate, and take actions across the entire UC ecosystem. This data can then be graphed and analyzed to improve business performance.
“Forward-thinking enterprises have fully embraced Unified Communications as a key enabler for business productivity,” said Glenn Means, President of LayerX. “We are excited to partner with Zenoss to enable best-in-class Unified Communications monitoring and rich log analytics”.
The Latest
AI is becoming the operating system of the enterprise. It acts as an invisible coordination layer that understands intent, connects systems, and executes work across complex SaaS environments. Previously, employees had to click through multiple systems — CRM, ERP, support tools, collaboration platforms — to complete a single task. Now, instead of navigating each application manually, they can simply state what they need to accomplish ...
In 2026, the cost of downtime or an outage is no longer just a technical inconvenience; it's a $600 billion wake up call for global businesses. As our digital ecosystems become more interconnected, each touchpoint introduces new risks and multiplies the consequences when things go wrong. And the data is clear: aggregate downtime costs for Global 2,000 companies have surged 50% since 2024, reaching a staggering $600 billion ...
Deloitte found that 74% of enterprises expect to deploy agentic AI solutions in the next 24 months. However, the rush to deployment is outpacing foundational work, though. Only 21% of enterprises have fully formed agent governance models in place. The result? AI agents deployed without guidance or governance begin to function as fragmented islands of complexity ...
Cloud spending is no longer viewed as a passthrough IT expense, but as a strategic financial lever that directly impacts innovation capacity, profitability and enterprise resilience, according to the CFO Cloud Cost Optimization Report from Azul ...
As AI moves from generating responses to performing actions, the need for trust increases exponentially. And as organizations enlist AI agents for increasingly sophisticated business processes, trust is going to be the single most important theme for spurring adoption. What can organizations do to build trustworthy AI agents? ...
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 ...