Corvil announced the general availability of its new Corvil Enterprise Monitoring System.
The new solution is based on its flagship CorvilNet platform and delivers the same powerful combination of high speed data capture, distributed transaction-application-network monitoring, and real-time business analysis.
New enterprise application transaction monitoring and an enterprise-reporting module are now included to support a broad range enterprise IT activities.
Key Benefits of the Enterprise Monitoring System:
- Visibility: Corvil has transformed how enterprise IT can monitor and deliver low latency applications and high performance networks, with integrated visibility between applications, transactions, and network performance, on one platform.
- High Velocity Data: Corvil captures all IT data “on the wire” and uses various stages of data transformation, structuring and analysis to turn this into valuable analytics that fuel business performance; for example in the rollout of a new high performance WAN, or data center.
- Expertise: Corvil’s real-time, deep analysis capabilities and insight provide IT with the expertise necessary to successfully deliver IT systems and services to the business.
Donal O’Sullivan, VP of Product Management at Corvil says, “The enterprise application environment is starting to look increasingly like what we deal with in the world of electronic trading – faster networks, more data, lower latency. And the link between IT performance and successful business outcomes is just as strong. If you couple this with the desire in 2013 to consolidate IT systems, it’s quite natural that there is a strong demand for the type of integrated monitoring system that Corvil provides and has proven so successful in financial markets.”
“In 2013 businesses must grow. Achieving a strong alignment of IT and business is a challenge but key to delivering growth for global enterprises. Corvil’s new Enterprise Monitoring Solution is architected in a manner that fosters greater collaboration and understanding between IT and the business as they look to leverage new applications, technologies and data to achieve this”, added O’Sullivan.
The Enterprise Monitoring System is available immediately.
The Latest
In MEAN TIME TO INSIGHT Episode 14, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses hybrid multi-cloud network observability...
While companies adopt AI at a record pace, they also face the challenge of finding a smart and scalable way to manage its rapidly growing costs. This requires balancing the massive possibilities inherent in AI with the need to control cloud costs, aim for long-term profitability and optimize spending ...
Telecommunications is expanding at an unprecedented pace ... But progress brings complexity. As WanAware's 2025 Telecom Observability Benchmark Report reveals, many operators are discovering that modernization requires more than physical build outs and CapEx — it also demands the tools and insights to manage, secure, and optimize this fast-growing infrastructure in real time ...
As businesses increasingly rely on high-performance applications to deliver seamless user experiences, the demand for fast, reliable, and scalable data storage systems has never been greater. Redis — an open-source, in-memory data structure store — has emerged as a popular choice for use cases ranging from caching to real-time analytics. But with great performance comes the need for vigilant monitoring ...
Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...
AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...
Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...
A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...
IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...
A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra ...