Goliath Technologies announced the release of their new Goliath for VMware Horizon product suite.
This product provides a different approach to VMware Horizon monitoring that brings together VMware Horizon session data, end user experience, metrics from the underlying infrastructure, and proactive application availability monitoring into a single product and console. The result is a solution that delivers proactive anticipation, troubleshooting and prevention of end user experience issues.
Goliath Performance Monitor for VMware Horizon offers IT organizations a single console which provides visibility from the end user experience issues to system and network performance issues. The system tracks critical metrics through integration with the Blast & PCoIP protocols, logon duration, Application, Machine, and Host Performance – all in one view. The advantage of having this information in a single console and platform is that metrics are fully aligned and integrated to show correlation and isolate how performance or resource availability impacts end user experience.
“Goliath Performance Monitor is purpose-built to find and monitor common VMware Horizon and Infrastructure failure points in the most complex VMware Horizon environments,” said Raja Jadeja, SVP of Product Management, Goliath Technologies. “Our solution provides a single view of the entire end user experience. This encompasses the performance of their connection to the Horizon session as well as their logon duration — including a breakdown of each stage and policy, application, and machine performance. Previously, administrators needed to open multiple consoles and disparate modules to visualize key performance metrics from VMware vSphere and multiple versions of VMware Horizon. Goliath Performance Monitor provides administrators with a single, unified console to monitor and troubleshoot performance issues from the entire environment. Moreover, by having visibility into the other architectural components integrated together, the troubleshooting workflow presents correlated data in a clearly defined view, aligned by time to more quickly derive root cause.”
The Latest
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 ...
According to Gartner, Inc. the following six trends will shape the future of cloud over the next four years, ultimately resulting in new ways of working that are digital in nature and transformative in impact ...
2020 was the equivalent of a wedding with a top-shelf open bar. As businesses scrambled to adjust to remote work, digital transformation accelerated at breakneck speed. New software categories emerged overnight. Tech stacks ballooned with all sorts of SaaS apps solving ALL the problems — often with little oversight or long-term integration planning, and yes frequently a lot of duplicated functionality ... But now the music's faded. The lights are on. Everyone from the CIO to the CFO is checking the bill. Welcome to the Great SaaS Hangover ...
Regardless of OpenShift being a scalable and flexible software, it can be a pain to monitor since complete visibility into the underlying operations is not guaranteed ... To effectively monitor an OpenShift environment, IT administrators should focus on these five key elements and their associated metrics ...