Goliath Technologies has developed proactive end user experience monitoring and management technology to meet IT Operations teams’ need to replace Citrix EdgeSight and enhance Desktop Director as they upgrade to XenApp and XenDesktop 7.6
With 400,000 organizations deploying Citrix virtual desktop infrastructure solutions like XenApp and XenDesktop, for those upgrading to the new 7.6 version, there is a growing challenge to effectively manage the end user experience because Citrix EdgeSight is no longer available in 7.6 versions and Desktop Director has limited functionality.
To meet this challenge, Goliath Technologies has enhanced their Goliath Performance Monitor with features and functions that allow IT Operations teams to replace Citrix EdgeSight and enhance Desktop Director to proactively manage the entire Citrix end user experience.
“With EdgeSight going away and Desktop Director essentially a helpdesk tool, Goliath Performance Monitor passes the test as a viable EdgeSight replacement product. Features such as alerting, real-time and historical reporting and logon simulation make GPM a great EdgeSight replacement,” said Jacob Rutski, Citrix Engineer.
To help IT Operations teams work through the process of selecting an EdgeSight replacement and a Desktop Director enhancement product as they upgrade to XenApp/XenDesktop 7.6, Goliath has collaborated with Citrix Engineer Jacob Rutski, to offer a number of complimentary resources, such as an EdgeSight replacement feature-to-feature comparison guide.
The Latest
Outages aren't new. What's new is how quickly they spread across systems, vendors, regions and customer workflows. The moment that performance degrades, expectations escalate fast. In today's always-on environment, an outage isn't just a technical event. It's a trust event ...
Most organizations approach OpenTelemetry as a collection of individual tools they need to assemble from scratch. This view misses the bigger picture. OpenTelemetry is a complete telemetry framework with composable components that address specific problems at different stages of organizational maturity. You start with what you need today and adopt additional pieces as your observability practices evolve ...
One of the earliest lessons I learned from architecting throughput-heavy services is that simplicity wins repeatedly: fewer moving parts, loosely coupled execution (fewer synchronous calls), and precise timing metering. You want data and decisions to travel the shortest possible path. The goal is to build a system where every strategy and each line of code (contention is the key metric) complements the decision trees ...
As discussions around AI "autonomous coworkers" accelerate, many industry projections assume that agents will soon operate alongside human staff in making decisions, taking actions, and managing tasks with minimal oversight. But a growing number of critics (including some of the developers building these systems) argue that the industry still has a long way to go to be able to treat AI agents like fully trusted teammates ...
Enterprise AI has entered a transformational phase where, according to Digitate's recently released survey, Agentic AI and the Future of Enterprise IT, companies are moving beyond traditional automation toward Agentic AI systems designed to reason, adapt, and collaborate alongside human teams ...
The numbers back this urgency up. A recent Zapier survey shows that 92% of enterprises now treat AI as a top priority. Leaders want it, and teams are clamoring for it. But if you look closer at the operations of these companies, you see a different picture. The rollout is slow. The results are often delayed. There's a disconnect between what leaders want and what their technical infrastructure can handle ...
Kyndryl's 2025 Readiness Report revealed that 61% of global business and technology leaders report increasing pressure from boards and regulators to prove AI's ROI. As the technology evolves and expectations continue to rise, leaders are compelled to generate and prove impact before scaling further. This will lead to a decisive turning point in 2026 ...
Cloudflare's disruption illustrates how quickly a single provider's issue cascades into widespread exposure. Many organizations don't fully realize how tightly their systems are coupled to third party services, or how quickly availability and security concerns align when those services falter ... You can't avoid these dependencies, but you can understand them ...
If you work with AI, you know this story. A model performs during testing, looks great in early reviews, works perfectly in production and then slowly loses relevance after operating for a while. Everything on the surface looks perfect — pipelines are running, predictions or recommendations are error-free, data quality checks show green; yet outcomes don't meet the ground reality. This pattern often repeats across enterprise AI programs. Take for example, a mid-sized retail banking and wealth-management firm with heavy investments in AI-powered risk analytics, fraud detection and personalized credit-decisioning systems. The model worked well for a while, but transactions increased, so did false positives by 18% ...
Basic uptime is no longer the gold standard. By 2026, network monitoring must do more than report status, it must explain performance in a hybrid-first world. Networks are no longer just static support systems; they are agile, distributed architectures that sit at the very heart of the customer experience and the business outcomes ... The following five trends represent the new standard for network health, providing a blueprint for teams to move from reactive troubleshooting to a proactive, integrated future ...