
Goliath Technologies has acquired TransformaTech, a privately held company with offices in Exton, PA, providing monitoring as a service (MaaS) from the cloud for hosted and on-premise virtual and physical infrastructure.
“We have seen an increased demand for Monitoring as a Service, or MaaS as it is now called, especially from our customers who have deployed desktop virtualization solutions like XenApp, XenDesktop, and VMware View,” said Thomas Charlton, Chairman and CEO of Goliath Technologies. “The acquisition of TransformaTech will allow us to immediately offer MaaS to our customers because TransformaTech has the expertise, infrastructure, and business model in place to support customers such as the PA Department of Revenue, PMA Insurance, Cigna, Finish Line, Tire Kingdom, Fidelity, PayPal, and Amerigas.”
“We are very proud of our growth and profitability over the years. Identifying market trends early and reacting with technology solutions has always been a hallmark of our company and virtualization, cloud computing, and Monitoring as a Service were no exception,” said Bill Karounos, CEO of TransformaTech. “Now being part of Goliath Technologies, we will have additional resources and capabilities to realize our vision relative to offering MaaS to a larger base of customers.”
Bill Karounos will be transitioning to the Executive Team at Goliath Technologies as Vice President of Technical Operations. In this role, he will manage the entire customer experience from the first technical interaction through the purchase journey to ongoing support for both on-premise solutions and Monitoring as a Service in the cloud. All TransformaTech employees will join the Goliath Technologies team as well.
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 thirdparty 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 ...