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Aviz outlines limitations of incumbent network observability solutions and proposes software-first alternative

Source Decision Insights Coverage Published November 29, 2025 Companies 3
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3 companies named across 10 categories, one of 327 articles referencing Nvidia. Previous coverage: Aviz details network copilot's AI-driven insights for multi-vendor networks (Nov 2025).

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Network observability solutions have remained largely unchanged despite advances in technology, posing challenges for enterprises requiring scalable, adaptable, and interoperable monitoring systems. This stagnation limits the ability of IT leaders and security professionals to effectively oversee increasingly complex digital infrastructures.

Current limitations in network observability

Many established network observability tools continue to rely on dedicated hardware appliances, restricting scalability and responsiveness due to hardware refresh cycles. Additionally, the use of field-programmable gate arrays (FPGAs) for packet inspection persists despite advancements in commodity hardware capable of similar functions.

The market is also characterized by limited interoperability caused by vendor-specific solutions, which induce operational silos and reduce the flexibility to integrate diverse network environments. Furthermore, traditional pricing models based on ports, chassis, or feature toggles do not align with modern usage patterns, affecting cost efficiency.

Incorporation of artificial intelligence

Absent or minimal integration of Artificial Intelligence (AI) in many network observability tools has resulted in limited automation and intelligence capabilities. While enterprises have adopted AI for various infrastructure monitoring and security tasks, network observability platforms largely remain straightforward packet forwarding utilities without leveraging AI-driven insights.

Aviz's network observability architecture

Aviz proposes a software-centric network observability framework that operates independent of specialized hardware, utilizing the Data Plane Development Kit (DPDK) to run on standard CPUs. The platform enables multi-vendor packet brokering without vendor lock-in, accommodating diverse ecosystem components out of the box.

Performance can be enhanced with NVIDIA BlueField data processing units (DPUs) when necessary, allowing for intelligent scaling. The solution also features real-time AI connectivity through the TestWork Copilot, facilitating dynamic interaction between network data, analytic tools, and automated actions.

Deployment example and operational outcomes

One telecommunications company serving 30 million customers deployed Aviz's observability solution with data processing intervals of five seconds, delivering precise real-time network insights. This deployment resulted in an approximately 80% reduction in hardware footprint, lowering Capital Expenditure (CAPEX), energy use, and data center space requirements.

Operational expenditures also declined by roughly 50%, attributed to standardized tooling and automation enabled by the platform's design.

Considerations for legacy and modern observability solutions

Traditional network observability tools' hardware dependence, proprietary FPGA-based processing, constrained interoperability, and outdated pricing lead to inflexibility and higher costs in contemporary software-first, AI-enabled, multi-vendor network environments. Modern observability solutions favor software-defined architectures that run on commodity CPUs and smart network interface cards, enhancing scalability and adaptability.

Aviz's approach embodies this modern framework by combining open, multi-vendor support with AI integration, reducing the lock-in effects of legacy systems while supporting real-time network oversight and management.

This Blog Signals brief provides a factual summary of a vendor blog discussing challenges in traditional network observability and presenting an alternative platform designed to address these issues for enterprise technology decision-makers.

Blog post, originally published by Vishal Shukla at Aviz Networks.

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