Gigamon, a leader in deep observability, has announced new capabilities that extend the Gigamon Deep Observability Pipeline with distributed GigaSMART processing to support increasingly AI-enabled network and security operations. The new GigaVUE-GSA110 network appliance adds high-density processing capacity alongside existing Gigamon visibility infrastructure, while Gigamon Application Metadata Intelligence transforms network traffic into trusted application context.
Gigamon has launched the GigaVUE-GSA110 network appliance to extend the Deep Observability Pipeline with distributed GigaSMART processing.
The appliance supports AMI across up to 400 Gbps of network traffic and optimized packet delivery for up to 800 Gbps in a compact 1RU footprint.
Its disaggregated architecture lets organizations add GigaSMART processing capacity where needed.
Gigamon AMI helps identify and classify GenAI and LLM application traffic, including shadow AI.
Flexible telemetry delivery includes native JSON export and support for JSON, CEF and IPFIX.
The GigaVUE-GSA110 appliance and new AMI enhancements are available now.
"Hybrid AI and agentic workflows will fundamentally change how enterprises operate and secure increasingly distributed infrastructure," said Gareth Maclachlan, chief operating officer at Gigamon. "As network and security operations become more AI-enabled, they need consistent, trusted network context to analyze activity and make informed decisions. The GigaVUE-GSA110 extends the Deep Observability Pipeline with distributed processing capacity and application intelligence at scale, helping organizations investigate issues faster, strengthen governance, and build a stronger foundation for AI-enabled operations."
As enterprise AI evolves toward Hybrid AI architectures spanning frontier, open-weight, specialized, and private models, organizations will increasingly use different models and services across public cloud, private cloud, and on-premises infrastructure based on the performance, cost, security, governance, and data requirements of individual workloads.
According to Gartner, "By 2028, more than 50 percent of enterprises will use public cloud selectively for bursty or experimental workloads while anchoring performance- and sovereignty-sensitive AI workloads in private and localized environments."
Emerging Hybrid AI architectures create new operational challenges for security and IT teams. They need to understand not only what infrastructure is running, but how applications, workloads, services, users, agents, and models are interacting across it. Increasingly, AI-enabled network and security operations require consistent, trusted network context to analyze activity and support informed decisions.
The Gigamon Deep Observability Pipeline transforms network traffic into trusted network-derived telemetry, providing an independent view of activity across hybrid cloud infrastructure. The GigaVUE-GSA110 extends the pipeline with dedicated GigaSMART processing capacity that can be added alongside existing GigaVUE TA Series and HC Series deployments.
Within this architecture, optimized packet traffic can be delivered to packet-based tools while AMI-derived telemetry provides application and protocol context to security, observability, data, and AI platforms. AMI helps reveal application identity, relationships, dependencies, protocol behavior, and certificate activity, giving human operators and AI-enabled workflows trusted context to understand activity across the infrastructure.
Distributed GigaSMART processing: Adds dedicated processing alongside existing GigaVUE TA Series and HC Series deployments.
Greater application intelligence at scale: High-capacity processing in a compact 1RU footprint enables AMI processing across up to 400 Gbps of network traffic.
High-scale packet optimization: Supports optimized packet processing for up to 800 Gbps of network traffic.
AI application visibility: AMI helps identify and classify GenAI and LLM application traffic, including shadow AI.
Flexible telemetry delivery: Native JSON export and support for JSON, CEF, and IPFIX enable network-derived telemetry to be delivered to security, observability, data, and AI platforms.
Optimized HTTPS metadata: Consolidates two metadata records into a single unified record for HTTPS traffic, reducing metadata records by approximately 50 percent.
About Gigamon
Gigamon protects the hybrid cloud networks and data of the world's most complex organizations. The AI-powered Gigamon Deep Observability Pipeline delivers complete visibility into all data in motion by providing trusted, network-derived telemetry directly to cloud, security, and observability tools. Gigamon is trusted by over 4,000 organizations worldwide, including 83 of the Fortune 100, major mobile network operators, and public sector agencies at every level.
