Gigamon 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 (AMI) transforms network traffic into trusted application context for security, observability, data, and AI workflows.
With support for AMI across up to 400 Gbps of network traffic and optimized packet delivery for up to 800 Gbps, the GigaVUE-GSA110 delivers high-capacity processing in a compact 1RU footprint. Its disaggregated architecture enables organizations to add GigaSMART processing capacity where it is needed and scale application intelligence and packet optimization as Hybrid AI and increasingly interconnected applications and AI agents place greater demands on network infrastructure.
Hybrid AI Raises the Stakes for Network and Security 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.
This shift toward Hybrid AI reflects a broader evolution in enterprise AI infrastructure. According to Gartner, in the report The Future of AI Infrastructure: Designing for Sovereignty, Cost Optimization, and Performance, “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. That includes visibility into sanctioned and unsanctioned AI activity, helping organizations identify shadow AI and strengthen governance across hybrid cloud infrastructure.
Extending the Deep Observability Pipeline for AI-Enabled Operations
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, enabling organizations to scale processing where it is needed across distributed environments.
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.
“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.”
Advancing Application Intelligence at Scale
Together, the new hardware and software capabilities enable organizations to add distributed GigaSMART processing capacity, scale application intelligence and packet optimization, and flexibly deliver trusted network-derived telemetry to downstream tools and platforms.
What Are the Key Capabilities?
- Distributed GigaSMART processing: Adds dedicated processing alongside existing GigaVUE TA Series and HC Series deployments, enabling organizations to scale GigaSMART applications where needed.
- 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, helping organizations scale visibility as traffic volumes grow.
- AI application visibility: AMI helps identify and classify GenAI and LLM application traffic, including shadow AI, providing trusted context to support AI governance.
- 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, Kafka, and existing workflows.
- Optimized HTTPS metadata: Consolidates two metadata records into a single unified record for HTTPS traffic, reducing metadata records for those flows by approximately 50 percent while preserving valuable application context.
Availability
The GigaVUE-GSA110 appliance and new Gigamon Application Metadata Intelligence (AMI) enhancements are available now.