Use Case

Zenera in Network Security Operations

Intelligent Assist for Broadcom Security Services Platform

Executive Summary

Network security operations teams face an impossible challenge: managing increasingly sophisticated threats across complex, distributed infrastructure—while documentation spans thousands of pages and platform APIs expose hundreds of methods. Security analysts spend more time searching documentation and writing scripts than actually defending the network.

Intelligent Assist, powered by Zenera, transforms this operational model. By combining intelligent knowledge retrieval with real-time code generation and live system correlation, it delivers instant answers and automated remediation—turning hours of manual work into seconds of natural language interaction.

"Production Results: Security teams report 100x productivity gains on routine operations—from policy cleanup scripts that previously took weeks completed in minutes, to troubleshooting workflows that compress multi-hour investigations into single queries."

How Intelligent Assist Works

Unlike simple chatbots that only retrieve documents, Intelligent Assist combines three deeply integrated capabilities:

Capability	Description
Knowledge-Grounded Q&A	Deep index of KB articles, reference designs, and official documentation—with version-aware retrieval tailored to the customer's environment
Real-Time API Code Generation	Understands 100–1000+ API methods per platform; translates natural language into validated Shell, Python, Ansible, or Terraform incorporating best-practice patterns
Live System Interrogation	Queries live telemetry, logs, and configuration state; correlates symptoms across infrastructure layers to identify root causes and guide remediation

"Security teams don't work in documentation portals. They work at the intersection of live infrastructure, evolving threats, and complex APIs. Intelligent Assist reasons natively across all three."

Why Traditional Approaches Fail in Security Operations

Challenge	Simple Chatbot / RAG Reality	Zenera Intelligent Assist
Version-specific guidance	Generic answers; ignores environment version	Version-aware retrieval scoped to customer's exact software release
100–1000+ API methods	Cannot reason over full API surface	Comprehends complete API documentation; generates validated, tested code
Live system correlation	Static answers from documentation only	Direct telemetry access; cross-layer correlation in real time
Script generation	Code snippets without error handling or best practices	Validated automation with rate limiting, logging, and dependency ordering
Multi-layer troubleshooting	Single-source answers; misses cross-layer root causes	Correlates 700+ telemetry points across virtual service, pool, network, and SE layers
Threat triage	Retrieves documents; cannot correlate with environment topology	Synthesizes threat intelligence with live topology and version-specific guidance

Use Cases

These use cases demonstrate how Zenera's agentic architecture transforms hours of manual work into minutes or seconds of intelligent assistance across vDefend (firewall) and AVI (load balancer) operations.

vDefend threat alert triage dashboard with context

Knowledge Assist — Triage of Sophisticated Threat Alerts

A high-severity IDS/IPS alert fires—"Cobalt Strike" activity detected. The analyst needs to understand the threat, assess impact, and determine response—immediately.

Security Analyst

ESX DFW memory anomaly analysis with root cause identification

Operator Assist — Real-Time Remediation of Resource Anomalies

A performance alert fires—DFW memory usage is elevated on a critical host. The administrator needs to understand root cause and remediation without manually parsing thousands of log lines and correlating across multiple data sources.

Security Administrator

Auto-generated Terraform policy cleanup script

Firewall-as-Code — Automated Policy Cleanup

After a project completes, stale security groups and rules need cleanup. Manually writing API scripts requires deep knowledge of the NSX Manager API (hundreds of methods), careful dependency ordering, robust error handling, and thorough testing.

Security Engineer / DevOps Engineer

AVI version-specific deployment checklist

Knowledge Insights — Version-Specific Deployment Guidance

Cloud-native migrations require precise configuration guidance—but documentation spans multiple versions with subtle but critical differences.

Network Architect

Multi-layer telemetry correlation identifying SNAT pool exhaustion

Assisted Troubleshooting — Root Cause Analysis for Application Failures

Users report connection failures on an internal application. The health score has dropped, but the root cause could be anywhere: virtual service configuration, pool health, SNAT pool exhaustion, Service Engine resource pressure, or upstream network issues.

Application Administrator

Terraform configuration for Private AI load balancer with AVI provider

Configuration-as-Code — Terraform Deployment for AI Workloads

A new Private AI workload requires a load balancer configuration with specific requirements: session persistence for stateful inference endpoints, extended timeouts for long-running model calls, connection multiplexing, and gradual traffic ramp for rolling deployment.

Site Reliability Engineer (SRE)

Production Impact Summary

Use Case	Traditional Time	With Intelligent Assist	Improvement
Threat alert triage	30–60 minutes	30 seconds	60–120x
Performance root cause	2–4 hours	45 seconds	160–320x
Terraform policy cleanup	1–2 weeks	2 minutes	500–1000x
Version-specific guidance	30+ minutes	15 seconds	120x
Multi-layer troubleshooting	2–4 hours	1 minute	120–240x
Terraform config generation	2–3 days	3 minutes	400–700x

Aggregate productivity gain: ~100x across routine security operations

Why This Works: Zenera's Approach

Intelligent Assist delivers these results through three deeply integrated capabilities that no simpler system can replicate:

Capability	What It Delivers
Deep Knowledge Integration	Comprehensive ingestion of official documentation, KBs, and reference architectures—with version-aware retrieval that ensures guidance matches the customer's actual environment. Continuously updated as documentation evolves.
Real-Time Code Generation	Comprehension of 100–1000+ API methods and data types per platform. Generated code follows best practices, includes proper error handling, and is validated against current API schemas to prevent runtime failures.
Live System Correlation	Direct telemetry access provides real-time infrastructure visibility. Cross-layer correlation identifies root causes that span infrastructure boundaries. Context-aware responses incorporate actual system state—not just documentation.

The Compounding Value

Each Intelligent Assist deployment creates reusable operational intelligence:

Threat triage responses become standing runbooks linked to your environment topology
Policy cleanup scripts become lifecycle management automation that runs on schedule
Troubleshooting analysis becomes automated health monitoring with pre-built remediation workflows
Configuration automation becomes a library of validated deployment patterns for new workloads

Traditional tools produce answers. Intelligent Assist produces capabilities.

Conclusion

Security operations teams are overwhelmed by sophisticated threats, complex distributed infrastructure, and documentation spanning thousands of pages. Traditional approaches—manual log analysis, documentation searches, custom scripting—don't scale to the pace of modern threats or the complexity of modern infrastructure.

Intelligent Assist transforms this model across three dimensions:

Knowledge that finds you: Relevant, version-aware guidance surfaced instantly—without documentation searches
Code that writes itself: Validated automation scripts from natural language—without deep API expertise
Troubleshooting that correlates: Multi-layer root cause analysis in seconds—without manual log parsing

For Broadcom Security Services Platform users, this translates to 100x productivity gains on routine operations—freeing security teams to focus on what matters: defending the enterprise against the threats that actually require human judgment.

*For technical architecture details, see the Zenera Capabilities Document.*

*For the enterprise AI adoption analysis, see From Tokens to Intelligence.*