FTAS 4.1: AI Factory Automation, Expanded FMCLI Coverage, and Large-Scale Validation


We’re excited to announce FTAS 4.1. This release adds 142 new test cases and brings the framework to

1,072 test cases in total. Its headline feature is automated validation for AI Factory fabrics.

Spotlight: AI Factory (N-S) automation

FTAS 4.1 adds an ordered 39-case AI Factory test plan that checks the full ONES-driven fabric lifecycle:

  • Design and planning: fabric types, scalable units, tenancy modes and network planes.

  • Deployment and onboarding: fabric deployment and tenant orchestration.

  • Control-plane parity: ONES API inventory compared with the switch CLI.

  • Data-plane proof: Ixia traffic across the deployed fabric.

By the numbers

CategoryTotal
SONiC Framework599
FMCLI188
Telemetry285
Total FTAS test cases1072

What else is new

  • FTAS with FMCLI: 54 new test cases bring FMCLI coverage to 188.

  • BGP convergence at IPv6 scale: 18 tests at 32k, 64k and 128k routes.

  • L3VNI multi-tenancy: 12 tests cover 3 VRFs with 128 VLANs.

  • BFD session scale: 4 tests with 64 and 128 sessions.

  • ACL loader (CONFIG_DB): 6 tests cover incremental update and switchover.

Conclusion

With 142 new test cases, a 39-case AI Factory test plan and expanded FMCLI coverage, FTAS 4.1

brings the framework to 1,072 test cases in total.

Reference:
Read the full release on the Aviz Networks blog

FTAS 4.1: AI Factory Automation, Expanded FMCLI Coverage, and Large-Scale Validation

Comments

Post a Comment

Popular posts from this blog

Scaling Deep Network Observability for 5G: Reflections from a Real Deployment

Image
  I recently went through a detailed implementation showing how deep network observability enhances 5G mobile user experience while reducing operational complexity. What stood out was how grounded the deployment was in real traffic and production-scale constraints. Some practical observations: • Fragmented systems increase cost and operational overhead • Frequent infrastructure upgrades create instability and repair expenses • Optimised filtering significantly reduces DPI hardware requirements • Real-time KPI computation improves SLA monitoring and service assurance • Standardised data export through streaming pipelines simplifies integration One misconception addressed during the walkthrough was that deeper observability automatically means more hardware. In reality, efficient filtering and intelligent packet processing reduce hardware footprint while improving performance. My biggest takeaway is that scalable observability in 5G environments requires architectural efficiency,...
Read more

How Network Copilot Uses Agentic AI to Correlate FortiGate and Splunk

Image
I recently went through a detailed implementation explaining how Network Copilot correlates FortiGate firewall telemetry with operational data indexed in Splunk . What stood out was how grounded the discussion was in real operational workflows rather than theoretical AI claims. Some practical observations: • Network and security logs are typically distributed across multiple platforms • Troubleshooting often requires manually correlating events between systems • Network Copilot ingests metrics, events, logs, and traces from firewall environments • Operators can interact with the system using natural language questions • Explainable root cause analysis improves operational confidence One misconception addressed during the walkthrough was that AI in operations means replacing engineers. In reality, the system augments teams by surfacing insights faster and correlating information across environments. Another interesting point was how the platform learns from real firewall deployments...
Read more

Evolving Packet Brokering for Modern Network Observability

Image
  I recently reviewed a technical overview describing how packet brokering platforms are evolving to support large-scale observability in modern data centers and service provider networks. The discussion focused on scalability, automated deployment, and operational efficiency. Some practical observations: • Network visibility platforms are expanding support for 400G switching hardware used in modern data center fabrics • GRE encapsulation enables mirrored traffic to move across Layer-3 networks while preserving packet metadata • Zero-Touch Provisioning simplifies onboarding for new or factory-reset switches • Packet brokers aggregate traffic from TAPs and SPAN ports and apply filtering and distribution policies • CLI improvements help operators manage large monitoring environments more efficiently One notable element was how GRE tunneling extends observability beyond Layer-2 boundaries. By encapsulating mirrored traffic into GRE tunnels, monitoring systems can receive full packet c...
Read more