NFD36: Aviz Delivers Observability
Aviz provides SONiC expertise, AI expertise, and has solid experience at Platform Integration, and Network Visibility / Observability.
Aviz products include Network CopilotTM (GenAI), Open Networking Enterprise Suite, Open Packet Broker, Service Nodes, and Fabric Test Automation Suite.
This particular set of technical skills says to me their likely customer is large enterprises and service providers.
Concerning AI, Aviz describes their skills as AI built into Networks and Networks built for AI computation.
Their two presentations at NFD36 focused on the Service Nodes and Packet Broker components, and a Japanese customer success story.
Packet Broker
Aviz’s Open Packet Broker (OPB) provides network traffic monitoring, and runs on SONiC NOS (Network Operating System). It leverages programmable ASICs for efficiency.
OPB is used for “advanced” security, analytics, and compliance network management tasks. It is intended for use in high-volume enterprise and telco networks, providing visibility and other data for 4G, 5G, and datacenter networks.
Service Nodes
A Service Node is a server appliance running AI Copilot. It produces management statistics from the packet data the Packet Broker provides.
Aviz previously provided this as an Operations product, and now have it for Network Visibility. The Service Node digests data from the Aviz or other packet brokers in a customer network. It then produces optimized summary information about the packet traffic in the network.
The Service Node is typically deployed as one or two devices on-premises, for security. The customer’s data thus stays onsite.
The Service Nodes produce metadata and insert that into a data lake. AI then consumes that metadata.
Analytics
For analytics about networks, Aviz computes top talkers and other flow data.
For telcos, Aviz correlates control and data plane flows to provide data about each phone call/conversation, especially information for mobile operators.
Researching “GTP” from my terse notes, I found this on their website:
“Provide essential metadata extraction for 4G-LTE, 5G-NSA, and 5G-SA, offering deep insights across network types. Specializing in correlation analysis, it uses protocols like S11 (GTP-C), S1-U (GTP-U) for LTE/5G-NSA, and N4 (PFCP), N3 (GTP-U), enhanced with N11 (SBI-HTTP2) correlations for comprehensive network analytics.”
In other words, specialized standard-compliant data for mobile operators.
Some of my other notes indicate Aviz runs micro services on physical Nvidia hardware, on-premises. Processed data can be (is) exported to Grafana for graphing.
Customer Reference
The second part of the Aviz presentations covered work Aviz did for a Japanese telco.
The telco had mobility network growth with increasing complexity. Also increased requirements. The Aviz solution improved performance and costs. It was perhaps 1/2 price of competitor offerings. The architecture cut traffic about 90%. This prepared the provider for advanced 5G and 6G, with larger networks and capacity and greater complexity. They noted that due to aging of the overall Japanese population mix, staffing is a real challenge there, meaning AI is a strong requirement.
Aviz also noted that Japan has very strong quality requirements, and they believe this could help them win more U.S. providers as customers.
For more information see the second Aviz presentation.
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About Aviz
Aviz has about 1400 customers. It does most R&D in India, has operations in Japan, has a U.S. presence, and is expanding slowly into the EU. Cisco is one of their investors, and Broadcom and Nvidia are partners.
The company’s products are available via channel or direct sales. Aviz has a ready-to-go server with AI installed. With channel, a potential customer can be shipped a device to try out NetOps and automation.
Aviz also offers a subscription model, with pricing computed from a base license and use cases.
Links
AvizNetworks home page:
Tech Field Day links:
NFD36 Delegate blogs already posted:
Fellow delegate Scott Robohn recommended the following 5G primer (thanks, Scott!):
Miscellany
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