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2T Ethernet Switch Enters Volume Production: What It Means for AI Cloud Deployments

The networking industry is in the middle of a rapid generational shift. As AI workloads push data centre fabrics to new throughput thresholds, Ethernet switch silicon and open-source network operating systems are

By xSONiC Team · · SONiCopen networkingdata centerAI fabricEthernet

The AI Networking Imperative: Why Switch Bandwidth Is Accelerating

Large-scale AI training and inference clusters demand deterministic, low-latency, high-throughput network fabrics. GPU-to-GPU communication patterns - particularly those using RDMA over Converged Ethernet (RoCE) - place enormous pressure on leaf-spine architectures to deliver consistent bandwidth at every tier.

The industry has been on a steep bandwidth-per-port ramp: 100G gave way to 400G, 400G is giving way to 800G, and switch ASIC total throughput has scaled from single-digit Terabits to tens of Terabits per second. NVIDIA’s Spectrum-4 SN5000 series, for example, delivers up to 51.2 Tb/s total throughput across 64 800GbE ports, purpose-built for deep-learning workloads. Edgecore’s DCS520 platform, built on Broadcom Tomahawk 4, provides 25.6 Tbps across 64 400G ports.

SONiC: The Open-Source NOS Powering the World’s Largest Cloud Networks

As switch hardware reaches new performance tiers, the software running on that hardware matters just as much. SONiC (Software for Open Networking in the Cloud) is an open-source network operating system based on Linux, originally developed for the data centres of some of the largest cloud service providers. It has since become a Linux Foundation project with a rapidly growing ecosystem.

Key architectural strengths of SONiC relevant to AI deployments:

  • Hardware-software decoupling: Built on the Switch Abstraction Interface (SAI), SONiC allows the same network OS to run on switches from multiple vendors and across different ASIC families. This gives cloud operators choice and negotiating leverage without rearchitecting their fabric.
  • Containerised, modular design: Each network function (BGP, RDMA, LLDP, etc.) runs in its own Docker container, enabling independent upgrades, faster debugging, and better fault isolation - critical when managing thousands of switches in an AI cluster.
  • Production-hardened at scale: SONiC has been battle-tested in the data centres of hyperscale cloud providers, supporting the full suite of networking functionality needed for AI workloads, including BGP and RDMA.
  • Standards-based: Uses standard Linux interfaces and tools, making it accessible to network engineers familiar with Linux operations.

For Australian organisations building or expanding AI infrastructure - whether hyperscale data centres, enterprise private clouds, or sovereign AI deployments - SONiC offers a path to avoid vendor lock-in while benefiting from community-driven innovation.

What ‘Volume Production’ Signals to the Market

When a new switch generation moves from sampling to volume production, several things change for the market:

  1. Supply normalisation: Volume production means consistent availability of both bare-metal switches and the underlying ASICs. Operators can plan deployments with confidence rather than managing scarce pre-production hardware.

  2. Price-per-bit improvements: As production scales, the cost economics of higher-bandwidth switching improve, making 2T-class economics accessible beyond just hyperscalers.

  3. Software ecosystem maturity: Volume production typically coincides with NOS support maturation. For SONiC-based deployments, this means tested integration, validated SAI implementations, and community-verified configurations.

  4. Australian market relevance: Australia’s growing investment in AI infrastructure - from government sovereign AI initiatives to hyperscale data centre expansions in Sydney and Melbourne - means local operators need access to the latest switching generations. Volume production availability de-risks procurement for Australian cloud and data centre providers.

The Open Networking Advantage for AI Cloud Operators

The convergence of high-bandwidth switch hardware and open-source NOS software creates a compelling value proposition:

For hyperscale operators: SONiC’s containerised architecture allows fine-grained control over networking services at massive scale. Operators can customise, optimise, and deploy network functions independently across thousands of switches.

For enterprise AI builders: Open networking eliminates the ‘NOS tax’ of proprietary switch software, redirecting budget toward compute (GPUs, accelerators) and storage - the resources that directly impact AI model training time.

For the Australian market: Open networking aligns with broader technology sovereignty objectives. SONiC’s open-source licensing (Apache 2.0) and multi-vendor hardware support give Australian operators flexibility to select the best hardware for their needs without being locked into a single vendor’s ecosystem.

Looking Ahead: From 2T to the Next Frontier

The entry of 2T-class Ethernet switches into volume production is one waypoint on a longer roadmap. The industry trajectory points toward:

  • Co-packaged optics: NVIDIA’s Spectrum-6 SN6000 series already introduces co-packaged silicon photonics networking, doubling bandwidth per lane compared to the previous generation and improving power efficiency and uptime for AI factories.
  • 800G and beyond: The shift from 400G to 800G per port is underway, with 1.6T on the horizon.
  • AI-native networking features: Beyond raw bandwidth, switch platforms are incorporating AI-specific features like zero-touch RoCE acceleration, enhanced congestion management, and digital twin simulation capabilities (e.g., NVIDIA DSX Air).

For Australian cloud operators and AI builders, the message is clear: the networking layer is no longer just plumbing - it’s a strategic differentiator for AI performance.

Sources Reviewed