Within the fast-paced world of community infrastructure, few applied sciences have confirmed as transformative as Phase Routing over IPv6 (SRv6). What began as a method to simplify service supplier networks and assist 5G rollouts has now change into vital for dealing with right now’s most difficult synthetic intelligence (AI) workloads. This thrilling evolution—from overcoming conventional networking challenges to driving cutting-edge AI networks—showcases not solely the outstanding flexibility of SRv6 but in addition its pivotal function in redefining the way forward for community structure. As we embrace this new frontier, SRv6 stands on the forefront, enabling improvements that may form the way in which we design AI infrastructures.
The genesis of SRv6: A quest for community simplification
Since 2012, Cisco has been on the forefront of pioneering Phase Routing, serving to pave the way in which for SRv6, which started to take form round 2016. This period marked a pivotal second within the trade because it acknowledged the pressing want for a extra agile and programmable community infrastructure able to accommodating the calls for of rising applied sciences corresponding to 5G, Web of Issues (IoT), and cloud companies. The SRv6 community programming mannequin was first launched on the Web Engineering Job Power (IETF) in March 2017, heralding the onset of an ecosystem that has since expanded quickly throughout varied industries.
A key driver behind SRv6 was the aspiration to simplify community operations by harnessing the inherent capabilities of IPv6. In distinction to its predecessor, Phase Routing Multiprotocol Label Switching (SR-MPLS), which nonetheless trusted the MPLS knowledge aircraft, SRv6 sought to function solely inside the IPv6 framework, thereby eliminating the complexities related to multiprotocol environments.
Cisco performed a key function within the early growth of SRv6 by selling its standardization on the IETF. This effort resulted in vital requirements corresponding to RFC 8402 (Phase Routing Structure), RFC 8754 (Phase Routing Header), and RFC 8986 (SRv6 Community Programming), which established the inspiration for the expertise. In 2019, Cisco launched the idea of SRv6 uSID (microsegment), enabling large-scale deployments whereas guaranteeing compatibility with older tools.
SRv6 and the 5G revolution
The preliminary driver for SRv6 adoption was clear: The telecommunications trade wanted an answer that might meet the stringent necessities of 5G networks. Conventional mobility administration executed by way of GPRS Tunneling Protocol (GTP) created advanced overlay tunneling architectures that didn’t scale to 5G necessities—elevated numbers of linked units, ultra-low latency calls for, community slicing capabilities, and cellular edge computing. The third Era Partnership Mission (3GPP) formally initiated a research merchandise titled “Examine on Consumer Aircraft Protocol in 5GC” to hunt potential candidates for the following user-plane protocol, with SRv6 rising as a compelling different.
What made SRv6 significantly enticing for 5G was its capability to simplify the community stack whereas enhancing capabilities. By leveraging IPv6’s tackle area to offer community programmability, SRv6 enabled operators to compose knowledge paths within the end-to-end IPv6 layer, integrating site visitors engineering, VPNs, and repair chaining options with out the complexity of sustaining per-session tunnel states. Community assets—even wavelengths in dense wavelength division multiplexing (DWDM) techniques—may very well be represented as IPv6 addresses, permitting management planes to program knowledge paths that met particular utility necessities.
Fast adoption throughout service supplier networks
Main communications service suppliers (CSPs) have embraced SRv6 and lots of extra are contemplating doing so.
Determine 1: Throughout the globe, lots of of SRv6 tasks have been deployed or are within the testing or planning phases
These deployments display the pliability of SRv6 throughout varied functions:
- Simplified VPN companies: SRv6 makes it simpler to deploy and handle community companies like L3VPNs, even throughout completely different networks. Solely the entry and exit routers have to assist SRv6, whereas the primary routers can simply ahead normal IPv6 site visitors. This streamlines community operations and lowers overhead.
- Service perform chaining (SFC): SRv6 permits community features, like firewalls and cargo balancers, to be included immediately in routing paths. This implies you possibly can handle site visitors with out difficult further protocols.
- Visitors engineering (TE) and quick reroute (FRR): SRv6 offers community operators effective management over site visitors routes, serving to to satisfy efficiency objectives like low latency or bandwidth ensures.
- Operational simplicity and price discount: By utilizing solely the IPv6 framework, SRv6 minimizes the reliance on varied overlay protocols, leading to an easier community. This results in simpler troubleshooting and decrease operational prices.
- Enhanced scalability and aggregation: SRv6 makes use of the scalability of IPv6, making it potential to handle massive networks with fewer prefixes, which simplifies routing and boosts effectivity.
The AI infrastructure problem: A brand new frontier
As SRv6 expertise superior in service supplier networks, a big transformation was additionally happening in knowledge facilities. The fast development of AI—and particularly the rise of large-scale mannequin coaching—created networking calls for which can be basically completely different from conventional workloads. AI coaching workloads scale to unbelievable ranges, involving hundreds and even tens of hundreds of graphics processing items (GPUs) working concurrently. In contrast to conventional knowledge heart site visitors patterns, which include various and unbiased transactions, AI coaching workloads intensify the long-standing “elephant movement” problem. Whereas elephant flows have existed in large knowledge shuffles, IP storage, and high-performance computing (HPC), AI coaching creates demanding patterns: hundreds of tightly synchronized GPUs executing collective communication operations (all-reduce, all-gather) at each coaching step, producing large, simultaneous knowledge transfers the place any straggler delays your complete cluster.
This synchronized habits creates important challenges that conventional networking approaches battle to deal with:
- Bursty site visitors and congestion spikes: When hundreds of GPUs concurrently push knowledge alongside the identical paths, sudden, intense congestion spikes can happen. Whereas Specific Congestion Notification (ECN) stays vital for managing congestion reactively, with out proactive site visitors placement these mechanisms could be overwhelmed, doubtlessly inflicting head-of-line blocking that spreads congestion throughout the community.
- The “slowest packet” drawback: AI community efficiency is dictated by the slowest packet, not averages. When hundreds of GPUs await a single straggler packet, even slight latency will increase can considerably impression job completion time (JCT). Each microsecond and each dropped packet issues.
- Scale-across complexity: As AI infrastructure extends past particular person knowledge facilities, organizations face community area fragmentation, state scalability challenges at geographic scale, dynamic WAN situations, and operational complexity spanning a number of protocol domains.
SRv6 in AI: The pure evolution
The networking neighborhood acknowledged that the identical ideas that made SRv6 profitable in 5G networks—stateless operation, source-driven path management, and unified IPv6-based structure—might tackle AI infrastructure challenges.
Backend GPU cloth optimization employs varied congestion administration methods. Adaptive routing and flowlet load balancing are actively deployed at hyperscalers and neoclouds, offering dynamic site visitors distribution based mostly on real-time community situations. SRv6’s uSID affords another strategy by way of deterministic path placement for distant direct reminiscence entry (RDMA) site visitors. By utilizing a deep integration between AI workloads and SRv6, community interface controllers (NICs) can leverage supply routing to carry out stateless, predictable path placement—explicitly distributing site visitors from completely different sources throughout accessible paths. This deterministic strategy enhances reactive strategies corresponding to ECN by enabling proactive site visitors placement that may cut back the frequency and severity of congestion occasions. Moreover, SRv6’s express path encoding simplifies failure restoration: When congestion or failures come up, new paths could be encoded on the supply with out counting on distributed routing convergence, permitting for fast site visitors movement changes.
Moreover, within the realm of frontend community unification, AI frontend networks should deal with a wide range of site visitors sorts, together with massive checkpoint writes to distributed storage, telemetry streams, management aircraft messages, and consumer entry. Every of those site visitors sorts has distinctive efficiency necessities. SRv6 affords a unified framework for implementing high quality of service (QoS), safety insurance policies, and site visitors steering throughout each backend and frontend domains. This streamlining eliminates the complexity related to managing completely different coverage frameworks, permitting for higher effectivity in community administration.
Moreover, SRv6 facilitates scale-across structure enablement by eradicating the normal fragmentation between knowledge heart and WAN domains, which ends up in the creation of unified IPv6-based knowledge planes. Organizations can apply constant insurance policies for managing AI site visitors, whether or not it traverses native materials, frontend networks, or spans huge distances between knowledge facilities. With SRv6, a single section checklist can encode paths from supply GPUs by way of the whole infrastructure to vacation spot GPUs situated in distant knowledge facilities. In contrast to Useful resource Reservation Protocol Visitors Engineering (RSVP-TE) or Multiprotocol Label Switching Visitors Engineering (MPLS-TE), which rely on sustaining per-flow state on community units, SRv6 incorporates all routing directions immediately inside packet headers. This strategy eliminates state explosion, making it significantly helpful for scale-across eventualities.
Quite a few hyperscalers started innovatively utilizing SRv6 of their AI backend networks to offer fine-grained community path management, maximize community utilization, and ship glorious cloth resiliency. At Open Supply Summit Europe 2025, Cisco and Microsoft showcased how SRv6 in SONiC permits a variety of knowledge heart use circumstances together with AI backend.
The trail ahead
The journey of SRv6, from its origins in service supplier networks to its promising function in AI infrastructure, illustrates a basic fact: Robust architectural ideas transcend particular use circumstances. The stateless operations, source-driven management, and unified IPv6 framework that simplified 5G networks are the identical ideas that allow deterministic efficiency in AI materials and seamless connectivity throughout geographic boundaries.
As AI continues to develop—from single-cluster deployments to large-scale architectures spanning continents—the networking challenges will solely develop. Coaching classes that contain lots of of hundreds of GPUs distributed throughout a number of knowledge facilities will demand community infrastructure able to sustaining microsecond-level precision on a worldwide scale.
SRv6’s inherent flexibility and extensibility enable it to adapt to those altering wants. Its programmability permits the introduction of latest community features and site visitors engineering capabilities with out requiring basic architectural adjustments. As new AI communication patterns emerge, SRv6 supplies a strong networking basis to assist them.
The expertise that simplified 5G cellular networks, enabled community slicing, and streamlined service supplier operations is now the identical expertise guaranteeing that AI infrastructure can scale with out limits. Since its first demonstrations in 2017, SRv6 has confirmed itself not simply as a networking protocol however as a basic constructing block for the way forward for digital infrastructure. As organizations develop the following technology of AI techniques, SRv6 will function a robust but unobtrusive engine, serving to be certain that the community stays an enabler of innovation relatively than a bottleneck. The journey from 5G to AI is only the start; the structure is properly positioned for no matter comes subsequent.
