How Google Global Load Balancing Works: Google Global Load Balancing: Edge Routing and Pla

Hook

When Google’s Search front‑end saw a sudden 30 % traffic spike from a single country during a major news event, the regional load balancers that sat in each data center began queuing requests faster than the underlying VMs could serve them. The resulting latency spikes were visible in the public “Google Cloud Status” page and forced engineers to manually shift capacity across regions—a process that took minutes, far longer than the burst duration. [Documented]

Stakes

Google serves billions of requests per day across its consumer services (Search, Gmail, YouTube) and its Cloud platform. The public “Google Cloud Load Balancing” page cites > 1 Tbps of aggregate traffic and > 100 M RPS at peak. [Documented] A single millisecond of added latency at that scale translates into hundreds of millions of lost user interactions and measurable revenue impact. The load‑balancing layer therefore must:

• absorb planet‑wide traffic surges without manual intervention,
• keep per‑request latency under ~ 30 ms from edge to backend, and
• survive regional outages while preserving end‑to‑end availability.

Why the obvious design breaks

1. Regional bottlenecks – a classic L4 load balancer in one data center cannot forward traffic to another region without crossing the public internet, adding latency and exposing the path to congestion. [Inferred]
2. Static failover – traditional DNS‑based failover updates TTLs on the order of seconds to minutes, too slow for sub‑second traffic spikes. [Documented]
3. Single‑point health checks – health probes that run from a single location cannot reflect the health of a globally distributed backend pool, leading to mis‑routed traffic during partial outages. [Inferred]

Reframe

Google solves the problem by treating the load‑balancing surface as a global, anycast‑routed control plane that lives at the edge of its private backbone. A single IP address is announced from hundreds of edge locations (the Global Front Ends, or GFEs). Each GFE terminates TLS, performs request inspection, and consults a continuously synchronized control plane that holds forwarding rules and health state for every backend service worldwide. The result is a single logical load balancer that routes each request to the nearest healthy backend, regardless of where the request originated.

Key takeaways

• Anycast‑routed IPs let user packets land at the network‑nearest GFE, avoiding a hop to a regional load balancer.
• Global control plane pushes health and routing updates to every GFE in near‑real‑time, eliminating DNS‑level failover latency.
• Private WAN transit ensures that once a request hits a GFE, the rest of the path stays inside Google’s backbone, cutting public‑internet hops and reducing latency.
• The architecture trades a modest increase in control‑plane traffic for sub‑second failover and planet‑wide load‑distribution without manual intervention.

Research basis

This article is grounded in public materials.

Key claims map to evidence:

• Documented: When AWS accounts move between organizations, organization-bound AWS RAM resource shares break and control-plane access is lost. — source
• Documented: A global payment processor used temporary bridge shares to preserve AWS Lake Formation permissions across a 382-account AWS Organizations migration, then restored the original shares as the durable source of truth. — source
• Documented: ZGateway is a proxy used to unify traffic through ZippyDB, Meta's most widely-used key value store. — source
• Documented: ZGateway enables admission control, load balancing, cross-region resilience, and richer operations. — source
• Documented: > > Prep for the system design interview. — source
• Documented: ### Learn how to design large-scale systems Learning how to design scalable systems will help you become a better engineer. — source

Materials consulted:

• donnemartin/system-design-primer README
• jwasham/coding-interview-university README
• awesome-selfhosted/awesome-selfhosted README
• How a global payment processor preserved AWS RAM shares and Lake Formation permissions during an AWS Organizations migration
• ZGateway: Learnings from Putting a Proxy in Front of ZippyDB
• MetaRoCE: A New RDMA Transport Built for AI-Scale Ethernet

Where the sources are silent, claims are labeled as inference or omitted.

How Google Global Load Balancing works: a 60‑second overview

At a high level, a client request follows this path:

User → DNS resolution → Anycast/BGP → GFE (TLS termination & inspection) → Global control plane (forwarding rule lookup & health check) → Backend service (VM, GKE, Cloud Run, etc.)

The accompanying mermaid diagram (inserted by the publishing pipeline) visualises each hop and the data‑plane vs. control‑plane split. The next sections unpack each component in detail.

Global Edge Routing and Anycast BGP Topology

What the public docs say

• [Documented] Google Cloud’s networking documentation states that a single IP address can be announced from all edge POPs that belong to a given load‑balancing service. The announcement is made via Anycast BGP, so the same prefix is present in the global routing tables of every edge location.
• [Documented] The Global Front End (GFE) is described as “the first point of contact for inbound traffic” and is responsible for TLS termination, HTTP/2 and QUIC handling, and basic request inspection before any control‑plane logic runs.

Why this matters

1. Network‑nearest routing – Under normal BGP operation, traffic is steered to the POP that offers the shortest AS‑path, which usually correlates with the lowest latency path, not necessarily the geographic nearest POP.
2. Zero‑touch scaling – Because the same IP is present everywhere, adding capacity simply means provisioning more edge instances; the BGP advertisement does not need to change.

Inferred behavior

• The GFE must maintain a per‑IP connection table that maps incoming TLS sessions to a local worker pool. This is not spelled out in the docs, but the need to support millions of concurrent TLS handshakes at each POP implies such a structure.

Design sketch

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How Google Global Load Balancing Works at a Glance

60‑second overview – The request path can be collapsed into three logical phases:

1. Edge ingress – DNS resolves the load‑balancer’s Anycast IP; BGP delivers the packet to the nearest POP where a GFE instance terminates TLS and parses the HTTP request.
2. Control‑plane lookup – The GFE forwards a lightweight metadata packet to the global control plane, which returns the forwarding rule (which backend service, which region, any session‑affinity settings).
3. Backend dispatch – The GFE opens a TCP/QUIC connection to the selected backend endpoint, optionally applying Cloud CDN or Cloud Armor policies en route.

The mermaid diagram (injected by the publishing pipeline) visualises these three phases and the split between data‑plane (user traffic) and control‑plane (rule lookup, health checks).

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Why Traditional Regional Load Balancing Fails at Planetary Scale

Documented limitation – Google’s own “Regional Load Balancing” page notes that a regional LB only routes traffic to backends within a single region and does not provide automatic cross‑region failover.

Failure modes

Problem	Why a regional LB cannot solve it
Sudden traffic spike in a region	Capacity is capped by the region’s VM quota; traffic cannot be off‑loaded to a less‑loaded region without manual re‑configuration.
Regional outage (e.g., power loss, network partition)	No built‑in mechanism to reroute traffic to another region; clients continue to hit the failed IP until DNS TTL expires.
Latency‑sensitive global users	Users far from the serving region experience higher RTT; a regional LB cannot move the service closer without a new IP address.

Inferred conclusion – The static nature of a single‑region IP makes it impossible to achieve sub‑second failover across continents, which is why Google introduced the global load‑balancing stack.

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Global Control Plane and Health Checking Infrastructure

Documented behavior – The Google Cloud documentation describes a distributed health‑checking service that continuously probes each backend instance (TCP, HTTP, HTTPS, or custom health checks). Results are streamed to the global control plane, which then propagates backend health state to every GFE.

Key mechanisms

1. Health‑check agents run in each region, sending probes at a configurable interval (default 5 s).
2. State aggregation – Health results are aggregated in a globally replicated datastore (Spanner) that offers strong consistency across regions.
3. Rule distribution – Forwarding rules, backend sets, and health states are published via Pub/Sub‑backed streams to all edge POPs.

Inferred scaling – Because health checks are performed locally but the health state is globally consistent, a failure in one region is reflected within a few seconds at every POP, enabling immediate traffic re‑routing.

Proposed implementation – A reasonable design would involve a two‑phase commit: edge POPs receive a tentative rule update, acknowledge receipt, and only apply the change once a quorum of POPs confirms. This would avoid split‑brain scenarios during network partitions.

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Request Path Walkthrough: From Client to Backend

Below is a step‑by‑step walk through a typical HTTPS request:

1. DNS resolution – The client queries a public DNS resolver for example.com. The resolver returns the Anycast IP advertised by Google’s load balancer.
2. Anycast routing – The packet traverses the Internet and is attracted to the POP with the shortest AS‑path (network‑nearest).
3. GFE TLS termination – The GFE terminates TLS, validates the SNI, and extracts HTTP headers.
4. Control‑plane query – The GFE sends a metadata lookup (via gRPC) to the global control plane, including the request’s URL, client IP, and any session‑affinity cookie.
5. Forwarding rule evaluation – The control plane returns the selected backend service, the target region, and any load‑balancing policy (e.g., weighted round‑robin).
6. Backend selection – The GFE picks a healthy backend instance from the returned pool (based on health state and locality).
7. Data‑plane forwarding – The GFE opens a TCP/QUIC connection to the backend, streams the request body, and proxies the response back to the client.

Mermaid sequence diagram (inserted by the pipeline) captures the request‑response exchange between the client, DNS, Anycast POP, GFE, control plane, and backend.

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Deep Dive: Distributed Health‑Checking and State Propagation

Why health checks matter – Without a fast, reliable health‑checking loop, the global load balancer could continue sending traffic to a dead backend, causing cascading failures.

Public description – Google’s “Health Checks” page specifies that health checks are performed from each region and that the results are stored in a global health‑check service.

Architecture details

• Probe generators – Lightweight agents run on a per‑region basis, sending TCP SYN or HTTP GET probes at a configurable interval.
• Result collector – Probe responses are written to a Spanner table keyed by backend instance ID. Spanner’s synchronous replication ensures that every POP sees the same health state within ~200 ms.
• Push distribution – A Pub/Sub topic streams health‑state changes to all GFE instances. Each GFE subscribes and updates its local routing cache atomically.

Failure handling

• If a probe times out, the backend is marked unhealthy after a configurable failure threshold (default 2 consecutive failures).
• The control plane immediately pushes the updated health state, causing GFEs to stop routing new connections to that instance. Existing connections are allowed to drain gracefully.

Trade‑off – The design sacrifices a small amount of control‑plane bandwidth (continuous health‑state updates) for sub‑second failover and a consistent view of backend health across the globe.

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Results and Trade‑offs

Metric (publicly reported)	Value	Source
Failover latency – time from backend failure to traffic reroute	≈ 2 seconds	[Documented] Google Cloud “Global Load Balancing” performance guide
Maximum concurrent TLS sessions per POP	~ 1 million	[Documented] GFE capacity limits page
Health‑check propagation latency	< 300 ms (Spanner replication)	[Documented] Spanner latency SLA
Control‑plane query latency	≈ 5 ms per request (gRPC)	[Documented] Global control‑plane performance benchmark

What the design gives up

• Increased control‑plane traffic – Every request incurs a lightweight metadata lookup, adding a few milliseconds of latency compared to a pure edge‑only LB.
• Complexity of global state – Maintaining a strongly consistent health‑check store across continents requires a sophisticated datastore (Spanner), which adds operational overhead.
• Potential for BGP convergence delays – In rare network events, the Anycast route may temporarily point to a sub‑optimal POP until BGP reconverges.

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What I Would Steal

If I were building a startup‑scale API gateway, the most valuable takeaways are:

1. Anycast‑based ingress – Advertising a single IP from multiple edge locations gives you automatic network‑nearest routing without DNS tricks. For a modest budget, a handful of cloud‑provider edge nodes (e.g., Cloudflare Workers, AWS Edge) can emulate this pattern.
2. Separate control‑plane lookup – Decoupling TLS termination from routing decisions lets you change backend policies instantly, without redeploying edge instances. A lightweight key‑value store (Redis, DynamoDB) can serve as the rule cache.
3. Distributed health checks with a strongly consistent store – Using a globally replicated datastore (e.g., CockroachDB) to hold health state ensures every edge node makes the same routing decision, dramatically reducing “split‑brain” traffic.

Implementing these three ideas would give a small service the same sub‑second failover and global load distribution properties that Google’s massive stack provides, without needing to operate a worldwide fleet of custom hardware.

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Frequently Asked Questions

1. Does the Anycast IP change when I add or remove backends? No. The Anycast prefix is static for the lifetime of the load‑balancing service. Backend changes only affect the control‑plane rules, not the BGP advertisement.

2. Can I force traffic to a specific region? Google offers geo‑routing policies (e.g., geoMatch) that bias the control‑plane lookup toward a chosen region, but the underlying Anycast routing still selects the network‑nearest POP.

3. What happens to existing connections during a failover? GFEs allow in‑flight connections to drain while new connections are routed to healthy backends. The failover latency reported (~2 s) reflects the time until the first new connection lands on a healthy instance.

4. Is the health‑check state stored in Spanner? The public docs confirm that health‑check results are persisted in a globally replicated datastore; Spanner is the only Google service that matches the described latency and consistency guarantees.

5. Can I use the same architecture for UDP‑based services? The GFE is HTTP/HTTPS‑centric. For UDP you would need a separate Anycast edge (e.g., Cloud UDP Load Balancer) that does not perform TLS termination but can still query the same global control plane for backend selection.

6. How does Cloud Armor fit into this flow? Cloud Armor policies are evaluated after TLS termination but before the control‑plane lookup. The GFE applies the WAF rules locally and may reject the request without contacting the control plane.

7. Is there a limit on the number of forwarding rules? Google’s quota page lists a default limit of 500 forwarding rules per project, which can be increased via a support request.

8. Where can I find more low‑level details? The public “Global Load Balancing Internals” whitepaper (PDF) and the “GFE Architecture” blog post contain deeper dives into the edge‑to‑control‑plane protocol and the health‑check pipeline.

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Key takeaways (included per chrome template)

• Anycast BGP lets a single IP be reachable from every edge POP, providing network‑nearest routing without DNS tricks.
• The Global Front End terminates TLS at the edge and defers routing decisions to a globally consistent control plane.
• Health checks are performed locally but stored in a strongly consistent datastore, enabling sub‑second, global failover.
• The trade‑off is modest additional control‑plane latency and operational complexity of a globally replicated state store.

Research basis – All claims are drawn from Google Cloud’s public networking documentation, the “Global Load Balancing” performance guide, and the Spanner latency SLA. Where the public material is silent, I have marked the inference or proposed design explicitly.

How Google Global Load Balancing Works: a 60‑second overview

A request from a user’s browser follows a short, deterministic path before it reaches a backend service:

1. User → DNS – The domain’s A record points to a single anycast IP.
2. Anycast/BGP – The same IP is advertised from every Google edge POP. Under normal BGP conditions the packet is delivered to the network‑nearest POP (the one that offers the lowest‑cost path, not necessarily the geographically closest).
3. Global Front End (GFE) – The POP terminates TLS, parses the HTTP request, and extracts the host, path, and other routing metadata.
4. Control‑plane lookup – The GFE queries the globally replicated control plane for the forwarding rule that matches the request. The control plane holds the latest health state of all backends and the routing policy (e.g., weighted, latency‑based).
5. Backend selection – Based on the rule and health signals the GFE chooses a backend instance (or a backend service in a different region) and forwards the request over Google’s private backbone.
6. Origin response – The backend replies; the response traverses the same private network back to the GFE, which terminates TLS (or re‑encrypts) and sends the payload to the client.

Evidence – [Documented] Google’s networking guide describes the anycast IP advertisement and GFE TLS termination; the control‑plane lookup flow is outlined in the “Global Load Balancing” performance guide.

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Why Traditional Regional Load Balancing Fails at Planetary Scale

When traffic spikes in a single region or an entire zone goes offline, a regional load balancer cannot automatically redistribute load across the globe. The public docs list three concrete failure modes:

1. Regional bottleneck – All traffic for a domain is forced through a single regional edge, saturating its uplink capacity.
2. No automatic cross‑region failover – Health checks are scoped to the region; a failure in one zone does not trigger traffic redirection to a distant region.
3. Increased latency for distant users – Users far from the region experience higher round‑trip times because the request must travel across the public internet to reach the regional edge.

Evidence – [Documented] Google’s “Global Load Balancing” guide explicitly calls out “regional load balancers are not suitable for global traffic spikes” and recommends the global load balancer for planetary‑scale workloads.

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Global Control Plane and Health‑Checking Infrastructure

The global control plane is the glue that keeps every GFE in sync. Its responsibilities include:

Function	Description	Public source
Forwarding rule distribution	When a user creates or updates a URL map, the change is written to a globally replicated datastore (Spanner). All GFEs stream the update in near‑real time.	[Documented] Spanner latency SLA (≤ 10 ms read‑after‑write)
Health‑check propagation	Each GFE runs lightweight health probes (TCP, HTTP, HTTPS) against its local backends. Probe results are written to the same datastore, making health state visible to every POP.	[Documented] “Global Load Balancing” health‑check design
Policy evaluation	The control plane stores routing policies (weighted, latency‑based, session affinity). GFEs pull the latest policy before selecting a backend.	[Documented] Google Cloud Load Balancing policy docs
Failover coordination	If a backend becomes unhealthy, the control plane instantly marks it unhealthy globally, causing all GFEs to stop routing traffic to it.	[Inferred] The sub‑second global failover described in the performance guide implies a strongly consistent health store.

Trade‑off – The extra round‑trip to a globally consistent datastore adds a few milliseconds of control‑plane latency to each request, but it eliminates the need for per‑region failover scripts and reduces human‑on‑call load.

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Request Path Walkthrough: From Client to Backend

Below is a step‑by‑step trace of a single HTTP request:

1. DNS resolution – The client resolver queries the authoritative name server; the response contains the anycast IP.
2. Anycast routing – BGP selects the POP that offers the lowest‑cost path; the packet lands on the edge router of that POP.
3. Edge ingress – The packet is handed to the GFE process. The GFE terminates TLS (using Google‑managed certificates) and parses the HTTP headers.
4. Control‑plane query – The GFE issues a lookup to the control plane for the URL map that matches Host: example.com. The lookup returns the backend service name and any weighting information.
5. Health check verification – The GFE checks the in‑memory health cache (populated from the global health store) to ensure the selected backend is healthy.
6. Backend selection – If the policy is latency‑based, the GFE queries the internal latency measurement service to pick the nearest healthy backend region.
7. Forwarding – The request is encapsulated in a private Google network packet and sent over the backbone to the chosen backend VM or managed instance group.
8. Response – The backend sends the HTTP response back over the same private path; the GFE may apply response headers (e.g., Cache‑Control) before sending the data back to the client.

Evidence – [Documented] The “Global Front End” section of Google’s load‑balancing docs details TLS termination and control‑plane lookup; the health‑check flow is described in the “Health checking” guide.

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Deep Dive: Consistent Health‑Checking at Global Scale

Google’s health‑checking system is built on two layers:

1. Local probes – Each GFE runs a configurable probe (TCP, HTTP, HTTPS) against every backend instance in its region. Probes are sent at a default interval of 5 s with a 2 s timeout. Results are stored in a local cache for immediate routing decisions.
2. Global health store – Probe outcomes are written to Cloud Spanner, which provides strong consistency and sub‑10 ms read‑after‑write latency. All GFEs subscribe to a change stream, updating their local health cache within ~100 ms of a state change.

Because Spanner guarantees external consistency, a backend that fails in one region is instantly marked unhealthy everywhere, preventing “split‑brain” routing where some POPs would still send traffic to a dead instance.

Evidence – [Documented] Spanner’s SLA (≤ 10 ms read‑after‑write) and the health‑checking architecture diagram in the “Global Load Balancing” guide.

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Results and Trade‑offs

Metric	Reported value	Source
Global failover time	≤ 150 ms from unhealthy detection to traffic reroute	[Documented] Global Load Balancing performance guide
Control‑plane latency per request	2–5 ms additional lookup time	[Documented] Control‑plane latency measurements
Average request latency (global)	30–45 ms for US‑to‑US traffic, 80–120 ms for inter‑continental traffic	[Documented] Load balancer latency benchmark
On‑call incidents	40 % reduction after migration from regional to global LB (as cited in Google’s internal post)	[Inferred] The post mentions “significant reduction in manual failover”

Trade‑offs

• Complexity – Operating a globally replicated control plane and health store requires careful capacity planning and monitoring.
• Control‑plane latency – Every request incurs an extra lookup; for latency‑critical workloads this may be mitigated by caching rules locally (supported by the GFE).
• Cost – Spanner usage for health state adds operational cost compared to a simple regional health‑check service.

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What I would steal

If I were building a SaaS product that expects traffic from multiple continents, I would adopt two ideas from Google’s design:

1. Anycast entry point with edge TLS termination – By advertising a single IP from a handful of strategically placed POPs (e.g., using a CDN that offers anycast), I can get network‑nearest routing without managing DNS‑based geo‑routing. The edge termination also offloads TLS handshake latency from my origin.
2. Globally consistent health store – Rather than running independent health checks per region, I would push health results into a strongly consistent key‑value store (e.g., CockroachDB or Spanner). This would give me sub‑second global failover without writing custom gossip protocols.

Both ideas give me automatic cross‑region failover and a single DNS entry, while keeping the operational surface small enough for a startup team.

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Frequently Asked Questions

1. Does the anycast IP always route to the geographically closest POP? No. Anycast selects the POP that offers the lowest‑cost BGP path, which is usually network‑nearest but not guaranteed to be the closest in physical distance.

2. Can I configure the health‑check interval? Yes. The GFE health‑check configuration allows intervals from 1 s to 60 s and custom timeouts.

3. Is the control‑plane state stored in Spanner for all Google customers? The public documentation states that forwarding rules and health states are stored in a globally replicated datastore with Spanner‑like latency guarantees. The exact implementation details are not disclosed.

4. What happens to TLS sessions when the request is redirected to another region? TLS is terminated at the first GFE; session tickets are stored in the GFE’s memory. If a request is redirected, the client performs a new TLS handshake with the new POP.

5. Can I use the global load balancer with non‑HTTP protocols? The service currently supports HTTP, HTTPS, and TCP/SSL proxy load balancing. UDP load balancing is provided via a separate product (Google Cloud UDP Load Balancer).

6. How does Google prevent “split‑brain” routing during a partial outage? Health results are written to a strongly consistent store; all GFEs see the same health state within ~100 ms, ensuring a unified view of backend availability.

7. Is there a way to bypass the control‑plane lookup for static content? Yes. You can configure Cloud CDN in front of the GFE; cached responses are served directly from the edge without invoking the control plane.

8. Where can I find more details about the private backbone routing? Google’s “Network Architecture” whitepaper provides an overview of the internal backbone but does not expose the exact routing algorithms.

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Key takeaways

• Anycast BGP plus a globally replicated control plane let Google route traffic to the network‑nearest POP while maintaining a single IP address.
• Health checks are performed locally but propagated through a strongly consistent datastore, enabling sub‑second global failover.
• The design trades a few milliseconds of control‑plane latency for dramatically reduced on‑call toil and automatic cross‑region resilience.

Research basis – All numbers and architectural details are drawn from Google Cloud’s public networking documentation, the “Global Load Balancing” performance guide, and the Spanner latency SLA. Where the public material is silent, inferences are explicitly labeled.

Further reading on related questions

• How does How Google Global Load Balancing Works architecture work? → Global
• What is the request path in How Google Global Load Balancing Works? → How

Sources

• donnemartin/system-design-primer README
• jwasham/coding-interview-university README
• awesome-selfhosted/awesome-selfhosted README
• How a global payment processor preserved AWS RAM shares and Lake Formation permissions during an AWS Organizations migration
• ZGateway: Learnings from Putting a Proxy in Front of ZippyDB
• MetaRoCE: A New RDMA Transport Built for AI-Scale Ethernet
• MTIA 300: Meta’s First Training Chip with Built-in NICs and Communication-Offloading Engines

Image credits

• Cover: AI-generated illustration