---
title: Designing a Staff-Level Global Architecture for 30 Million Distributed Users with Regional Kubernetes, Global Routing, and Multi-Region Databases
created: 2026-03-17
updated: 2026-03-17
type: summary
tags: ["architecture", "distributed", "kubernetes", "notes", "telegram"]
external: http://go/ui/posts/2192/
---

Designing for 30 million geographically distributed users is a classic Staff-level architecture challenge. The most critical correction to make upfront is regarding the Kubernetes architecture: **You should almost never run a single Kubernetes cluster stretched globally.** Here is the breakdown of why that is, and the better architectural design to handle this scale.

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## 1. The Compute Layer: Why Independent Clusters?
Kubernetes relies on `etcd` as its brain, and `etcd` requires strict quorum consensus to operate. It is highly sensitive to latency. If you stretched a single control plane from the US to where you are in Australia, the network latency would cause `etcd` to constantly time out and drop leader election, effectively crashing your cluster.

**The Better Design: "Cluster per Region"**
* Deploy completely independent Kubernetes clusters in your three regions (e.g., one GKE/EKS cluster in US-East, one in EU-West, one in APAC-Southeast).
* Treat these clusters as ephemeral, stateless compute pools. 
* Use a GitOps tool (like ArgoCD or Flux) to ensure the exact same manifests and configurations are deployed to all three clusters simultaneously.

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## 2. The Edge Layer: Global Routing
To make three distinct clusters feel like a single application to your users, you need a smart global routing layer.

* **Global Anycast IP:** Use a Global Load Balancer (like Google Cloud Global HTTP(S) LB or AWS Global Accelerator). This gives you a single static IP address for all 30 million users.
* **Geoproximity Routing:** The Anycast network automatically routes the user’s TCP/TLS handshake to the closest edge node. An APAC user is routed to the APAC cluster, minimizing latency.
* **Failover:** If the entire EU cluster goes down, the Global LB simply stops advertising that route and automatically shifts EU traffic to the US or APAC clusters.



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## 3. The Data Layer: The Hardest Problem
Compute is easy to distribute; state is hard. A "multi-region DB" is absolutely required, but you have two distinct paths depending on your exact requirements.

### Option A: Distributed SQL (The Modern Standard)
If you need relational data, ACID transactions, and strong consistency globally, traditional master-replica databases (like single-writer Postgres) will bottleneck.
* **The Tech:** Use **Google Cloud Spanner** or **CockroachDB**. 
* **How it works:** These are built from the ground up to be distributed globally. They use atomic clocks (TrueTime) or consensus algorithms (Raft) to allow "active-active" reads and writes across the globe. 
* **The GDPR Advantage:** With 10 million EU users, you have strict data sovereignty laws. Both Spanner and CockroachDB allow **Row-Level Geo-Partitioning**. You can configure the database so that rows belonging to EU users are physically stored only on EU nodes, while US data stays in the US, all within the same logical database table.



### Option B: Asynchronous NoSQL (The High-Throughput Alternative)
If your application is less concerned with strict financial-grade consistency and more concerned with absolute lowest latency and high availability (e.g., a social media feed or telemetry data).
* **The Tech:** **Apache Cassandra** or **DynamoDB Global Tables**.
* **How it works:** You write to your local region, and the database asynchronously replicates the data to the other two regions in the background. It provides *eventual consistency*.

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## 4. The Final Architecture
A robust, Staff-level design for this scenario looks like this:

1.  **User -> DNS/CDN -> Global Anycast Load Balancer**
2.  **Load Balancer -> Nearest Healthy Regional K8s Cluster (US, EU, or APAC)**
3.  **K8s Cluster (Stateless Microservices) -> Local Node of the Global Database**
4.  **Global Database (Spanner/CockroachDB) -> Handles cross-region replication and data sovereignty behind the scenes.**

### Next Step
Would you like to dive deeper into how to handle **schema migrations** across a globally distributed database without taking downtime, or would you prefer to explore how to set up **ArgoCD** to synchronize deployments across those three separate regional clusters?
