The cloud is no longer a single-provider destination. Most organisations today run a combination of AWS, Azure, GCP, and sometimes on-premise data centres. What started as an accidental mix of platforms has now evolved into intentional multi-cloud strategy—driven by resilience, compliance, cost optimisation, and avoiding vendor lock-in.
But while multi-cloud enables flexibility, it also brings one of the biggest challenges in modern architecture:
Networking.
Connecting workloads across multiple clouds is not a trivial task. Each provider has its own:
- networking models
- routing behaviour
- DNS management
- security groups / firewalls
- native connectivity services
Multi-cloud networking is rarely about tools — it’s about understanding how each provider handles routing, DNS, security, and connectivity. The real challenge is achieving consistent behaviour across fundamentally different cloud architectures.
Building predictable, secure, and scalable connectivity across clouds requires deep planning and understanding of each provider’s behaviour. In this blog, we break down the essential concepts, connectivity patterns, and best practices for multi-cloud networking done right.
Although this blog references AWS, Azure and GCP together, the principles apply equally to any multi-cloud or hybrid cloud environment. Whether you are connecting AWS and Azure only, Azure and GCP, or extending workloads across cloud and on-premise environments, the same networking challenges appear — routing, DNS, security, IP planning and connectivity patterns. The core design patterns remain relevant regardless of how many cloud providers you use.
Why Multi-Cloud Networking is Hard
Before diving into solutions, it’s important to understand the difficulties.
1. Different Networking Constructs
AWS uses VPCs and subnets.
Azure uses VNets and subnets.
GCP uses global VPCs.
Prefix limits, route propagation, and firewall rules behave differently.
2. Security Model Variations
AWS Security Groups act statefully.
Azure NSGs are similar but attach differently.
GCP firewalls operate at VPC level.
3. Different Native Connectivity
- AWS has Transit Gateway, DX, PrivateLink
- Azure has vWAN, ExpressRoute, Private Link
- GCP has Cloud Router, HA VPN, Interconnect
Making them speak to each other is an art.
4. Overlapping IP Ranges
Many organisations reuse the same CIDR in different clouds — leading to painful conflicts.
5. Failing DNS Resolution
Cross-cloud private DNS resolution requires manual design or custom DNS forwarders.
6. Latency & Routing Control
Each cloud influences routing differently, so traffic may take unexpected paths.
Multi-cloud networking requires deliberate engineering, or it quickly becomes a mess of tunnels and manual routes.
Multi-Cloud Network Connectivity Patterns
There are four major patterns used today. Which one is “best” depends on scale, compliance, and traffic needs.
Pattern 1: VPN-to-VPN Connectivity (Good for Small Environments)
This is the simplest approach:
- Create site-to-site VPN between AWS-Azure
- Another VPN between Azure-GCP
- And optionally AWS-GCP
Pros:
✔ Fast to deploy
✔ No special services needed
✔ Great for POCs or low-volume traffic
Cons:
✘ High latency
✘ Not scalable
✘ Difficult for large enterprises
✘ Hard to manage 20+ connections
Use this approach only for small deployments or temporary setups.
Pattern 2: Cloud-to-On-Prem Hub (Hybrid Hub Model)
Many enterprises have a strong on-prem network, so they use it as the central hub.
Traffic flow:
AWS → On-Prem → Azure → On-Prem → GCP
Usually built using:
- Direct Connect
- ExpressRoute
- Cloud Interconnect
Pros:
✔ Centralised controls
✔ Stable routing
✔ Can reuse enterprise firewalls
Cons:
✘ On-prem becomes a bottleneck
✘ Expensive
✘ Not cloud-native
Good for regulated industries or companies with strong legacy infrastructure.
Pattern 3: Cloud Native Hub (Transit Gateway + vWAN + Cloud Router)
This is the most common modern pattern, connecting:
- AWS Transit Gateway
- Azure Virtual WAN
- GCP Cloud Router / HA VPN
Architecture:
AWS TGW ↔ Azure vWAN
Azure vWAN ↔ GCP Cloud Router
AWS TGW ↔ GCP Cloud Router
Pros:
✔ Cloud-native
✔ Highly scalable
✔ Vendor-managed routing
Cons:
✘ More complex
✘ Requires careful IP planning
This is ideal for medium to large enterprises aiming for resilience and performance.
Pattern 4: Multi-Cloud Mesh with Layer 3 Backbone (Enterprise Grade)
Large enterprises now use providers like:
- Megaport
- Equinix Fabric
- PacketFabric
These provide global Layer 2/3 private backbones.
How it works:
All clouds connect to Megaport/Equinix → traffic flows through private backbone → low latency → predictable routing.
Pros:
✔ Extremely low latency
✔ High performance
✔ Reduces complexity
Cons:
✘ Expensive
✘ Requires global architecture knowledge
Use this when building mission-critical multi-region, multi-cloud systems.
Core Design Principles for Multi-Cloud Networking
Regardless of architecture, the fundamentals remain the same.
1. Plan IP Addressing EARLY
The most common multi-cloud mistake:
Overlapping CIDRs.
Avoid:
- 10.0.0.0/16 everywhere
- Reusing VPC/VNet ranges
Define:
- Cloud-wide IP management
- Clear subnet allocations
- Reserved blocks for future growth
2. Standardise Naming Conventions
Consistent naming such as:
aws-prod-eu-vpc-coreaz-prod-eu-vnet-core
This reduces confusion across providers.
3. Use Zero Trust + Least Privilege
Cloud-to-cloud traffic must adhere to:
- identity-based access
- firewall rules
- segmentation
- micro-network boundaries
Avoid full /16 to /16 allow rules.
4. Automate Networking with IaC
Use:
- Terraform
- Azure Bicep
- AWS CDK
- Terragrunt
Multi-cloud networking should never be configured manually.
5. Implement Unified Observability
To avoid blind spots:
- Centralise logs
- Use OpenTelemetry
- Cross-cloud metrics
- Network flow logs
- Unified dashboards (Grafana, Datadog, New Relic)
Observability is critical when traffic travels across 3 clouds.
6. Build DNS That Works Everywhere
DNS is a hidden pain point.
Options:
- Route53 Resolver
- Azure Private DNS Resolver
- Cloud DNS Forwarders
- Custom DNS servers
You must define:
- authoritative zones
- forwarding rules
- split-horizon DNS
- PrivateLink/Private Endpoint compatibility
7. Enforce SLA and Latency Targets
Cross-cloud traffic isn’t free.
Define:
- max acceptable latency per service
- failover mechanisms
- DR strategies
- traffic distribution rules
Real-World Example Multi-Cloud Architecture
Here’s a typical enterprise setup:
- AWS runs microservices & compute
- Azure hosts AD DS, identity, API layers
- GCP runs machine learning workloads
Connectivity:
- TGW ↔ Azure vWAN + ExpressRoute
- Azure vWAN ↔ GCP Cloud Router
- AWS ↔ GCP HA VPN (backup)
DNS:
- Route53 outbound resolver
- Azure DNS private resolver
- Forwarding rules to GCP
Observability:
- OpenTelemetry exporter
- Central Grafana/Datadog view
This gives high resiliency across all 3 major cloud providers.
When Should You Use Multi-Cloud?
Multi-cloud is appropriate when:
- You need high availability beyond one cloud
- You want best-of-breed services from AWS/Azure/GCP
- Compliance requires provider diversity
- Teams have different cloud skillsets
- You need cost arbitrage across regions
It is NOT appropriate when:
- You have inexperienced cloud teams
- Simplicity is more important than flexibility
- You lack automation maturity
Final Thoughts
Multi-cloud is not just about “using AWS, Azure, and GCP.”
It is about engineering predictable connectivity, security, and routing across different cloud philosophies.
Done right, multi-cloud provides:
- availability
- flexibility
- cost control
- global reach
- independence from any one provider
Done wrong, it becomes a slow, complex network with unpredictable behaviour.
If your organisation is planning or struggling with multi-cloud networking, our team at Cloud DevOps Ltd can help design, implement, and manage a resilient architecture tailored to your needs.
Cloud DevOps Ltd specialises in:
- AWS, Azure, GCP networking
- Transit Gateway, vWAN, Cloud Router
- Private connectivity design
- Hybrid cloud integration
- Terraform automation
📩 Contact us today to discuss your project and build a future-ready cloud architecture.
