Multi-Cloud

Cloud › Multi-Cloud

🌐Multi-Cloud

BeginnerEngineerArchitectMulti-cloud strategy, Terraform multi-provider, challenges and patterns

[What is Multi-Cloud](#sec-what)[Tools](#sec-tools)[Challenges](#sec-challenges)[Q&A](#sec-interview)

🌐 What is Multi-Cloud?›

#### What is multi-cloud?

Multi-cloud means using services from more than one public cloud provider simultaneously. For example: AWS for machine learning workloads (SageMaker has the deepest ML ecosystem), Azure for Kubernetes and enterprise identity (AKS + Active Directory integration), and GCP for analytics (BigQuery is unmatched for large-scale data warehousing). Each cloud used for what it does best.

Multi-cloud is different from hybrid cloud. Hybrid cloud = one public cloud connected to your own on-premise data centre. Multi-cloud = multiple public cloud providers (AWS, Azure, GCP) — no on-premise required.

#### Why organisations use multi-cloud

Reason	Explanation	Real example

|---|---|---|

Best-of-breed services	Each cloud has unique strengths that no other cloud matches	GCP BigQuery, Azure AD + M365, AWS broadest managed services
Avoid vendor lock-in	One cloud controls your pricing. Two clouds gives negotiation leverage.	Renegotiate AWS contract because Azure is a real option
Regulatory compliance	Some regions require data processing by specific providers	India RBI regulations, European data residency requirements
Resilience	Major cloud outages happen — AWS us-east-1, Azure East US both have had multi-hour incidents	Route traffic to Azure if AWS has an outage
Mergers and acquisitions	Acquired company uses a different cloud — consolidation takes years	Post-acquisition: one team on AWS, another on Azure

#### Multi-cloud by design vs by accident

Most organisations are multi-cloud by accident — different teams chose different clouds independently, or acquisitions brought in companies using different providers. Managing this unplanned multi-cloud is harder than designing for it. The tools and patterns below apply to both scenarios.

🔷 Terraform Multi-Cloud›

Multi-provider Terraform + Route53 failoverCopy

☸️ Multi-Cluster Kubernetes›

ArgoCD ApplicationSet + Cluster API + SubmarinerCopy

🔧 Tools — Terraform, Kubernetes, Observability›

#### Why organisations go multi-cloud

Reason	Explanation	Real example

|---|---|---|

Avoid vendor lock-in	No single provider can hold you hostage on pricing or features	Use AWS for compute, Azure for AD integration
Best-of-breed services	Each cloud has unique strengths	GCP BigQuery for analytics, Azure for enterprise identity, AWS for ML
Regulatory compliance	Some countries require specific cloud providers	India: RBI mandates some data on local providers
Resilience	One cloud outage does not take down everything	Route traffic to AWS if Azure has an outage
Mergers and acquisitions	Acquired company uses different cloud	Post-acquisition: one team on AWS, another on Azure
Cost arbitrage	Different pricing for different workloads	Spot instances cheaper on AWS for batch

#### Multi-cloud challenges

Challenge	Impact	Mitigation

|---|---|---|

Skills gap	Need expertise in 2-3 clouds — expensive	Focus on cloud-agnostic tools (K8s, Terraform)
Data egress costs	Moving data between clouds is expensive	Keep compute close to data — process where data lives
Security complexity	Separate IAM, policies, tools per cloud	CSPM tools (Prisma Cloud, Wiz) for unified view
Operational overhead	2x the monitoring, alerting, ops runbooks	Unified observability (Datadog, Prometheus federation)
Networking complexity	Cross-cloud connectivity needs VPN or SD-WAN	Avoid cross-cloud data paths where possible

#### Tools that make multi-cloud manageable

Tool	Category	What it does

|---|---|---|

Terraform	IaC	Manage AWS, Azure, GCP with one codebase. Provider per cloud, same workflow.
Kubernetes	Compute	Same manifests, Helm charts, ArgoCD on any cloud K8s cluster
Datadog / Prometheus	Observability	Unified metrics and alerts across all clouds
Vault (HashiCorp)	Secrets	One secrets store accessed from any cloud
Packer	Images	Build machine images for AMI (AWS), VHD (Azure), GCE image (GCP) from one template
Pulumi	IaC	Like Terraform but uses Python/TypeScript instead of HCL

#### Terraform multi-cloud example

# providers.tf — configure multiple clouds
terraform {
required_providers {
aws   = { source = "hashicorp/aws",     version = "~> 5.0" }
azurerm = { source = "hashicorp/azurerm", version = "~> 3.0" }
google  = { source = "hashicorp/google",  version = "~> 5.0" }
}
}

provider "aws" {
region = "us-east-1"
}
provider "azurerm" {
features {}
subscription_id = var.azure_subscription_id
}
provider "google" {
project = var.gcp_project
region  = "us-central1"
}

# Use AWS for primary, Azure for DR
resource "aws_instance" "primary" { ... }
resource "azurerm_virtual_machine" "dr" { ... }

⚠️ Challenges and Tradeoffs›

#### Common multi-cloud architecture patterns

Pattern	How it works	When to use

|---|---|---|

Cloud-agnostic apps	Apps containerised with K8s, deploy anywhere, use abstracted storage/DB APIs	Portability is a requirement, no vendor lock-in acceptable
Cloud bursting	Primary workload on one cloud, burst to second cloud for peaks	Cost optimisation, seasonal peaks
Active-active DR	Full deployment on two clouds, Route 53/Traffic Manager routes between them	Zero downtime requirement, can afford 2x cost
Best-of-breed	Each cloud used for what it does best, integrated via APIs	GCP BigQuery + Azure AD + AWS EKS in same platform
Shadow IT consolidation	Different business units chose different clouds — consolidate with unified governance	Post-merger, large enterprise with many teams

#### Multi-cloud networking options

Option	What it is	Cost

|---|---|---|

Cloud VPN	IPSec VPN tunnels between clouds over internet	Low — pay for gateway + data transfer
SD-WAN	Software-defined WAN connecting all clouds and on-prem	Medium — managed service cost
Direct interconnect	Dedicated physical link between AWS Direct Connect + Azure ExpressRoute	High — dedicated bandwidth
Aviatrix / Megaport	Third-party cloud networking fabric	Medium — subscription-based

#### Multi-cloud adds real operational complexity — know the tradeoffs before choosing it

Challenge	Impact	How to address

|---|---|---|

Skills gap	Team needs expertise across 2-3 clouds — expensive to hire and train	Invest in cloud-agnostic skills (K8s, Terraform, Prometheus). Accept some per-cloud specialisation.
Data egress costs	Moving data between clouds costs $0.08-0.09/GB — active-active multi-cloud is expensive	Keep compute close to data. Process where data lives. Avoid cross-cloud data movement.
Security complexity	Separate IAM per cloud, more attack surface, harder to audit

Multi-Cloud Strategy — Fundamentals

Multi-Cloud

🌐 What is Multi-Cloud?›

🔷 Terraform Multi-Cloud›

☸️ Multi-Cluster Kubernetes›

🔧 Tools — Terraform, Kubernetes, Observability›

⚠️ Challenges and Tradeoffs›