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Cloud Bursting – Key Element of Modern Hybrid Cloud Architectures

Author

Govardhana M K
April 05, 2025

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  • Cloud Bursting – Key Element of Modern Hybrid Cloud Architectures

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🧠 USE CASE

Cloud Bursting – Key Element of Modern Hybrid Cloud Architectures

Not many cloud engineers are aware of cloud bursting, though it's widely adopted in retail, trading, gaming, and media platforms that see unpredictable traffic.

Here’s what it means in practice. Your app runs in a private cloud or on prem environment. When traffic suddenly spikes beyond its capacity, the extra demand is offloaded to the public cloud. This offloading is called bursting.

I’ve prepared this simple and self explanatory breakdown for easy understanding.

Download a high resolution copy of this diagram here for future reference.

But what does it take to actually implement cloud bursting in production?

1. Your Architecture Must Support Cloud Native Dual Deployment

Start by making sure the application or workload can run identically in both private and public environments. This means:

  • Stateless or loosely coupled services work best

  • Session persistence must be externalized (think Redis, Memcached)

  • Use containerized workloads (Kubernetes or Nomad) to simplify portability

  • Externalize environment configs using tools like Consul, Vault, or SSM Parameters

If your workloads rely on local storage or hardcoded infra settings, cloud bursting will fail before it starts.

2. You’ll Need a Load Balancer That Can Split Between Clouds

Cloud bursting isn’t just about compute. It’s about routing.

  • Use DNS based traffic management (Route53, Azure Traffic Manager, NS1) to distribute requests

  • Combine with L7 load balancers like HAProxy, NGINX, or cloud native equivalents (ALB, Cloud Armor, Application Gateway)

  • Apply health checks to detect spike thresholds and burst triggers

For advanced setups, deploy a service mesh like Istio or Consul Mesh for east-west traffic routing across clusters.

3. Set Up Automation for Burst Triggers

This is where most implementations get messy.

  • Use pod autoscalers (K8s HPA/VPA) with metrics from Prometheus, CloudWatch, or Datadog

  • Trigger infrastructure scale out using Terraform or Pulumi via event driven systems like AWS EventBridge, Azure Event Grid, or GCP Pub/Sub

  • Leverage CI/CD pipelines to prepare standby infra in public cloud, but only scale when needed

Avoid static thresholds. Use real metrics (CPU, memory, request latency, queue depth) to trigger intelligently.

4. Security and Compliance Cannot Be Bolted On Later

The moment data moves between two clouds, you need to be extra cautious.

  • Enable end to end encryption between clouds (TLS + mutual auth)

  • Use IAM federation between private and public environments (e.g., AD → AWS IAM Roles via SAML or Microsoft Entra)

  • Log access and actions across both clouds using centralized systems (ELK, Splunk, or cloud native logging tools)

Build in audit trails and compliance hooks from the start.

My 2 Cents:

  • Don’t try bursting your monolith.

  • Document which metrics trigger bursting.

  • Always simulate bursting before real traffic.

  • Create burn back plans for when traffic reduces.

Cloud bursting is powerful, but only if you’ve done the groundwork. The theory is simple. The implementation is not.

Get the architecture, automation, and observability right or expect pain when traffic hits.

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