Migrating your existing application load balancer infrastructure from an on-premises hardware solution to Cloud Load Balancing offers substantial advantages in scalability, cost-efficiency, and tight integration within the Google Cloud ecosystem. Yet, a fundamental question often arises: “What about our current load balancer configurations?”
Existing on-premises load balancer configurations often contain years of business-critical logic for traffic manipulation. The good news is that not only can you fully migrate existing functionalities, but this migration also presents a significant opportunity to modernize and simplify your traffic management.
This guide outlines a practical approach for migrating your existing load balancer to Google Cloud’s Application Load Balancer. It addresses common functionalities, leveraging both its declarative configurations and the innovative, event-driven Service Extensions edge compute capability.
A simple, phased approach to migration
Transitioning from an imperative, script-based system to a cloud-native, declarative-first model requires a structured plan. We recommend a straightforward, four-phase approach.
Phase 1: Discovery and mapping
Before commencing any migration, you must understand what you have. Analyze and categorize your current load balancer configurations. What is each rule’s intent? Is it performing a simple HTTP-to-HTTPS redirect? Is it engaged in HTTP header manipulation (addition or removal)? Or is it handling complex, custom authentication logic?
Most configurations typically fall into two primary categories:
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Common patterns: Logic that is common to most web applications, such as redirects, URL rewrites, basic header manipulation, and IP-based access control lists (ACLs).
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Bespoke business logic: Complex logic unique to your application, like custom proprietary token authentication, advanced header extraction / replacement, dynamic backend selection based on HTTP attributes, or HTTP response body manipulation.
Phase 2: Choose your Google Cloud equivalent
Once your rules are categorized, the next step involves mapping them to the appropriate Google Cloud feature. This is not a one-to-one replacement; it’s a strategic choice.
Option 1: the declarative path (for ~80% of rules)
For the majority of common patterns, leveraging the Application Load Balancer’s built-in declarative features is usually the best approach. Instead of a script, you define the desired state in a configuration file. This is simpler to manage, version-control, and scale.
Common patterns to declarative feature mapping:
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Redirects/rewrites -> Application Load Balancer URL maps
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ACLs/throttling -> Google Cloud Armor security policies
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Session persistence -> backend service configuration
Option 2: The programmatic path (for complex, bespoke rules)
When dealing with complex, bespoke business logic, you have a programmatic equivalent: Service Extensions, a powerful edge compute capability that allows you to inject custom code (written in Rust, C++ or Go) directly into the load balancer’s data path. This approach gives you flexibility in a modern, managed, and high-performance framework.
