Case Study

GCP Load Balancing Foundational IAC

Challenge

The customer, a large financial media company, operates a hybrid cloud environment comprised of on-premise data centers and multiple cloud providers. Rearc worked with the customer's internal cloud team, which strives to empower their application developer teams to rapidly deploy both containerized and VM based workloads in ANY cloud provider by providing a simple menu item of foundational compute capabilities and platforms they can choose from. This insulates developer teams from having to deal with idiosyncrasies of individual cloud compute platforms. One of those foundational capabilities is load balancing. GCP has myriad load balancing options and the objective was to present those options as easy-to-consume Infrastructure-as-code (IAC) modules to encourage proper, fast and secure adoption.

Solution

Rearc researched and understood the capabilities of various load balancing options available in GCP and compared those with required customer use-cases. Rearc then leveraged Terraform in a "module library pattern" to implement and document the various flavors of GCP load balancing. The modules are consumed by Jenkins as the CI/CD platform to deploy infrastructure in GCP for Internet-facing as well as internal web applications.

Outcome

With Rearc's assistance, the customer has enriched their IAC module registry with multiple load balancing options that application developer teams can leverage to expose their applications in GCP. These options include:

  • Global External Load Balancer module for Internet-facing compute applications running on NEGs and Instance Groups that require multi-region redundancy. The same module could be optionally "locked down" for Internal-only access if required.
  • Global Kubernetes Ingress Load Balancer module for Internet-facing layer-7 applications running on GKE. This employed both the Google and Kubernetes providers for Terraform.
  • Internal Kubernetes Ingress Load Balancer module for internal layer-7 applications running on GKE. This also employed both the Google and Kubernetes providers for Terraform.
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