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An online retail enterprise currently hosts a monolithic backend application on a fleet of Compute Engine virtual machines. As business demand increases, the engineering team encounters several challenges:
You need to modernize the architecture to support independent CI/CD release cycles, eliminate infrastructure management overhead, and achieve rapid elasticity with zero idle cost.
Which modernization strategy should you recommend?
Decompose the application into modular, containerized microservices and event-driven services deployed on Cloud Run and Cloud Run functions, integrated with automated CI/CD pipelines and Pub/Sub messaging.
Maintain the monolithic virtual machines on Compute Engine, implement Cloud Memorystore for Redis in-memory caching, and conduct code profiling to reduce database load.
Rehost the monolithic application across a Compute Engine Managed Instance Group (MIG) configured with predictive autoscaling, and automate VM image creation using CI/CD pipelines.
Refactor the monolith into containerized services hosted on custom, self-managed Kubernetes clusters on Compute Engine VMs with manual node provisioning.
Decompose the application into modular, containerized microservices and event-driven services deployed on Cloud Run and Cloud Run functions, integrated with automated CI/CD pipelines and Pub/Sub messaging.
A serverless microservices architecture breaks down a large, monolithic application into smaller, loosely coupled domain services. Deploying these containerized components onto fully managed services like Cloud Run and Cloud Run functions abstracts away all underlying server and infrastructure management while leveraging native Google Cloud event-driven tools like Pub/Sub and Eventarc.
Migrating directly to serverless container and event platforms addresses the organizational shift toward agility and cost efficiency. It eliminates legacy VM maintenance debt while granting development teams the autonomy to innovate and release code continuously.
Maintain the monolithic virtual machines on Compute Engine, implement Cloud Memorystore for Redis in-memory caching, and conduct code profiling to reduce database load.
Rehost the monolithic application across a Compute Engine Managed Instance Group (MIG) configured with predictive autoscaling, and automate VM image creation using CI/CD pipelines.
Refactor the monolith into containerized services hosted on custom, self-managed Kubernetes clusters on Compute Engine VMs with manual node provisioning.
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