Mountkirk Games has deployed their new backend on Google Cloud Platform (GCP). You want to create a through testing process for new versions of the backend before they are released to the public. You want the testing environment to scale in an economical way. How should you design the process?

Creating a scalable environment in GCP for simulating production load is the most effective approach. GCP's auto-scaling capabilities (e.g., Managed Instance Groups, Google Kubernetes Engine) allow you to dynamically provision resources only when needed for testing, making it economical. This setup accurately reflects how your production environment will behave under varying loads, ensuring robust testing. Using existing infrastructure to test a GCP-based backend is inefficient and doesn't leverage GCP's native scaling. Building stress tests into each component might identify individual bottlenecks but won't simulate end-to-end system behavior or external load effectively. Creating static environments for different load levels is less economical and flexible than a dynamically scalable environment, as resources might be idle or insufficient for unexpected load patterns.