Scenario: You are managing an application on Google Cloud Platform (GCP) that serves a global audience with both static and dynamic content. To improve user experience, you implemented a caching layer in Cloud Memorystore (Redis). However, as usage has increased, so has the cost of maintaining the Redis cache. You notice that the Redis cache hit rate is lower than expected, with many requests still reaching the backend, which drives up costs for both the cache and backend resources.What action would be the most effective way to optimize cache utilization and reduce costs?
An enterprise cloud customer received a custom rebate on cloud spend for the last quarter due to exceeding their usage commitment. The cloud provider’s rebate terms state that the rebate will only apply to actual consumption that meets specific cost-saving initiatives, such as using Reserved Instances and reducing idle resources. The FinOps team wants to ensure they maximize these rebate opportunities while keeping spend efficient across the next quarter. What is the most effective strategy to achieve this?
Scenario: A gaming company operates a serverless backend on Google Cloud Platform (GCP) to support a global multiplayer game. They use Google Cloud Functions to handle API requests from players and store game state data in Google Cloud Firestore. Recently, costs have surged due to increased player interactions, leading to frequent Cloud Function invocations and high Firestore read/write charges. The development team wants to optimize the serverless architecture to reduce these expenses while maintaining real-time game response times for a smooth player experience.What is the most cost-effective approach to optimize the architecture while meeting the performance requirements?
Which of the following actions best ensures that cloud financial policies designed at the engineering level are followed consistently across multiple development teams?