The best option for implementing guard rails on all GKE clusters to only allow the deployment of trusted and approved images is to use Binary Authorization to attest images during your CI/CD pipeline. Binary Authorization is a feature that allows you to enforce signature-based validation when deploying container images. You can use Binary Authorization to create policies that specify which images are allowed or denied in your GKE clusters. You can also use Binary Authorization to attest images during your CI/CD pipeline by using tools such as Container Analysis or third-party integrations. An attestation is a digital signature that certifies that an image meets certain criteria, such as passing vulnerability scans or code reviews. By using Binary Authorization to attest images during your CI/CD pipeline, you can ensure that only trusted and approved images are deployed to your GKE clusters.

Explanation
The correct answer is B. Increase the memory limit in the application deployment.
The application is experiencing a memory leak, which means that it is allocating memory that is not freed or reused. This causes the heap usage to grow constantly until it reaches the memory limit of the pod, which triggers a restart by Kubernetes. Increasing the memory limit in the application deployment can help mitigate the problem by allowing the application to run longer before reaching the limit. However, this is not a permanent solution, as the memory leak will still occur and eventually exhaust the available memory. The best solution is to identify and fix the source of the memory leak in the application code, using tools like Cloud Profiler and pprof12.

Explanation
The best option for storing and using the API key in your application by following Google-recommended practices is to save the API key in Secret Manager as a secret and reference the secret as an environment variable in the Cloud Run application. Secret Manager is a service that allows you to store and manage sensitive data, such as API keys, passwords, and certificates, in Google Cloud. A secret is a resource that represents a logical secret, such as an API key. You can save the API key in Secret Manager as a secret and use IAM policies to control who can access it. You can also reference the secret as an environment variable in the Cloud Run application by using the ${SECRET_NAME} syntax. This way, you can securely store and use the API key in your application without exposing it in your code or configuration files.

Comprehensive and Detailed 150 to 200 words of Explanation From Google Cloud DevOps guides documents:
Google Cloud's recommended practice for scalable, multi-cluster monitoring is Google Cloud Managed Service for Prometheus (GMP). This service is a fully managed, multi-cloud-capable solution built on top of Monarch (the same globally scalable time-series database Google uses internally). By using managed collection, GKE clusters automatically deploy collectors that scrape metrics without the operational overhead of managing a manual Prometheus server, scaling, or long-term storage (sharding).
This solution satisfies the "centralized and scalable" requirement because GMP allows you to query data across multiple projects and clusters using PromQL, which provides the flexible query language requested.
While the Ops Agent (Option C) is useful for VM-based workloads, GMP is the purpose-built solution for Kubernetes environments. Standard sidecar deployments (Option A) or self-managed admin clusters (Option D) introduce significant administrative toil and fail to leverage the global scale and high availability of the Cloud Monitoring backend. By centralizing metrics in Metrics Explorer, SRE teams gain a unified view of system health, making it easier to define SLOs and manage incidents across a complex microservices landscape.