Explanation
The best option for troubleshooting the issue without having execute access to workloads and nodes is to use Network Connectivity Center to perform a Connectivity Test from Cluster A to Cluster B. Network Connectivity Center is a service that allows you to create, manage, and monitor network connectivity across Google Cloud, hybrid, and multi-cloud environments. You can use Network Connectivity Center to perform a Connectivity Test, which is a feature that allows you to test the reachability and latency between two endpoints, such as GKE clusters, VM instances, or IP addresses. By using Network Connectivity Center to perform a Connectivity Test from Cluster A to Cluster B, you can identify the layer at which the network connectivity is broken, such as the firewall, routing, or load balancing.

https://cloud.google.com/binary-authorization/docs/overview

The best option for configuring Cloud Monitoring to view the number of requests from a specific IP address with minimal operational overhead is to configure the Ops Agent with a logging receiver andcreate a logs- based metric. The Ops Agent is an agent that collects system metrics and logs from your VM instances and sends them to Cloud Monitoring and Cloud Logging. A logging receiver is a configuration that specifies which logs are collected by the Ops Agent and how they are processed. You can use a logging receiver to collect web server logs from your VM instances and send them to Cloud Logging. A logs-based metric is a metric that is extracted from log entries in Cloud Logging. You can use a logs-based metric to count the number of requests from a specific IP address by using a filter expression. You can then use Cloud Monitoring to view and analyze the logs-based metric.

Comprehensive and Detailed 150 to 200 words of Explanation From Google Cloud DevOps guides documents:
Google Cloud's Dynamic Workload Scheduler offers two distinct modes designed to balance resource availability with cost and criticality. Flex Start mode is optimized for cost-sensitive, asynchronous workloads that do not have a strict start time. It allows the scheduler to obtain capacity when it becomes available within a 7-day window, making it the ideal choice for the Research team's hundreds of small experiments. This mode prioritizes resource optimization and lower costs over immediate execution.
Conversely, Calendar mode is designed for business-critical jobs that require guaranteed capacity at a specific date and time. By using Calendar mode, the Production team can reserve the necessary GPU or TPU resources for their Friday 10:00 PM retraining session. This ensures the job starts exactly on time and runs without interruption, satisfying the "business-critical" requirement. Combining these two modes allows an organization to maximize cluster utilization: using Flex Start to fill the gaps with non-urgent research while ensuring that high-priority production tasks have the "just-in-time" resource guarantees they need to maintain SLOs (Service Level Objectives).