You have a Python web app needing ~0.1 CPU and 128MB RAM, require high machine utilization monitoring and reliable deployments. Which approach should you take?

The correct option leverages GKE for containerized applications, offering robust deployment strategies and high machine utilization monitoring. Using n1-standard-1 nodes is appropriate for an app needing only 0.1 CPU and 128MB RAM, as it allows for efficient resource packing. Building a Docker image from the production branch and tagging by version ensures immutability and traceability. Deploying to staging first and then promoting to production is a standard, reliable release process. imagePullPolicy: IfNotPresent is suitable for staging to avoid unnecessary pulls if the image is already present, while Always is often preferred in production to ensure the latest image is always used. The first incorrect option uses f1-micro VMs, which are too small for reliable production use, and relies on startup scripts for deployments, which is error-prone and lacks version control. The second incorrect option uses n1-standard-1 VMs but bakes images, which is less flexible than containerization and still relies on VM restarts for deployments. The third incorrect option uses n1-standard-4 nodes, which are overkill for the stated requirements, leading to higher costs and lower utilization. It also suggests tagging with 'latest' and restarting pods, which is a less controlled and reliable deployment strategy compared to versioned images and phased rollouts.