Professional-Cloud-DevOps-Engineer Exam Dumps : Google Cloud Certified - Professional Cloud DevOps Engineer Exam

To speed up Docker builds, optimize layer caching. Google Cloud recommends using --cache-from with Artifact Registry, and placing frequently changed files late in the Dockerfile so earlier layers can be reused.

“Put instructions that are less likely to change (like installing packages) early in the Dockerfile, and more frequently changing lines (like copying app code) near the end.”

— Dockerfile Best Practices

“Use the --cache-from argument to pull layers from previously built images in Artifact Registry.”

— Cloud Build Docker Caching

This dramatically reduces build time by avoiding redundant rebuilds of static layers.

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).

The best option for selecting a deployment and testing strategy that meets your requirements is to use blue/green deployment and canary testing. A blue/green deployment is a deployment strategy that involves creating two identical environments, one running the current version of the application (blue) and one running the new version of the application (green). The traffic is switched from blue to green after testing the new version, and if any issues are discovered, the traffic can be switched back to blue instantly. This way, you can reduce the complexity of release deployments and minimize the duration of deployment rollbacks. A canary testing is a testing strategy that involves releasing a new version of an application to a subset of users or servers and monitoring its performance and reliability. This way, you can test real production traffic with a gradual increase in the number of affected users.