Your company is building containerized applications as part of their CI/CD pipeline. To improve the security and maintainability of the build process, you need to: •Identify potential vulnerabilities within your container images. •Generate verifiable metadata about the builds for auditing and compliance. •Create a comprehensive inventory of your application’s dependencies What should you do?
Answer(s): A
A — Use Cloud Build to build container images, and then trigger Artifact Analysis on images pushed to Artifact Registry.You need to address three specific goals in your CI/CD pipeline:Identify potential vulnerabilities in container imagesGenerate verifiable metadata for auditing and complianceCreate a comprehensive inventory of application dependencies
Your team is running applications on a Google Kubernetes Engine (GKE) cluster with a private endpoint. You've set up a Cloud Deploy pipeline, but deployments to the GKE cluster are failing. You need to resolve the issue. What should you do?
Answer(s): C
C: Create a Cloud Build private pool that is peered with the same VPC network as your GKE cluster. Update the Cloud Deploy pipeline to use this private pool as its execution environment. When a GKE cluster has a private endpoint, its control plane is only accessible from within its own Virtual Private Cloud (VPC) network or peered networks. The default execution environment for Cloud Deploy is a Google-managed, multi-tenant infrastructure which does not have access to your private VPC network. To resolve this connectivity issue, you must configure a private execution
You are planning to migrate your on-premises compute and SAP workloads to Google Cloud. You want to follow Google-recommended practices to quickly create a cost estimate for running these workloads in Google Cloud. What should you do?
Answer(s): D
D: Gather data about your current environment, and leverage Google Cloud Migration Center to generate a cost estimate.Google’s recommended approach for migrating on-prem workloads (especially complex ones like SAP) is to use Migration Center because it:Collects data from your existing infrastructureAnalyzes current utilization and dependenciesProvides automated right-sized cost estimatesHelps plan migration strategies and timelinesIt’s purpose-built for migration discovery + cost estimation, which is exactly what you need.
Your organization has a significant amount of log data stored in Cloud Logging. The data engineering team is accustomed to using SQL for analysis and wants the ability to create insightful dashboards for visualizing log trends and patterns. You want to follow the recommendations of the Google Cloud Well-Architected Framework to provide a solution for the data engineering team. What should you do?
C: Enable log analytics and run queries in the linked log dataset in BigQuery. Visualize the data with LookerStudio dashboards.This aligns best with Google Cloud Well-Architected Framework recommendations:Log Analytics automatically links Cloud Logging data to BigQuery without complex pipelines.The data engineering team can use standard SQL — exactly what they want.Looker Studio is designed for building dashboards and visualizations from BigQuery datasets.Minimal operational overhead (no custom export pipelines)Native SQL analyticsScalable dashboarding solutionCloud-native best practice
You are designing the storage architecture for a financial analytics platform. The platform ingests and stores terabytes of transactional data daily, which is used for both real-time fraud detection and long-term historical analysis. Transaction data from the last 30 days must be accessible with very low latency for the fraud detection engine. Data older than 30 days is accessed infrequently for quarterly reports, where retrieval times of a few seconds are acceptable. All data must be retained for five years to meet compliance regulations. You need to design a solution as cost-effective as possible. What should you do?
D — Configure a Cloud Storage bucket with an Object Lifecycle Management policy to transition data from the Standard class to the Coldline class after 30 days.Your platform needs to handle very different access patterns:Last 30 days of dataVery low latencyUsed for real-time fraud detectionData older than 30 daysAccessed infrequentlyRetrieval time of a few seconds is acceptableRetentionAll data must be kept for 5 yearsCostMust be as cost-effective as possible
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