Cloud-Digital-Leader Exam Dumps : Google Cloud Digital Leader exam

The key to remember here is that for a service provided (GCP in this case) to take responsibility for its PaaS, it must offer the service as a managed service. GCP offers its own Kubernetes platform called GKE. But OpenShift is not a Google-offered PaaS solution. As such, Google will not take responsibility for the back-end operations and design of your OpenShift environments. You will need to manage all the VMs that OpenShift will provision as part of its GCP deployment. So this is an IaaS deployment from a shared responsibility model perspective.

Google Cloud Dataflow is a fully managed service for creating data pipelines that can handle both batch and stream processing. It is scalable and requires minimal management, making it ideal for transforming data before reconciling it in a data warehouse. Dataflow integrates seamlessly with other Google Cloud services, such as BigQuery, to create end-to-end data processing solutions.

Option B: Dataflow is correct because it provides a scalable and managed solution for building data pipelines.

References:

Google Cloud Dataflow: Scalable Data Processing Service

Google Cloud Data Integration: Building Data Pipelines with Dataflow

Service Level Agreement (SLA) 

A service level agreement (SLA) is a contract between a service provider (either internal or external) and the end user that defines the level of service expected from the service provider. Some common SLA’s are uptime, Response Time, etc.