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Cloud Digital Leader

Certification exam guide

A Cloud Digital Leader can articulate the capabilities of Google Cloud core products and services and how they benefit organizations. The Cloud Digital Leader can also describe common business use cases and how cloud solutions support an enterprise. The Cloud Digital Leader exam is job-role agnostic and does not require hands-on experience with Google Cloud.

Section 1. General cloud knowledge

1.1 Define basic cloud technologies. Considerations include:

  • Differentiate between traditional infrastructure, public cloud, and private cloud
  • Define cloud infrastructure ownership
  • Shared Responsibility Model
  • Essential characteristics of cloud computing

1.2 Differentiate cloud service models. Considerations include:

  • Infrastructure as a service (IaaS), platform as a service (PaaS), and software as a service (SaaS)
  • Describe the trade-offs between level of management versus flexibility when comparing cloud services
  • Define the trade-offs between costs versus responsibility
  • Appropriate implementation and alignment with given budget and resources

1.3 Identify common cloud procurement financial concepts. Considerations include:

  • Operating expenses (OpEx), capital expenditures (CapEx), and total cost of operations (TCO)
  • Recognize the relationship between OpEx and CapEx related to networking and compute infrastructure
  • Summarize the key cost differentiators between cloud and on-premises environments

Section 2. General Google Cloud knowledge

2.1 Recognize how Google Cloud meets common compliance requirements. Considerations include:

  • Locating current Google Cloud compliance requirements
  • Familiarity with Compliance Reports Manager

2.2 Recognize the main elements of Google Cloud resource hierarchy. Considerations include:

  • Describe the relationship between organization, folders, projects, and resources

2.3 Describe controlling and optimizing Google Cloud costs. Considerations include:

  • Google Cloud billing models and applicability to different service classes
  • Define a consumption-based use model
  • Application of discounts (e.g., flat-rate, committed-use discounts [CUD], sustained-use discounts [SUD])

2.4 Describe Google Cloud’s geographical segmentation strategy. Considerations include:

  • Regions
  • Zones
  • Regional resources
  • Zonal resources
  • Multiregional resources

2.5 Define Google Cloud support options. Considerations include:

  • Distinguish between billing support, technical support, role-based support, and enterprise support
  • Recognize a variety of Service Level Agreement (SLA) applications

Section 3. Google Cloud products and services

3.1 Describe the benefits of Google Cloud virtual machine (VM)-based compute options. Considerations include:

  • Compute Engine, Google Cloud VMware Engine, and Bare Metal 
  • Custom versus standard sizing
  • Free, premium, and custom service options
  • Attached storage/disk options
  • Preemptible VMs

3.2 Identify and evaluate container-based compute options. Considerations include:

  • Define the function of a container registry
  • Distinguish between VMs, containers, and Google Kubernetes Engine

3.3 Identify and evaluate serverless compute options. Considerations include:

  • Define the function and use of App Engine, Cloud Functions, and Cloud Run
  • Define rationale for versioning with serverless compute options
  • Cost and performance tradeoffs of scale to zero

3.4 Identify and evaluate multiple data management offerings. Considerations include:

  • Describe the differences and benefits of Google Cloud’s relational and non-relational database offerings (e.g., Cloud SQL, Cloud Spanner, Cloud Bigtable, BigQuery)
  • Describe Google Cloud’s database offerings and how they compare to commercial offerings

3.5 Distinguish between ML/AI offerings. Considerations include:

  • Describe the differences and benefits of Google Cloud’s hardware accelerators (e.g., Vision API, AI Platform, TPUs)
  • Identify when to train your own model, use a Google Cloud pre-trained model, or build on an existing model

3.6 Differentiate between data movement and data pipelines. Considerations include:

  • Describe Google Cloud’s data pipeline offerings (e.g., Pub/Sub, Dataflow, Cloud Data Fusion, BigQuery, Looker)
  • Define data ingestion options

3.7 Apply use cases to a high-level Google Cloud architecture. Considerations include:

  • Define Google Cloud’s offerings around the Software Development Life Cycle (SDLC)
  • Describe Google Cloud’s platform visibility and alerting offerings

3.8 Describe solutions for migrating workloads to Google Cloud. Considerations include:

  • Identify data migration options
  • Differentiate when to use Migrate for Compute Engine versus Migrate for Anthos
  • Distinguish between lift and shift versus application modernization

3.9 Describe networking to on-premises locations. Considerations include:

  • Define Software-Defined WAN (SD-WAN)
  • Determine the best connectivity option based on networking and security requirements
  • Private Google Access

3.10 Define identity and access features. Considerations include:

  • Cloud Identity, Google Cloud Directory Sync, and Identity Access Management (IAM)