Google Cloud Certified – Cloud Digital Leader Learning Path

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Google Cloud – Cloud Digital Leader Certification Learning Path
Google Cloud – Cloud Digital Leader Certification Summary
Google Cloud – Cloud Digital Leader Exam Domains (Current)
Google Cloud – Cloud Digital Leader Certification Resources
Google Cloud – Cloud Digital Leader Certification Topics
Related Google Cloud Certifications

Google Cloud – Cloud Digital Leader Certification Learning Path

🆕 2026 Update: A new Cloud Digital Leader beta exam is open for registration through July 5, 2026 (~75 questions, 2 hours, $59). The standard exam remains available through July 29, 2026. The exam is now delivered via Pearson VUE (replacing Kryterion). Google also launched a new Generative AI Leader certification in May 2025 for non-technical professionals.

Continuing on the Google Cloud Journey, glad to have passed the seventh certification with the Professional Cloud Digital Leader certification. Google Cloud was missing the initial entry-level certification similar to AWS Cloud Practitioner certification, which was introduced as the Cloud Digital Leader certification. Cloud Digital Leader focuses on general Cloud knowledge, Google Cloud knowledge with its products and services.

Google Cloud – Cloud Digital Leader Certification Summary

  • Has 50-60 questions to be answered in 90 minutes (standard exam).
  • Registration fee is $99 USD (plus tax where applicable).
  • Covers a wide range of General Cloud and Google Cloud services and products knowledge.
  • This exam does not require much Hands-on and theoretical knowledge is good enough to clear the exam.
  • Certification validity is 3 years, with a renewal exam option (20 questions, 45 minutes, $60).
  • Exam is delivered online-proctored or at onsite test centers via Pearson VUE.

Google Cloud – Cloud Digital Leader Exam Domains (Current)

The current Cloud Digital Leader exam covers six domains:

  1. Digital Transformation with Google Cloud (~17%)
  2. Exploring Data Transformation with Google Cloud (~16%)
  3. Innovating with Google Cloud Artificial Intelligence (~16%)
  4. Modernizing Infrastructure and Applications with Google Cloud (~17%)
  5. Trust and Security with Google Cloud (~17%)
  6. Scaling with Google Cloud Operations (~17%)

Google Cloud – Cloud Digital Leader Certification Resources

Google Cloud – Cloud Digital Leader Certification Topics

General cloud knowledge

  1. Define basic cloud technologies. Considerations include:
    1. Differentiate between traditional infrastructure, public cloud, and private cloud
      1. Traditional infrastructure includes on-premises data centers
      2. Public cloud include Google Cloud, AWS, and Azure
      3. Private Cloud includes services like AWS Outpost
    2. Define cloud infrastructure ownership
    3. Shared Responsibility Model
      1. Security of the Cloud is Google Cloud’s responsibility
      2. Security on the Cloud depends on the services used and is shared between Google Cloud and the Customer
    4. Essential characteristics of cloud computing
      1. On-demand computing
      2. Pay-as-you-use
      3. Scalability and Elasticity
      4. High Availability and Resiliency
      5. Security
  2. Differentiate cloud service models. Considerations include:
    1. Infrastructure as a service (IaaS), platform as a service (PaaS), and software as a service (SaaS)
      1. IaaS – everything is done by you – more flexibility more management
      2. PaaS – most of the things are done by Cloud with few things done by you – moderate flexibility and management
      3. SaaS – everything is taken care of by the Cloud, you would just use it – no flexibility and management
    2. Describe the trade-offs between level of management versus flexibility when comparing cloud services
    3. Define the trade-offs between costs versus responsibility
    4. Appropriate implementation and alignment with given budget and resources
  3. Identify common cloud procurement financial concepts. Considerations include:
    1. Operating expenses (OpEx), capital expenditures (CapEx), and total cost of operations (TCO)
      1. On-premises has more of Capex and less OpEx
      2. Cloud has no to least Capex and more of OpEx
    2. Recognize the relationship between OpEx and CapEx related to networking and compute infrastructure
    3. Summarize the key cost differentiators between cloud and on-premises environments

General Google Cloud knowledge

  1. Recognize how Google Cloud meets common compliance requirements. Considerations include:
    1. Locating current Google Cloud compliance requirements
    2. Familiarity with Compliance Reports Manager
  2. Recognize the main elements of Google Cloud resource hierarchy. Considerations include:
    1. Describe the relationship between organization, folders, projects, and resources i.e. Organization -> Folder -> Folder or Projects -> Resources
  3. Describe controlling and optimizing Google Cloud costs. Considerations include:
    1. Google Cloud billing models and applicability to different service classes
    2. Define a consumption-based use model
    3. Application of discounts (e.g., flat-rate, committed-use discounts [CUD], sustained-use discounts [SUD])
      1. Sustained-use discounts [SUD] are automatic discounts for running specific resources for a significant portion of the billing month
      2. Committed use discounts [CUD] help with committed use contracts in return for deeply discounted prices for VM usage
  4. Describe Google Cloud’s geographical segmentation strategy. Considerations include:
    1. Regions are collections of zones. Zones have high-bandwidth, low-latency network connections to other zones in the same region. Regions help design fault-tolerant and highly available solutions.
    2. Zones are deployment areas within a region and provide the lowest latency usually less than 10ms
    3. Regional resources are accessible by any resources within the same region
    4. Zonal resources are hosted in a zone are called per-zone resources.
    5. Multiregional resources or Global resources are accessible by any resource in any zone within the same project.
  5. Define Google Cloud support options. Considerations include:
    1. Distinguish between billing support, technical support, role-based support, and enterprise support
      1. Role-Based Support provides more predictable rates and a flexible configuration. Although they are legacy, the exam does cover these.
      2. Enterprise Support provides the fastest case response times and a dedicated Technical Account Management (TAM) contact who helps you execute a Google Cloud strategy.
    2. Recognize a variety of Service Level Agreement (SLA) applications

Google Cloud products and services

  1. Describe the benefits of Google Cloud virtual machine (VM)-based compute options. Considerations include:
    1. Compute Engine provides virtual machines (VM) hosted on Google’s infrastructure.
    2. Google Cloud VMware Engine helps easy lift and shift VMware-based applications to Google Cloud without changes to the apps, tools, or processes
    3. Bare Metal lets businesses run specialized workloads such as Oracle databases close to Google Cloud while lowering overall costs and reducing risks associated with migration
    4. Custom versus standard sizing
    5. Free, premium, and custom service options
    6. Attached storage/disk options
    7. Spot VMs (formerly Preemptible VMs) are instances that can be created and run at a much lower price than standard instances. Google Cloud can reclaim them at any time when resources are needed. Spot VMs are the recommended replacement for Preemptible VMs.
      ⚠️ Note: Preemptible VMs have been superseded by Spot VMs. Google recommends using Spot VMs for fault-tolerant, batch, and stateless workloads. Spot VMs have no maximum 24-hour runtime limit unlike legacy Preemptible VMs.
  2. Identify and evaluate container-based compute options. Considerations include:
    1. Define the function of a container registry
      1. Artifact Registry is the recommended service to manage container images, perform vulnerability analysis, and manage access control. It supports Docker images, language packages, and OS packages.
        ⚠️ Note: Container Registry was shut down on March 18, 2025. All users must use Artifact Registry which provides all Container Registry functionality plus additional features including multi-format support and regional repositories.
    2. Distinguish between VMs, containers, and Google Kubernetes Engine
  3. Identify and evaluate serverless compute options. Considerations include:
    1. Define the function and use of App Engine, Cloud Functions, and Cloud Run
    2. Define rationale for versioning with serverless compute options
    3. Cost and performance tradeoffs of scale to zero
      1. Scale to zero helps provides cost efficiency by scaling down to zero when there is no load but comes with an issue with cold starts
      2. Serverless technologies like Cloud Functions, Cloud Run, App Engine Standard provide these capabilities
  4. Identify and evaluate multiple data management offerings. Considerations include:
    1. Describe the differences and benefits of Google Cloud’s relational and non-relational database offerings
      1. Cloud SQL provides fully managed, relational SQL databases and offers MySQL, PostgreSQL, MSSQL databases as a service
      2. Cloud Spanner provides fully managed, relational SQL databases with joins and secondary indexes
      3. AlloyDB for PostgreSQL is a fully managed, PostgreSQL-compatible database service designed for demanding enterprise workloads, offering up to 4x faster performance than standard PostgreSQL
      4. Cloud Bigtable provides a scalable, fully managed, non-relational NoSQL wide-column analytical big data database service suitable for low-latency single-point lookups and precalculated analytics
      5. Firestore is a fully managed, serverless NoSQL document database for mobile, web, and server development
      6. BigQuery provides fully managed, no-ops, OLAP, enterprise data warehouse (EDW) with SQL and fast ad-hoc queries.
    2. Describe Google Cloud’s database offerings and how they compare to commercial offerings
  5. Distinguish between ML/AI offerings. Considerations include:
    1. Describe the differences and benefits of Google Cloud’s AI and ML services
      1. Vertex AI is Google Cloud’s unified AI/ML platform for building, deploying, and scaling ML models and AI applications
      2. Gemini is Google’s multimodal large language model available through Vertex AI for generative AI use cases
    2. Identify when to train your own model, use a Google Cloud pre-trained model, or build on an existing model
      1. Vision AI provides out-of-the-box pre-trained models to extract data from images
      2. Vertex AI AutoML provides the ability to train custom models with minimal ML expertise
      3. BigQuery ML provides support for limited models and SQL interface
      4. Gemini and other foundation models allow fine-tuning for domain-specific tasks
    3. Understand generative AI concepts
      1. Large Language Models (LLMs), foundation models, and multimodal models
      2. Prompting, fine-tuning, and grounding
      3. Responsible AI principles
  6. Differentiate between data movement and data pipelines. Considerations include:
    1. Describe Google Cloud’s data pipeline offerings
      1. Cloud Pub/Sub provides reliable, many-to-many, asynchronous messaging between applications. By decoupling senders and receivers, Google Cloud Pub/Sub allows developers to communicate between independently written applications.
      2. Cloud Dataflow is a fully managed service for strongly consistent, parallel data-processing pipelines
      3. Cloud Data Fusion is a fully managed, cloud-native, enterprise data integration service for quickly building & managing data pipelines
      4. BigQuery Service is a fully managed, highly scalable data analysis service that enables businesses to analyze Big Data.
      5. Looker provides an enterprise platform for business intelligence, data applications, and embedded analytics.
      6. Data Studio (formerly known as Looker Studio) is a free, self-service data visualization and reporting tool for creating interactive dashboards.
    2. Define data ingestion options
  7. Apply use cases to a high-level Google Cloud architecture. Considerations include:
    1. Define Google Cloud’s offerings around the Software Development Life Cycle (SDLC)
    2. Describe Google Cloud’s platform visibility and alerting offerings covers Cloud Monitoring and Cloud Logging
  8. Describe solutions for migrating workloads to Google Cloud. Considerations include:
    1. Identify data migration options
      1. Storage Transfer Service for transferring data between cloud storage providers
      2. Transfer Appliance for large-scale offline data migration
      3. Database Migration Service for migrating databases to Cloud SQL and AlloyDB
    2. Differentiate when to use Migrate to Virtual Machines versus Migrate to Containers
      1. Migrate to Virtual Machines (formerly Migrate for Compute Engine) provides fast, flexible, and safe VM migration to Google Cloud
        ⚠️ Note: Migrate for Compute Engine was deprecated on April 30, 2024 and replaced by Migrate to Virtual Machines.
      2. Migrate to Containers (formerly Migrate for Anthos and GKE) makes it fast and easy to modernize traditional applications away from virtual machines and into native containers. This significantly reduces the cost and labor that would be required for a manual application modernization project.
    3. Distinguish between lift and shift versus application modernization
      1. Lift and shift involves migration with zero to minimal changes and is usually performed with time constraints
      2. Application modernization requires a redesign of infra and applications and takes time. It can include moving legacy monolithic architecture to microservices architecture, building CI/CD pipelines for automated builds and deployments, frequent releases with zero downtime, etc.
  9. Describe networking to on-premises locations. Considerations include:
    1. Define Software-Defined WAN (SD-WAN)
    2. Determine the best connectivity option based on networking and security requirements – covers Cloud VPN, Interconnect, and Peering.
    3. Private Google Access provides access from VM instances to Google services like Cloud Storage or third-party services without external IP addresses
  10. Define identity and access features. Considerations include:
    1. Cloud Identity & Access Management (Cloud IAM) provides administrators the ability to manage cloud resources centrally by controlling who can take what action on specific resources.
    2. Google Cloud Directory Sync enables administrators to synchronize users, groups, and other data from an Active Directory/LDAP service to their Google Cloud domain directory.

Related Google Cloud Certifications

After completing the Cloud Digital Leader certification, consider the following paths: