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Google Cloud Fundamentals

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Google Cloud Fundamentals

GCP

Duration
45 Hours

Course Description

              A Google Cloud Fundamentals course provides an overview of Google Cloud Platform (GCP) and its core services, including infrastructure, storage, and networking. It covers essential concepts like IaaS and PaaS, resource management, and security principles. Hands-on labs and assessments are often included to help participants gain practical experience. 

Course Outline For Google Cloud Fundamentals

Introducing Google Cloud:

  • Cloud computing concepts and benefits.
  • GCP's global infrastructure, including regions and zones.
  • Comparison of GCP with other cloud providers.
  • IaaS and PaaS service models.

Getting Started with Google Cloud:

  • Creating and configuring GCP projects.
  • Managing billing and setting up alerts.
  • Using the Cloud Console, Cloud Shell, and Cloud SDK.
  • Managing resources with projects.
  • Understanding Identity and Access Management (IAM).

Compute Services:

  • Introduction to Compute Engine (VMs).
  • Google Kubernetes Engine (GKE) for container orchestration.
  • Google App Engine for platform-as-a-service (PaaS) deployments.
  • Cloud Functions for event-driven serverless computing.
  • Cloud Run for managed serverless containers.

Storage and Database Services:

  • Google Cloud Storage for object storage.
  • Persistent Disks and Cloud Filestore for block and file storage.
  • Cloud SQL for managed relational databases.
  • Cloud Spanner for horizontally scalable relational databases.
  • Cloud Bigtable for NoSQL databases.
  • Cloud Datastore (now integrated into Firestore).
  • Firestore for NoSQL document databases.
  • Cloud Memorystore for in-memory data storage.
  • Choosing the right storage option for different use cases.

Networking Services:

  • Virtual Private Cloud (VPC) networking basics.
  • VPC network architectures and components.
  • Cloud Load Balancing for distributing traffic.
  • Cloud DNS for domain name management.
  • Cloud CDN for content delivery.
  • Hybrid connectivity options (e.g., Cloud VPN, Cloud Interconnect).

Identity and Access Management (IAM):

  • Overview of Cloud IAM and its importance for security.
  • Managing IAM identities, permissions, and roles.
  • Understanding service accounts.

Data and Analytics Services:

  • Introduction to BigQuery for data warehousing and analytics.
  • Cloud Pub/Sub for messaging and data ingestion.
  • Cloud Dataflow for data processing.
  • Cloud Dataproc for Hadoop and Spark clusters.
  • Cloud Data Fusion for data integration.

AI and Machine Learning Services:

  • Introduction to Vertex AI for ML development and deployment.
  • Google Cloud AI Building Blocks.
  • Generative AI models and access through Vertex AI.

Management and Operations Tools:

  • Cloud Monitoring and Cloud Logging for observability.
  • Cloud Deployment Manager for infrastructure as code.
  • Cloud Trace, Debugger, and Error Reporting for troubleshooting.
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