GCP Associate Cloud Engineer

DASVM’s GCP course ensure learners receive the most industry-relevant training and acquire on-job skills to maintain GCP Cloud Infrastructure. This Google Cloud Platform course content offers topic-based learning on google cloud’s IAM, Security services, Cloud APIs, Network services and Computing & migration to Google Cloud.


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DASVM’s GCP course ensure learners receive the most industry-relevant training and acquire on-job skills to maintain GCP Cloud Infrastructure.  This Google Cloud Platform course content offers topic-based learning on google cloud's IAM, Security services, Cloud APIs, Network services and Computing & migration to Google Cloud.

An Associate Cloud Engineer deploys and secures applications and infrastructure, monitors operations of multiple projects, and maintains enterprise solutions to ensure that they meet target performance metrics. This individual has experience working with public clouds and on-premises solutions. They are able to use the Google Cloud console and the command-line interface to perform common platform-based tasks to maintain and scale one or more deployed solutions that leverage Google-managed or self-managed services on Google Cloud.

Course Objectives:

This Google Cloud Platform training course builds the skills needed to be successful in a cloud architect role. By the end of this training, you’ll be able to:

  • Master Google Cloud platform fundamentals and terminologies.
  • Design and plan a cloud solution architecture
  • Manage and provision Google Cloud solutions
  • Implement Google cloud architecture
  • Develop and deploy  Google Cloud solutions
  • Manage GCP services using the app, CLI and console
  • Understand Machine Learning services in GCP
  • Work with the Compute Engine, Cloud SQL, Cloud Storage, and Big Query GCP services.

Course content


What is Cloud Computing? and Why GCP?
  • What is traditional IT environment and how it works?
  • Servers, storage, network in traditional IT
  • What is cloud computing?
  • Basic architecture of cloud computing
  • Difference between traditional IT and Cloud computing
  • Advantages of cloud computing
  • Deployment Model and service model
  • Private, Public and hybrid Cloud
  • Why google cloud? And its exclusive benefits
  • GCP locations
  • Gartners Magic quadrant and market share
Cloud Computing and Basic Concepts
  • Different cloud providers
  • Regions and zones
  • GCP interfaces
  • Lab: Google cloud shell overview
  • How to create GCP account
  • Lab: GCP console overview and navigations
  • Organizations, folders, project and resources
  • Lab: Setting up Billing and alerts
IAM – Identity and Access Management
  • Basic concepts of IAM
  • Organizations, Roles, members, service accounts, policy
  • Policy hierarchy
  • Understanding of different roles and permission
  • IAM Best practices
  • Lab: Assigning various roles and test
  • Lab: Create service account and assign role
Compute Engine
  • Overview of Virtual machine
  • Life cycles of VM instances
  • Access options
  • Lab: Creation of Linux and windows VM instances
  • Different Machine types
  • Preemptible and sole tenant VMs
  • Images
  • Machine images
  • Live migration and auto restart
  • Types of disks, Local SSD, persistent disk and balanced persistent disk
  • Lab: Adding new disk and mount in OS
  • Lab: Deleting VM and recreate using disk
  • Snapshots
  • firewall Rules
  • Pricing criteria and discounts
  • Lab: Creating snapshot and snapshot schedules
  • Lab: Recover using snapshot
  • Lab: Compute engine activities in gcloud shell
Storage: Google Cloud Storage (GCS)
  • Overview of object storage (GCS)
  • Features and use cases of GCS
  • Structure of GCS
  • Bucket name standards
  • Lab: Creation of bucket and upload object
  • Lab: Setting IAM and ACL permission on bucket
  • Storage classes
  • Versioning
  • Life cycle policies
  • Pricing
  • Lab: Versioning and Life cycle policies
  • Lab: GCS using gcloud
Networking Basics
  • Why interconnecting compute devices is necessary?
  • SOHO networks
  • LAN and WAN
  • OSI Model
  • Overview and traffic flow in layers
  • TCP/IP protocol
  • IP address
  • Subnet mask
  • CIDR notation
  • Broadcast and default gateway
  • NAT
Load Balancing and Autoscaling
  • Overview and features of GCP load balancer
  • Types of load balancers
  • Global and regional load balancers
  • External and internal load balancers
  • technology behind LB
  • Internal/external https load balancing
  • Internal TCP/UDP load balancing
  • SSL/TCP proxy load balancing
  • Components of LB
  • Auto scaling
  • Managed and unmanaged instance groups
  • Lab: Create external http global load balancer with autoscaling
VPC (Virtual Private Cloud)
  • Overview and features of VPC
  • Types of VPC – default / automode and custom VPC
  • VPC Components
  • Internal and external IPs
  • Routes
  • Firewall
  • Shared VPC
  • VPC peering
  • NAT Gateway
  • Pricing criteria
  • Lab: Creation of Auto mode VPC
  • Lab: Creation of Custom VPC
  • Lab: Creating subnets (LAB)
  • Lab: Distributing VM instances in different subnets
  • Lab: Creation of firewall rules
  • Lab: VPC peering
  • Lab: NAT gateway
Cloud SQL
  • Overview of relational and nonrelational database
  • Types of cloud SQL databases
  • Cloud MySQL
  • Cloud PostgreSQL
  • SQL server
  • Components of MySQL
  • HA SQL
  • Lab: Create SQL instance
  • Lab: Create HA SQL
  • Replication
  • Backups
Cloud Spanner
  • Overview of cloud spanner
  • Comparison with traditional databases
  • Features
  • Architecture – regional and global
  • Replication
  • Backup and restore
  • Lab: Creation of cloud spanner instance, loading database and query
BigData And Other Database/Storage Services
  • Cloud firestore / Datastore
  • Data model of firestore
  • Data, document and collection
  • Overview and features of DataProc
  • Use cases
  • Customers
MemCache (Redis)
  • Introduction to Redis
  • Introduction to MemCache
  • Lab: Creating MemCache Instance
  • Challenges of transitional data handling
  • Overview and features of Bigtable
  • Lab: Creating a cluster
  • Use cases
  • What is data warehousing
  • Features
  • Pricing criteria
  • Overview of data streaming
  • Architecture of data flow
  • Features
Cloud Pub/Sub
  • Overview of messaging and injection
  • How pub/sub works
  • Features
  • Topics subscription and message
  • Use cases
  • Lab: Creation of topic and publish
Compute Services – Others
App Engine
  • Overview of App engine
  • Service, versions of app engine
  • Standard and flexible environments
  • Architecture
  • Types of scaling
  • Lab: Create app engine using python code
  • Deploy new version of App engine
  • Test Autoscaling in App engine
Cloud functions
  • Overview and use cases of cloud functions
  • Features and use cases
  • Creation of cloud functions
  • Lab: Create function to blur offensive images
Cloud Run
  • Cloud run on containerization
  • Service and revisions
  • Use cases
  • Lab: Creating cloud Run instance and run hello world
Management Tools
Cloud monitoring and logging
  • Overview of cloud monitoring and logging
  • Metrix, logs
  • Log management
  • Error reporting
  • Health check monitoring and Alert mechanism
  • Lab: Creating Metrix and alerts
  • Lab: Setting up monitoring on different resources
Cloud deployment manager
  • Overview of deployment manager
  • Working with deployment manager
  • Lab: Create instance using Deployment manager
GKE (Google Kubernetes Engine)
  • What is a microservice
  • What is a container
  • What is docker and docker images
  • Container optimized OS and Container registry
  • Lab: Run WordPress on docker
  • Lab: Create a Microservice, then image and run on docker
  • what is Kubernetes
  • Kubernetes Architecture
  • Understanding of nodes
  • Understanding of cluster
  • Lab: Create Kubernetes cluster
  • Lab: Run WordPress on Kubernetes and expose outside
  • Understanding pods
  • Understanding services
  • Understanding replication controllers
  • Understanding deployments
  • Understanding yaml files
  • Understanding Kustomize
  • Managing deployments using Kustomize
  • Lab: Create guestbook application which include frontend deployment, backed redis master and slave deployments
  • Lab: Test scale up and scale down of pods
  • Lab: Upgrade and downgrade pod version


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Course Prerequisites

  • Google cloud infrastructure hasn’t specified any mandatory prerequisites to get started with Google cloud training. But it is recommended to have a basic understanding of Google cloud architecture and how it works, to help you master it in a short time.
  • Basic understanding of computer science and information technology concepts.
  • Google cloud platform account.

Who can attend


This Google Cloud Platform Architect course is best suited for:

  • Software developers
  • IT professionals
  • Cloud solutions architects
  • Network administrators
  • DevOps engineers
  • Anyone who wants to enhance their skills with Google Cloud Platform Architecture

Number of Hours: 40hrs


GCP Associate Cloud Engineer (ACE)

Key features

  • One to One Training
  • Online Training
  • Fastrack & Normal Track
  • Resume Modification
  • Mock Interviews
  • Video Tutorials
  • Materials
  • Real Time Projects
  • Virtual Live Experience
  • Preparing for Certification


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  • Online Training
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  • Resume Modification
  • Mock Interviews
  • Video Tutorials
  • Materials
  • Real Time Projects
  • Materials
  • Preparing for Certification

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