Google Associate(GCP) Cloud Certification Training

>>Student Testimonial<<

Hi Sanjeev! I passed! Couldn’t believe it. Your training made certification so easy for me! Thank you for everything. - Jhon 

**Highlights**

Practical Hands-On | Instructor-led & Guided | LIVE Interactive class with many other students participating

January 8, 2022 - February 27, 2022 for 32 hours over 8 weekends, 16 sessions, 2 sessions per weekend, 2 hours per session.

Training material | Lab exercises | Training session recordings

All Published Ticket Prices are in US Dollars

The course will be taught in English language

8 Weekends Google Associate (GCP) Cloud Certification Prep. Training Course Weekly Schedule

January 8, 2022 - February 27, 2022 US Pacific time

32 Hours | 2 Hours on Saturdays, 2 Hours on Sundays every weekend IST

11:00 AM - 1:00 PM US IST each of those days

Please click here to add your city name and check your local date and time for the first session to be held on January 8, 2022 

8 Weekends | 16 Sessions | 2 Sessions per weekend | 2 hours per session

32 Hours of total Instructor-led and guided training

Training material, instructor handouts and access to useful resources on the cloud provided

Practical Hands-on Lab exercises provided

Real-life Scenarios

Course taught by Certified Trainer who is also Certified Google Associate Cloud engineer

Unlimited Repeat of this course for upto 1 year or until you pass the Google Associate Cloud Engineer Certification exam.

Course Overview

This course prepares you to become Google Associate Cloud Engineer who deploys applications, 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 Google Cloud Console and the command-line interface to perform common platform-based tasks to maintain one or more deployed solutions that leverage Google-managed or self-managed services on Google Cloud.

Audience profile

Those who want to become Google Associate Cloud Engineers

Those preparing for the Google Associate Cloud Engineer exam

Prerequisites

Basic understanding of Google Cloud Platform products and services

Basic understanding of cloud concepts such as virtual machines, containers, and networking

Course Outline

1. Setting up a cloud solution environment

1.1 Setting up cloud projects and accounts. Activities include:

Creating projects

Assigning users to predefined IAM roles within a project

Managing users in Cloud Identity (manually and automated)

Enabling APIs within projects

Provisioning one or more Stackdriver workspaces

1.2 Managing billing configuration. Activities include:

Creating one or more billing accounts

Linking projects to a billing account

Establishing billing budgets and alerts

Setting up billing exports to estimate daily/monthly charges

1.3 Installing and configuring the command line interface (CLI), specifically the Cloud SDK (e.g., setting the default project).

2. Planning and configuring a cloud solution

2.1 Planning and estimating GCP product use using the Pricing Calculator

2.2 Planning and configuring compute resources. Considerations include:

Selecting appropriate compute choices for a given workload (e.g., Compute Engine, Google Kubernetes Engine, App Engine, Cloud Run, Cloud Functions)

Using preemptible VMs and custom machine types as appropriate

2.3 Planning and configuring data storage options. Considerations include:

Product choice (e.g., Cloud SQL, BigQuery, Cloud Spanner, Cloud Bigtable)

Choosing storage options (e.g., regional, multi-regional, nearline, coldline)

2.4 Planning and configuring network resources. Tasks include:

Differentiating load balancing options

Identifying resource locations in a network for availability

Configuring Cloud DNS

3. Deploying and implementing a cloud solution

3.1 Deploying and implementing Compute Engine resources. Tasks include:

Launching a compute instance using Cloud Console and Cloud SDK (gcloud) (e.g., assign disks, availability policy, SSH keys)

Creating an autoscaled managed instance group using an instance template

Generating/uploading a custom SSH key for instances

Configuring a VM for Stackdriver monitoring and logging

Assessing compute quotas and requesting increases

Installing the Stackdriver Agent for monitoring and logging

3.2 Deploying and implementing Google Kubernetes Engine resources. Tasks include:

Deploying a Google Kubernetes Engine cluster

Deploying a container application to Google Kubernetes Engine using pods

Configuring Google Kubernetes Engine application monitoring and logging

3.3 Deploying and implementing App Engine, Cloud Run, and Cloud Functions resources. Tasks include, where applicable:

Deploying an application, updating scaling configuration, versions, and traffic splitting

Deploying an application that receives Google Cloud events (e.g., Cloud Pub/Sub events, Cloud Storage object change notification events)

3.4 Deploying and implementing data solutions. Tasks include:

Initializing data systems with products (e.g., Cloud SQL, Cloud Datastore, BigQuery, Cloud Spanner, Cloud Pub/Sub, Cloud Bigtable, Cloud Dataproc, Cloud Dataflow, Cloud Storage)

Loading data (e.g., command line upload, API transfer, import/export, load data from Cloud Storage, streaming data to Cloud Pub/Sub)

3.5 Deploying and implementing networking resources. Tasks include:

Creating a VPC with subnets (e.g., custom-mode VPC, shared VPC)

Launching a Compute Engine instance with custom network configuration (e.g., internal-only IP address, Google private access, static external and private IP address, network tags)

Creating ingress and egress firewall rules for a VPC (e.g., IP subnets, tags, service accounts)

Creating a VPN between a Google VPC and an external network using Cloud VPN

Creating a load balancer to distribute application network traffic to an application (e.g., Global HTTP(S) load balancer, Global SSL Proxy load balancer, Global TCP Proxy load balancer, regional network load balancer, regional internal load balancer)

3.6 Deploying a solution using Cloud Marketplace. Tasks include:

Browsing Cloud Marketplace catalog and viewing solution details

Deploying a Cloud Marketplace solution

3.7 Deploying application infrastructure using Cloud Deployment Manager. Tasks include:

Developing Deployment Manager templates

Launching a Deployment Manager template

4. Ensuring successful operation of a cloud solution

4.1 Managing Compute Engine resources. Tasks include:

Managing a single VM instance (e.g., start, stop, edit configuration, or delete an instance)

SSH/RDP to the instance

Attaching a GPU to a new instance and installing CUDA libraries

Viewing current running VM inventory (instance IDs, details)

Working with snapshots (e.g., create a snapshot from a VM, view snapshots, delete a snapshot)

Working with images (e.g., create an image from a VM or a snapshot, view images, delete an image)

Working with instance groups (e.g., set autoscaling parameters, assign instance template, create an instance template, remove instance group)

Working with management interfaces (e.g., Cloud Console, Cloud Shell, GCloud SDK)

4.2 Managing Google Kubernetes Engine resources. Tasks include:

Viewing current running cluster inventory (nodes, pods, services)

Browsing the container image repository and viewing container image details

Working with node pools (e.g., add, edit, or remove a node pool)

Working with pods (e.g., add, edit, or remove pods)

Working with services (e.g., add, edit, or remove a service)

Working with stateful applications (e.g. persistent volumes, stateful sets)

Working with management interfaces (e.g., Cloud Console, Cloud Shell, Cloud SDK)

4.3 Managing App Engine and Cloud Run resources. Tasks include:

Adjusting application traffic splitting parameters

Setting scaling parameters for autoscaling instances

Working with management interfaces (e.g., Cloud Console, Cloud Shell, Cloud SDK)

4.4 Managing storage and database solutions. Tasks include:

Moving objects between Cloud Storage buckets

Converting Cloud Storage buckets between storage classes

Setting object life cycle management policies for Cloud Storage buckets

Executing queries to retrieve data from data instances (e.g., Cloud SQL, BigQuery, Cloud Spanner, Cloud Datastore, Cloud Bigtable)

Estimating costs of a BigQuery query

Backing up and restoring data instances (e.g., Cloud SQL, Cloud Datastore)

Reviewing job status in Cloud Dataproc, Cloud Dataflow, or BigQuery

Working with management interfaces (e.g., Cloud Console, Cloud Shell, Cloud SDK)

4.5 Managing networking resources. Tasks include:

Adding a subnet to an existing VPC

Expanding a subnet to have more IP addresses

Reserving static external or internal IP addresses

Working with management interfaces (e.g., Cloud Console, Cloud Shell, Cloud SDK)

4.6 Monitoring and logging. Tasks include:

Creating Stackdriver alerts based on resource metrics

Creating Stackdriver custom metrics

Configuring log sinks to export logs to external systems (e.g., on-premises or BigQuery)

Viewing and filtering logs in Stackdriver

Viewing specific log message details in Stackdriver

Using cloud diagnostics to research an application issue (e.g., viewing Cloud Trace data, using Cloud Debug to view an application point-in-time)

Viewing Google Cloud Platform status

Working with management interfaces (e.g., Cloud Console, Cloud Shell, Cloud SDK)

5. Configuring access and security

5.1 Managing identity and access management (IAM). Tasks include:

Viewing IAM role assignments

Assigning IAM roles to accounts or Google Groups

Defining custom IAM roles

5.2 Managing service accounts. Tasks include:

Managing service accounts with limited privileges

Assigning a service account to VM instances

Granting access to a service account in another project

5.3 Viewing audit logs for project and managed services.

>>Student Testimonial<<

Hi Sanjeev! I passed! Couldn’t believe it. Your training made certification so easy for me! Thank you for everything. - Jhon 

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