This blog post gives a walkthrough of the Step-By-Step Activity Guides of the Google Cloud Associate Cloud Engineer Certification Training program that you must perform to learn this course. To know more about the certification read our blog Google Associate Cloud Engineer (GCP): All You Need To Know About
The Google Cloud Associate Cloud Engineer exams mesh towards those who are interested in fundamental skills of deploying, monitoring, and maintaining projects on Google Cloud and want to start their career in it. It can be used as a path to professional-level certifications.
The walkthrough of the Step-By-Step Activity Guides of the Google Cloud Associate Clou Engineer Training program will prepare you thoroughly for this certification.
The hands-on list is as follows:
- Register for Google Cloud Free-Trial Account
- Google Cloud Console & Cloud Shell Overview and Navigation
- Setting up Projects
- Set Billing budgets & Alerts in GCP
- Install & Initialize Google Cloud SDK
- Add IAM User & Assign Various Roles
- Creation of Auto-mode VPC
- Creation of Custom-mode VPC
- Create Firewall Rules
- Bastion Host / CloudNAT
- Create Linux and Windows VM instances in Google Cloud Console
- Working With Images
- Working With Snapshots
- Compute Engine Activities in gcloud Shell
- Create Bucket & Upload Objects
- Set IAM & ACL Permissions
- Create & Delete Lifecycle Policy for a Cloud Storage Bucket
- Move Objects Between Cloud Storage Buckets
- Create Google Cloud SQL Instance
- Create Google Cloud SQL Database
- Create & Manage Cloud Spanner Instances
- Design Cloud Bigtable Schema
- Create & Manage Cloud Bigtable Instances
- Create a Kubernetes Cluster
- Working with Node pools, pods, services
- Deploy a container application to Google Kubernetes Engine using pods
- Deploy a Simple Web Server Containerized Application to a GKE Cluster
- Deploy a simple web application using App Engine
- Create & Deploy a Python Cloud Function using Google Cloud Console
- Billing Administration
- Examining Billing Data with BigQuery
- Installing Stackdriver agent for Resource Monitoring
- Error Reporting and Debugging with Stackdriver
- Create HTTP Load Balancer
- Autoscaling and Load Balancing
- Deployment Manager
Let’s take a quick sneak-peek in these labs to get an overview of the course requirements
1.) Register for Google Cloud Free-Trial Account
Before starting with the labs we will require a Google Cloud Account to get started where we can create VM, Kubernetes cluster, cloud storage, etc.
Google Cloud Platform (GCP) is providing 90 days of Free Trial account with $300 credits to new subscribers to get hands-on experience with all the Google cloud services.
To Create a Google Cloud Free-trial account follow the steps from the blog Google Cloud Free Account
2.) Google Cloud Console & Cloud Shell Overview and Navigation
This lab covers the navigation of Google Cloud Console & Cloud Shell and how to activate cloud shell in the Google Cloud Platform.
To know more about Google Cloud Platform read the blog at Introduction to Google Cloud Platform
The Cloud Console enables you to perform basic storage management tasks with your data using a browser.
Cloud Shell is an in-browser command prompt execution environment that allows you to enter commands at a terminal prompt in order to manage resources and services in your Google Cloud project.
3.) Setting Up Projects
A project organizes all the Google Cloud resources. It consists of a set of users, APIs, billing, authentication, and monitoring settings for those APIs.
This guide covers how to set up a project for an experiment in the Google Cloud Platform.
4.) Set Billing Budgets & Alerts in GCP
A Cloud Billing account defines who pays for a given set of Google Cloud resources. To use Google Cloud services, users must have a valid Cloud Billing account and must be linked to the Google Cloud projects. This guide covers how to set a billing budget and get alerts when the budget amount is reached or crossed. A budget enables you to track your actual Google Cloud spend against your planned spend.
5.) Install and Initialize Google Cloud SDK
Google Cloud SDK is a set of tools and libraries used for managing applications and resources that are hosted on the Google Cloud Platform. It is composed of the gsutil, gcloud, and bqcommand line tools.
In this lab, we are going to install and configure the Google Cloud SDK command-line interface in our systems.
6.) Add IAM User & Assign Various Roles
Identity and Access Management (IAM) lets you create and manage permissions for Google Cloud resources. IAM unifies access control for Google Cloud services into a single system and presents a consistent set of operations.
In this lab, we will focus on adding a user to a project and assign various roles to the added user.
7.) Creation Of Auto-mode VPC
Google Cloud offers two types of VPC networks, determined by their subnet creation mode:
- Auto-mode VPC
- Custom mode VPC
In this lab, we are going to create an auto-mode VPC, where one subnet from each region is automatically created within it. The automatically created subnets use a set of predefined IP ranges that fit within the 10.128.0.0/9 CIDR block.
8.) Creation Of Custom-mode VPC
When a custom mode network is created, no subnets are created automatically and users have complete control over the custom network’s subnets and IP ranges.
In this lab, we will create a custom-mode VPC using Cloud Console and check the connection by creating a VM instance in Compute Engine.
9.) Create Firewall Rules
VPC firewall rules let the users allow or deny connections to or from their virtual machine (VM) instances based on the configuration specified by them.
This lab describes the step to create firewall rules for egress and ingress traffic flow.
10.) Bastion Host/ Cloud NAT
This guide covers the steps to securely connect to compute virtual machine instances using Bastion host key/Cloud NAT gateway.
11.) Create Linux and Windows VM instances in Google Cloud Console
Compute Engine instances can run the public images for Linux and Windows Server that Google provides as well as private custom images that you can create or import from your existing systems.
This lab focuses on creating Linux and Windows server VM instances in Compute Engine using the Google Cloud Console.
To know more about Google Compute Engine read the blog Introduction To Google Compute Engine.
12.) Working With Images
Google Compute Engine uses operating system images to create the root persistent disks for the instances. It is specified when an instance is created.
This guide covers the steps to create an image from a VM or a snapshot, view images, and delete an image.
13.) Working With Snapshots
Snapshots are global resources, which can be used to restore data to a new disk or instance within the same project.
The lab includes creating a snapshot from a VM, viewing snapshots, and deleting a snapshot.
14.) Compute Engine Activities In gcloud Shell
The gcloud command-line tool helps in managing the Compute Engine resources, using the gcloud compute command group. It is an alternative to using the Compute Engine API.
This lab covers the compute engine activities in the cloud shell-like creating a VM instance, deleting the VM instance, etc.
15.) Create Bucket And Upload Objects
Buckets are the basic containers that hold the data so, everything that is stored in Cloud Storage must be contained in a bucket. Objects are individual pieces of data that can be stored in Cloud Storage.
Read the blog on Google Cloud Storage Service to learn more about it.
This lab guides you to create a storage bucket in cloud storage and uploading objects to the bucket.
16.) Set IAM & ACL Permissions
This lab covers how to set access control and IAM permissions to the Cloud Storage buckets and objects and what level of access they can have.
17.) Create & Delete Lifecycle Policy For A Cloud Storage Bucket
Lifecycle management configuration can be applied to a bucket. The configuration contains a set of rules which apply to current and future objects in the bucket. So, when an object meets the criteria of one of the rules, Cloud Storage automatically performs a specified action on the object, for example, delete objects created before April 1, 2020.
18.) Move Objects Between Cloud Storage Buckets
This guide covers how to move or copy the objects between different Google Cloud Storage Buckets.
19.) Create Google Cloud SQL Instance
Cloud SQL provides a cloud-based alternative to local MySQL, PostgreSQL, and SQL Server databases.
This guide describes the steps to create and manage the cloud SQL instance in Google Cloud Console.
20.) Create Google Cloud SQL Database
This lab guides us through the process of creating, listing, and deleting MySQL databases on a Cloud SQL instance.
21.) Create And Manage Cloud Spanner Instances
To get started with Cloud Spanner, we must first create a Cloud Spanner instance within our Google Cloud project. This instance is an allocation of resources that are used by Cloud Spanner databases created in that instance.
This lab covers the steps to create and manage the Cloud Spanner Instances in Google Cloud using Google Cloud Console and gcloud commands.
22.) Design Cloud Bigtable Schema
In Cloud Bigtable, a schema is a blueprint or model of a table, including the structure of the row keys, Column families, and column table components. In this lab, we will learn how to create a schema and the best practices for designing the schema.
23.) Create & Manage Cloud Bigtable Instances
This lab covers the steps to create and manage Cloud Bigtable instances. A Cloud Bigtable instance is a container for the data. It has one or more clusters, located in different zones and each cluster has at least 1 node.
24.) Create A Kubernetes Cluster
Cluster is the foundation of Google Kubernetes Engine (GKE). The Kubernetes objects that represent the containerized applications all run on top of a cluster.
This guide covers the steps to create different types of clusters like Zonal, regional, private, etc.
25.) Working with Node pools, Pods, Services
This lab covers the steps to create and manage node pools, pods, and services in Google Kubernetes Cluster.
- A node pool is a group of nodes within a cluster that all have the same configuration.
- Pods are the smallest and most basic deployable objects in Kubernetes. They represent a single instance of a running process in the cluster.
26.) Deploy a Container Application To Google Kubernetes Engine Using Pods
This guide covers the steps to deploy a containerized applications using Pods (smallest and basic deployable objects in Kubernetes) using Google Kubernetes Engine (GKE).
27.) Deploy a Simple Web Server Containerized Application To A GKE Cluster
This lab covers the steps of how to package a web application in a Docker container image, and run that container image on a Google Kubernetes Engine (GKE) cluster.
28.) Deploy A Simple Web Application Using App Engine
App Engine is a fully managed, serverless platform for developing and hosting web applications at scale. The lab focuses on the steps to deploy a web application using App Engine in Google Cloud Shell.
Read the blog Overview Of Google App Engine to know more about it in detail.
29.) Create & Deploy A Python Cloud Function Using Google Cloud Console
This guide takes you through the process of writing a Cloud Function using the Python runtime. Cloud Functions is a serverless execution environment for building and connecting cloud services.
30.) Billing Administration
Cloud Billing lets you control which users have administrative and cost viewing permissions for specified resources by setting Identity and Access Management (IAM) policies on the resources. This guide covers the core aspects of billing like how to manage billing of projects, cloud billing roles in IAM, manage various billing account, etc.
31.) Examining Billing Data With BigQuery
BigQuery is Google’s serverless, highly scalable enterprise data warehouse designed to make data analysts more productive with unmatched price-performance.
In this lab, we will learn how to use BigQuery to examine sample Cloud Billing records.
32.) Installing Stackdriver Agent For Resource Monitoring
Stackdriver Monitoring agent is used to monitor Virtual Machines, which is a collection-based daemon that collects system and application metrics from virtual machine instances. This lab covers the steps to install the monitoring agent on a Compute Engine VM.
33.) Error Reporting And Debugging With Stackdriver
This lab takes you through the process of setting error reporting and debugging on the instances created using a Stackdriver.
34.) Create HTTP Load Balancer
This setup guide shows you how to create a simple HTTP load balancer. A load balancer distributes user traffic across multiple instances of your applications.
35.) Autoscaling And Load Balancing
Google Cloud offers load balancing and autoscaling for groups of instances. In this guide, we are going to look at the concepts of Autoscaling and Load Balancing and steps to auto scale a compute VM instance.
36.) Deployment Manager
Cloud Deployment Manager is an infrastructure deployment service that automates the creation and management of Google Cloud resources.
This guide gives a walkthrough of how to get started with the Google Cloud Deployment Manager and automate infrastructure.
So these are the labs/hands-on guides that are important for understanding the concepts of the Google Cloud and will help in clearing the Google Cloud Associate Cloud Engineer Certification.
Related References
- GCP Associate Cloud Engineer: All You Need To Know About
- GCP Professional Cloud Architect: Everything You Need To Know
- Introduction To Google Cloud Platform
- Google Cloud Services & Tools
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If you are also interested and want to know more about the Google Cloud Associate Cloud Engineer certification then register for our Free Class.
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