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GCP Essentials
In this introductory-level quest, you will get hands-on practice with the Google Cloud Platform’s fundamental tools and services. GCP Essentials is Qwiklabs’ most popular quest and for good reason—you will come in with little, or no prior cloud knowledge and come out with practical experience that you can apply to any GCP project. From writing Cloud Shell commands and deploying your first virtual machine, to running applications on Kubernetes Engine with load balancing, GCP Essentials is a prime introduction to the platform’s features.
Baseline: Infrastructure
If you are a novice cloud developer looking for hands-on practice with GCP’s core infrastructure services, do yourself a favor and enroll in this quest. As a student, you will get practical experience by taking labs that dive into Cloud Storage, computing engines like Kubernetes, and key application services like Stackdriver and Deployment Manager. By taking this quest, you will develop invaluable skills that apply to any GCP project.
Baseline: Data, ML, AI
Big data, machine learning, and artificial intelligence are today’s hot computing topics, but these fields are quite specialized and introductory material is hard to come by. Fortunately, GCP provides user-friendly services in these areas and Qwiklabs has you covered with this introductory-level quest, so you can take your first steps with tools like Big Query, Cloud Speech API, and Cloud ML Engine. Want extra help? 1-minute videos walk you through key concepts for each lab.
Baseline: Deploy & Develop
In this introductory-level quest, you will learn the fundamentals of developing and deploying applications on the Google Cloud Platform. You will get hands-on experience with the Google App Engine framework by launching applications written in languages like Python, Ruby, and Java (just to name a few). You will see first-hand how straightforward and powerful GCP application frameworks are, and how easily they integrate with GCP database, data-loss prevention, and security services.
Cloud Architecture
This advanced-level quest is unique amongst the other Qwiklabs offerings. The labs have been curated to give developers hands-on practice with topics and services that appear in the Google Cloud Certified Professional Cloud Architect Certification. From IAM, to networking, to Kubernetes engine deployment, this quest is composed of specific labs that will put your GCP architecture knowledge to the test. Be aware that while practice with these labs will increase your knowledge and abilities, you will need other preparation too. The exam is quite challenging and external studying, experience, and/or background in cloud architecture is recommended.
Data Engineering
This advanced-level quest is unique amongst the other Qwiklabs offerings. The labs have been curated to give developers hands-on practice with topics and services that appear in the Google Cloud Certified Professional Data Engineer Certification. From Big Query, to Dataproc, to Tensorflow, this quest is composed of specific labs that will put your GCP data engineering knowledge to the test. Be aware that while practice with these labs will increase your knowledge and abilities, you will need other preparation too. The exam is quite challenging and external studying, experience, and/or background in cloud data engineering is recommended.
VPC Networking Fundamentals
In this lab, you create an auto-mode VPC network with firewall rules and 2 VM instances. Then, you explore the connectivity for the VM instances.
Using VPC Network Peering
In this lab, you configure VPC Network Peering between two networks. Then, you verify private communication between two VMs in those networks.
App Dev: Storing Image and Video Files in Cloud Storage - Python
In this lab, you add images and video to an application. You store files as objects in a Cloud Storage bucket.
Exploratory Data Analysis using Google Cloud Datalab
Learn the process of analyzing a data set stored in BigQuery using Cloud Datalab to perform queries and present the data using various statistical plotting techniques.
Using a NAT Gateway with Kubernetes Engine
This lab shows how to define new node IP address mappings by using network address translation (NAT) gateways.
Awwvision: Cloud Vision API from a Kubernetes Cluster
This hands-on-lab uses Kubernetes and Cloud Vision API to create an example of how to use the Vision API to classify (label) images from Reddit’s /r/aww subreddit and display the labelled results in a web app.
Terraform Fundamentals
In this hands-on-lab you will create infrastructure, a virtual machine, using Terraform in the cloud environment.
HTTPS Content-Based Load Balancer with Terraform
This lab shows you how to create a HTTPS load balancer to forward traffic to a custom URL map, which then sends traffic to the region closest to you with static assets being served from a Cloud Storage bucket.
App Dev: Adding User Authentication to your Application - Python
In this lab, you will enhance the online Quiz application to use Firebase authentication.
Deploy Kubernetes Load Balancer Service with Terraform
In Terraform, a Provider is the logical abstraction of an upstream API. This lab will show you how to setup a Kubernetes cluster and deploy Load Balancer type Nginx service on it.
Modular Load Balancing with Terraform - Regional Load Balancer
This lab will demonstrate how to use the Regional Load Balancer GCP Terraform modules for setting up various load balancers.
Loading Data into Google BigQuery for Exploratory Data Analysis
You will learn how to load text data into Google BigQuery and then use that data for rapid exploratory data analysis using Google Cloud Datalab notebooks.
Using Ruby on Rails with Cloud SQL for PostgreSQL
In this lab, you'll learn how to deploy a new Ruby on Rails application using Google Cloud SQL for PostgreSQL to Google App Engine Flexible environment.
VPC Networks - Controlling Access
In this lab, you create two nginx web servers and control external HTTP access to the web servers using tagged firewall rules. Then, you explore IAM policies and service accounts.
Scanning User-generated Content Using the Cloud Video Intelligence and Cloud Vision APIs
This lab will show you how to deploy a set of Cloud Functions in order to process images and videos with the Cloud Vision API and Cloud Video Intelligence API.
Building High Availability and High Bandwidth NAT Gateways
This lab shows you how to set up multiple NAT gateways with Equal Cost Multi-Path (ECMP) routing and autohealing enabled for a resilient and high-bandwidth deployment.
Detect Labels, Faces, and Landmarks in Images with the Cloud Vision API
The Cloud Vision API lets you understand the content of an image by encapsulating powerful machine learning models in a simple REST API. In this lab you’ll send an image to the Cloud Vision API and have it identify objects, faces, and landmarks.
Rent-a-VM to Process Earthquake Data
In this lab you spin up a virtual machine, configure its security, access it remotely, and then carry out the steps of an ingest-transform-and-publish data pipeline manually. This lab is part of a series of labs on processing scientific data.
App Dev: Developing a Backend Service - Python
In this lab, you will enhance the online Quiz application by developing a backend service to process user feedback and save scores.
Creating a Persistent Disk
In this hands-on lab, you’ll learn how to create a persistent disk and use it on a Google Compute Engine virtual machine. You’ll also learn about zones, regions, and different disk types.
Cloud Source Repositories: Qwik Start
In this lab you will create a local Git repository that contains files for a sample App Engine application, add a GCP repository as a remote, and push the contents of the local repository.
Creating a Custom Machine Type with Terraform
In this lab you'll create an instance with a custom machine type, a bastion host, and a NAT gateway using Terraform.
Entity and Sentiment Analysis with the Natural Language API
The Cloud Natural Language API lets you extract entities, and perform sentiment and syntactic analysis on a block of text. In this hands-on lab you’ll learn how to extract entities and sentiment from text using the Cloud Natural Language API.
Internal Load Balancer
Internal Load Balancer offers you the possibility to load balance TCP/UDP traffic without exposing your VMs via a public IP to the Internet. In this lab we will create a public facing web server to serve the result of a simple web application.
Cloud SQL with Terraform
In this hands-on lab you will learn to create Cloud SQL instances with Terraform, thenset up the Cloud SQL Proxy, testing the connection with both MySQL and PostgreSQL clients.
Evaluating a Data Model
Learn the process for partitioning a data set into a training set that will be used to develop a model, and a test set that can then be used to evaluate the accuracy of the model and then independently evaluate predictive models in a repeatable manner.
Multiple VPC Networks
In this lab, you create several VPC networks and VM instances and test connectivity across networks.
Using Kubernetes Engine to Deploy Apps with Regional Persistent Disks
In this lab you will learn how to configure a highly available application by deploying WordPress using regional persistent disks on Kubernetes Engine.
VPC Network Peering
Google Cloud Platform (GCP) Virtual Private Cloud (VPC) Network Peering allows private connectivity across two VPC networks regardless of whether or not they belong to the same project or the same organization.
Cloud Security Scanner: Qwik Start
The Cloud Security Scanner identifies security vulnerabilities in your Google App Engine web applications.
Deploy a Ruby on Rails App to App Engine Flexible Environment
In this lab, you will learn how to deploy a new Ruby on Rails application or Rails app for short to Google App Engine Flexible environment. You will learn Cloud Shell and the Cloud SDK to get started without needing any downloads or installs.
Dynamic VPN Gateways - Cloud Routers
In this lab you connect two networks using Cloud Routers. Cloud Routers build on top of VPN by enabling BGP Routing that dynamically discovers changes in network topology and passes updates to peers.
Google Maps Web Services Proxy for Mobile Applications
In this lab, you'll build a Google App Engine proxy for the Google Places API web service.
Setting up Jenkins on Kubernetes Engine
This hands-on lab will show you how to set up Jenkins on Google Kubernetes Engine to help orchestrate your software delivery pipeline.
Create a Custom Network Using Deployment Manager
This lab creates a complex Deployment Manager (DM) configuration for deploying a custom network resource in Google Cloud Platform. It also explains the basic fundamental block of developing a Deployment Manager.
Networking 101
In this lab you will learn how to perform basic networking tasks on Google Cloud Platform by setting up a network and 3 subnetworks; and how GCP might differ from an on-premises setup.
App Dev: Setting up a Development Environment - Java
In this lab, you will provision a Google Compute Engine virtual machine and install software libraries for software development.
Provision Services with Cloud Launcher
In this hands-on lab you'll learn how to use Cloud Launcher to quickly get started with common operating systems, web frameworks, and databases.
Managing Deployments Using Kubernetes Engine
Dev Ops best practices make use of multiple deployments to manage application deployment scenarios. This lab provides practice in scaling and managing containers to accomplish common scenarios where multiple heterogeneous deployments are used.
BigQuery: Qwik Start - Command Line
This hands-on lab shows you how to query public tables and load sample data into BigQuery using the Command Line Interface. Watch the short videos Get Meaningful Insights with Google BigQuery and BigQuery: Qwik Start - Qwiklabs Preview.
Running Distributed TensorFlow on Compute Engine
This lab shows you how to use a distributed configuration of TensorFlow on multiple Compute Engine instances to train a convolutional neural network model using the MNIST dataset.
App Dev: Setting up a Development Environment - Python
In this lab, you will provision a Google Compute Engine virtual machine and install software libraries for software development.
Running a Node.js Container in Kubernetes with Container Engine
Containers are becoming a popular way to run and scale applications across multiple cloud providers or on both cloud and on premise hardware. This lab provides a quick introduction to running a website on Google Container Engine using Docker.
Deployment Manager - Package and Deploy
In this lab you will develop an advanced Deployment Manager template using JINJA and YAML. You will learn how to install and run a Python application on an instance through Deployment Manager.