De-mystifying the cloud: Free cloud infrastructure training

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Want to make your life easier by moving from on-prem to the cloud, but don’t know where to start? There’s a Quest for that. The Baseline: Infrastructure Quest gives you hands-on practice with GCP’s core infrastructure services like Cloud IAM, Kubernetes, and Stackdriver. Enroll in the Quest by Monday, September 24th you’ll get a 1-month pass (free of charge, no CC required) to earn the badge and show your “flight time” with Google Cloud.

Even better, each lab in the Quest has 1-minute videos to walk you through key concepts for each lab. Here are some of the labs in the Quest:

  • Cloud Storage: Qwik Start – Console: Use the Google Cloud Platform Console to create a storage bucket, upload objects, create folders & subfolders, and then make those objects publicly accessible.

When you’ve created a bucket & uploaded an object into the bucket, you can check your progress: 

Ensure that you’ve understood each concept by answering multiple choice questions: 

How did you do? Share your results @Qwiklabs. Need extra help? Watch Jenny as she walks you through this lab.

  • Cloud IAM: Qwik Start: Cloud IAM unifies access control for GCP services into a single system and presents a consistent set of operations. Learn to create and manage permissions with this lab. You’ll assign and remove roles associated with Identity and Access Management (IAM).

When you’ve removed project viewer access for a user with IAM, you should see a similar permission error:

If not, let Jenny come to your rescue in this video!

  • Kubernetes Engine: Qwik Start: After you’ve created a cluster, you’ll execute kubectl run command to create a new Deployment, hello-server, using the hello-app container image. Before you can inspect the hello-server service, you’ll need to expose your application to external traffic:

If you’re unable to view the application from your web browser using the external IP address with the exposed port, let Jenny help you!

  • Deployment Manager: Qwik Start: Since Deployment Manager is an infrastructure deployment service that automates the creation and management of GCP resources, you can write configuration files for Cloud Storage, Compute Engine, Cloud SQL, etc.

In this lab, you’ll write a file to create & deploy configuration, inspect the running environment and view the deployment manifest. While waiting to deploy your configuration, you’ll see a status message:

Don’t see it? Jenny can help you with this lab too!

Why wait? Enroll now before 2020 hits, and your server closet in the back room is still humming (:

Your challenge, should you choose to accept it….

There are 8000+ Cloud Architect jobs on LinkedIn and they can make up to $170k+ per year. High salary means high expectations. When you earn your Cloud Architect certification, you are tested on your ability to solve real-world problems. Prepare for the Cloud Architect certification exam and set yourself apart.

Need help practicing for the exam and testing your skills in a simulated crisis? Qwiklabs can help! Tackle the Challenge: GCP Architecture Quest to put your skills to the test. Instead of following “cookbook” steps, you’ll practice with common business/technology solutions using GCP.

Enroll in the Challenge: GCP Architecture Quest by Friday, September 21st and you’ll get a 1-month pass (free of charge, no CC required) to help you complete the Quest and practice for the Cloud Architect certification exam.

Here are a couple of scenarios from the Quest:

  • Google Cloud Essential Skills: Challenge Lab: Your company is ready to launch a brand new website, but the person who built the new site left the company before they could deploy it. Your challenge is to deploy the site in the public cloud.

Tip: Need help with VM? Check out the Creating a Virtual Machine lab before tackling this scenario.

If you need additional help with gcloud, read this documentation.

  • Deploy a Compute Instance with a Remote Startup Script: Since you need to manage the deployment and configuration of Google Cloud virtual machines, you’ve decided to make some changes to the framework. For example, storing startup scripts in a Cloud Storage bucket to make them easily modifiable.

Since these scripts automate initialization of compute instances, this will help you with overcoming a challenge. You will use a remote startup script to configure a Linux Google Compute Engine instance that installs the Apache web server. Have you ensured Apache installation by accessing the Compute Engine instance via HTTP?

Tip: Need help with Cloud Storage? Check out the Cloud Storage: Qwik Start – Console lab first.

  • Build and Deploy a Docker Image to a Kubernetes Cluster: Your development team wants to adopt containerized microservices approach to application architecture. Your task? Ensure you can deploy a sample application to a GCP Kubernetes container. To test deployment of echo-web with a Dockerfile, you must use a tag to build the Docker container image and store it on the Google Container Registry.

Tip: Having trouble with tagging? Take the Container Registry: Qwik Start lab first.

  • Update and Scale Out a Containerized Application on a Kubernetes Cluster: Your system architecture team has adopted a containerized micro-service architecture. You need to take ownership of a test environment to manage containerized web applications. Your challenge is to update the running echo-app application in the echo-web deployment from the v1 to the v2 code. And (because there’s always an “and”) then scale out the application to 2 instances and confirm that they are all running.

Tip: Need help with scaling your containerized applications? Take the Kubernetes Engine: Qwik Start lab first.

Fun fact: The Quest consists of seven scenarios and all of them have activity tracking so, you must score 100% in each scenario to earn the badge. Here’s a qwik preview of activity tracking you’ll see on the right hand side of each scenario:

Think you’ve got what it takes to earn the badge that very few people have added on their resumes? Tackle the Quest now to get the practice for the exam you won’t get anywhere else in the world and increase your career opportunities!

Machine Learning for .NET developers

Democratizing machine learning continues, this time for .NET. Google Cloud is committed to supporting developers getting their .NET workloads up and running on the GCP. Learn how with the newest Qwiklabs Quest, Developing Data and Machine Learning Apps with C#. Use this link to enroll this weekend (before Sept. 25), and get 25 Qwiklabs credits free of charge, good towards labs in the new Quest.

Each lab demonstrates how to hook up your data to Google’s ML tools with just a few simple commands. You even get app templates you can re-use when you work on your own projects.

  • Using BigQuery with C# (60 mins): To  or not to , that is the question. Use BigQuery to analyze Shakespeare, a GitHub dataset and data you upload yourself (could be anything).
  • Using the Natural Language API with C# (45 mins): Analyze how awesome Yukihiro Matsumoto is, with documentSentiment. What did you get? The overall sentiment analysis consists of two fields: sentiment and magnitude. Sentiment ranges between -1.0 (negative) and 1.0 (positive). Magnitude indicates the overall strength of emotion (both positive and negative) within the given text, between 0.0 and +inf. Pop quiz: who remembers how to diagram a sentence? Now you can #makegoogledoit, one more talent of the Natural Language API.
  • Using the Speech-to-Text API with C# (45 mins): How many languages do you speak? The Google Cloud Speech-to-Text API has 120 different languages and variants. Even French or a Brooklyn accent. For extra credit, see if the API can transcribe a clip of your speech when you take the lab. Check it out on TechCrunch (:
  • Using the Video Intelligence API with C# (45 mins): You’ll work with a shot-change detection example in this lab. What other types of changes would you want to identify? Maybe a model that detects activity in wildlife monitoring cameras or security footage…
  • Using the Vision API with C# (45 mins): What do otter crossing signs have in common with the Eiffel Tower? The Google Cloud Vision API can recognize them both. Learn how to protect wildlife and organize your vacation photos with a lab. Then apply the skills you learned next time you build a license plate recognition app, or rank the most popular landmarks #teampixel is sharing.

  • Using the Translation API with C# (45 mins): How do you say “hello world” in Turkish? I don’t know – but we can use the Translation API to do it for us. Text is translated using the Neural Machine Translation (NMT) model. If the NMT model is not supported for the requested language translation pair, then the Phrase-Based Machine Translation (PBMT) model is used. And “hello world” in Turkish? Selam Dünya!
  • Cloud Spanner: Create a Gaming Leaderboard with C# (60 mins): Ready player one – wait, who won the last round? Learn to create a leaderboard with C# – this one is the most advanced lab in the Quest so prepare to be challenged!

Hurry, click here to enroll by the weekend and get 25 credits free of charge to help you get started. Good luck!

Terraform training on GCP

Did you know that there are over 3000 jobs on LinkedIn that require Terraform expertise? Terraform is the first multi-cloud immutable infrastructure tool for developing, changing and versioning infrastructure safely and efficiently. Terraform can also manage existing service providers and custom in-house solutions.

Qwiklabs can help you learn how to take advantage of what Terraform has to offer. Enroll in the Managing Cloud Infrastructure with Terraform Quest by Thursday, August 30th and you’ll get 40 credits. Use these credits to launch a range of configurations, from simple servers to full load-balanced applications.

If you’re new to GCP, consider tackling the Baseline: Deploy & Develop Quest first. Are you an experienced Google Cloud user? Here’s how the Managing Cloud Infrastructure with Terraform Quest can help you get more comfortable with Terraform:

     After creating a Kubernetes engine cluster, you’ll extract the Kubernetes        engine master IP and network tag name using the gcloud command-line        tool:

And then deploy the NAT gateway instance using Terraform commands.

  • Modular Load Balancing with Terraform – Regional Load Balancer: GCP uses forwarding rules to construct a load balancer across multiple regions and instance groups. Since these forwarding rules are combined with backend services, target pools, URL maps and target proxies, Terraform uses modules to simplify the provisioning of load balancers.

In this lab, you’ll work with different modules to create various load balancers. For example, in the terraform-google-lb-http (global HTTP(S) forwarding rule) module, you’ll provide a reference to the managed instance group and certificates for SSL termination. Then the module creates a global HTTP load balancer for multi-regional content-based load balancer

Do you know what happens behind the scenes? The module creates the http backend service, URL map, HTTP(S) target proxy, and the global http forwarding rule to route traffic based on HTTP paths to healthy instances:

You’ll then unseal the Vault after getting the decrypted keys from Cloud Storage:

Are your results similar to the example output? Share your results @Qwiklabs.

    • Cloud SQL with Terraform: In this lab you’ll create Cloud SQL instances with Terraform, set up the Cloud SQL Proxy and test the database connection with both MySQL and PostgreSQL clients.

Enroll now to either build career opportunities or to boost your team’s efficiency.

Dig deep into BigQuery Machine Learning with Google Cloud

You don’t need a B.S. in Computer Science to take advantage of powerful GCP data analysis tools. Google announced fully managed service at Next’18, BigQuery Machine Learning (BQML). BQML allows you to:

  • Create, train, evaluate, predict and deploy machine learning models with minimal coding
  • Use SQL directly in the database

Get started with BQML by taking the Predict Visitor Purchases with a Classification Model in BQML lab today and get a 30 day pass (free of charge, no CC required) to help you take advantage of this shiny new toy — I mean, seriously, an impactful data analysis tool!

Here’s some of what you’ll do in the lab:

  • Explore Ecommerce data & run the Query to find out what percentage made a purchase from website visitors:
  • Run the Query to find out your top 5 selling products: 
  • Preview the demo dataset to find useful features a machine learning model uses to understand if a first time visitor will return to make a purchase & dig deeper to know the risks of only using these fields for your classification model:
  • Evaluate classification model to maximize the True Positive Rate (predict that returning users will make a purchase) & visualize a ROC (Receiver Operating Characteristic) curve to maximize the area under the curve:Take the lab  and get your 30 day pass to be one step closer to earning the Data Engineering Quest badge.

The independence of upskilling

The U.S. will be celebrating its 242nd year of independence on July 4th. Set your own “independence” day – learn new skills and take your career where *you* want to go. Enroll in any of these Quests by Monday, July 8th and get a 30 day pass to earn these badges (free of charge, no credit card required). What skills can you add to your resume? 

  1. Baseline: Infrastructure Quest: Learn to use Cloud Storage, deploy a containerized application with Google Kubernetes Engine, build a Docker image, create and deploy a Cloud Function, publish and consume messages, create a Cloud IoT Core device registry and use Cloud Spanner. Here’s the badge you’ll earn:

  1. GCP Essential Quest: This Quest has the best of both worlds! While it helps you get more comfortable with the Google Cloud, like spinning up a virtual machine, it also challenges you to configure key infrastructure tools through working with more advanced Stackdriver and Kubernetes concepts. Tackle the Quest to earn this badge:

  1. Application Development Quest: Think you’re a Java Jedi or a Python powerhouse? Well we’ve got challenging Quests for you! In these two Quests, you’ll either put your Java or Python skills to test by developing cloud-based applications using GCP services such as App Engine, Cloud Datastore and Cloud Spanner. Then integrate these services and deploy to an App Engine and a Kubernetes Engine. Are you excited to earn these badges?

 

                                                           

 

 

4. Scaling Your Infrastructure Quest: Not for beginners! If you’re ready for an expert level Quest, this one’s for you. Learn how to: set up multiple NAT gateways, deploy an autoscaling Compute Engine, customize Stackdriver logging, set up Jenkins on Google Kubernetes Engine to help orchestrate your software delivery pipeline and use Spinnaker to continuously deploy the application when changes are made. You’ll earn this badge:

Celebrate your own independence day with us. Enroll by Monday, July 8th, get a 30 day pass (free of charge, no credit card required), and take charge of your career!

Dig deep into Machine Learning with Google Cloud: Part 2

If you haven’t enrolled in the machine learning Quests mentioned in this blog, you’re missing out! One last chance for free labs, follow any of the Quest links in this post and get a 30 day pass to finish these Quests. Hurry, offer expires Thursday, June 28 (free of charge, no CC required).

Tackle any of the Quests from the roadmap below to become a ML master. If you’re a beginner… begin at the beginning 🙂

Earn a machine learning Quest badge or two, get practice with real-world scenarios, and make the most out of your time at Next ‘18 with some ML rockstars. Who might you meet at Next ’18?

Fei Fei Li is a Chief Scientist of Cloud AI and ML at Google Cloud. She works in the areas of computer vision and cognitive neuroscience. Her publications include Scaling Human-Object Interaction Recognition through Zero-Shot Learning  and Social GAN: Socially Acceptable Trajectories with Generative Adversarial Networks. Get hands-on practice with Cloud AI at scale with the Machine Learning APIs Quest.

Or you might run into Valliappa Lakshmanan. Lak is on a mission to democratize machine learning so anyone can do it using Google’s infrastructure. Check out his latest book, Data Science on the Google Cloud Platform, explaining how to apply statistical and machine learning methods to real-world problems. And try it for yourself with a lab from the Scientific Data Processing Quest!

Take some labs ahead of time, gain a little experience, and ask better questions at the ML sessions offered at the Next ’18! Check out these sessions:

Can’t get enough of machine learning? When you register for Next ‘18, you will have the option to add some of these ML boot camps:

    • End-to-End Machine Learning with TensorFlow on GCP: You’ll go through the process of building a complete machine learning pipeline, covering ingest, exploration, training, evaluation, deployment and prediction.
    • Building and updating a Machine Learning Model on Edge Network using Cloud ML: You’ll learn how to process and store IoT or other data using Cloud Pub/Sub, Cloud Dataflow, Cloud Storage, and Google BigQuery.
    • Building Chatbots with Machine Learning: You’ll use Dialogflow and Cloud Natural Language API to rapidly convert an HR manual document into a fully functional and conversational chatbot. You’ll also add text and voice interactions to the chatbot and secure and scale it for production.

If you can’t make it to Next in San Francisco, take classes worldwide. Find one here.

To make the most of your time at Next ’18, enroll in these ML Quests by Thursday, June 28 (free of charge, no CC required).

Dig deep into Machine Learning with Google Cloud

Fun fact: there are 1,829 open positions for machine learning engineers on LinkedIn. Do you want to become a machine learning engineer? It’s easier than you might think, and we can help with a Quest or two.

Tackle any of the Quests from the roadmap below and become a ML expert:

1. Enroll in Baseline: Data, ML & AI Quest – If you’re new to ML, it’s a perfect Quest! You’ll work with big data, machine learning and artificial intelligence services in Google Cloud, like Dataproc and Bigtable.  Enroll now and get a free 30 day pass to earn this badge, plus as many others as you can (free of charge, no CC required). Hurry, link expires Thursday, June 21. 

 

2. The Machine Learning APIs Quest: This is the next step in your ML journey. You’ll capture text strings from images, recognize characters translate text into other languages using Cloud Vision API, Natural Language API and Translation API. You’ll even build a responsive chat bot using Google Cloud Dialogflow and train & deploy a TensorFlow model to Cloud ML Engine for serving (prediction).

 3. Enroll in Scientific Data Processing: Ready for a challenge? Tackle this Quest next. You’ll explore public domain scientific data sets, and learn to manipulate and transform data using the power of Google’s cloud infrastructure.

Can’t get enough of machine learning? Want to know what’s Next?  Stay tuned for Part 2!

This is the Quest you have been looking for…

You have been waiting patiently for a security training Quest…. today’s your lucky day! A new Quest from Qwiklabs, just released: Security & Identity Fundamentals. Dig deep into the building blocks of Google Cloud Platform Security by working with: Cloud Identity and Access Management (IAM), Network Security, setting up VPCs, VPNs and a private Kubernetes Cluster.

Are you ready to earn your Google Cloud Security and Identity badge? Click here to accept the challenge! (And use this link for 10 credits free of charge to help you along… click now, offer expires Friday.)

Here’s some of what you’ll do in this Quest:

Cloud IAM Custom Roles: Work with the right tools to manage resource permissions. Instead of directly granting users permissions, you grant them roles, which bundles permissions to map job functions within your company to groups and roles. Permissions management at scale? Yup.

Cloud Key Management Storage (KMS): Practice with advanced features of Google Cloud Security and Privacy APIs, set up a secure Cloud Storage bucket and manage keys and encrypted data using KMS. You’ll even use the Enron Corpus!

Virtual Private Cloud (VPC) Network Peering: Work with private connectivity across two VPC networks even if they don’t belong to same project or same organization. Plus, learn to save money with lower GCP egress bandwidth costs.

Cloud Security Scanner: Learn how to identify security vulnerabilities in your Google App Engine web applications. You will scan a sample app – can you find the vulnerabilities?

Data Loss Prevention: Practice with an intelligent data service, Google Cloud Dataprep, to visually explore, clean and prepare data for analysis. This one’s in beta so you’ll be one of the first to use it!

Private Kubernetes Cluster: Learn how to create a private cluster in the cloud environment. Since nodes in the private cluster do not have public IP addresses, your workload runs in an isolated environment from the Internet. This one’s a two-fer, which means if you complete this one lab, you’re making progress on both your Security & Identity Quest, and your Kubernetes in the Google Cloud Quest.

Ready to tackle this challenge? Enroll by Friday, June 22 and get 10 Qwiklabs credits free of charge (no credit card required).

 

 

Next ’18: Got your ticket?

Are you ready for the Next ‘18 conference? You’ll get access to Google keynotes, working sessions, exclusive certification opportunities, expert Q&A, opportunities to participate in bootcamps, and more. And if you can’t make it to San Francisco, check out these Next Extended events around the world. 

Next ’18 is the perfect opportunity to take a certification exam. Not sure where to begin, or how to prepare? Start your certification journey with hands-on labs. You can even take labs before the event so you get the most out of your experience at the conference.

Enroll in any of the following Quests, and get 30 credits free of charge (no credit card required). 

 1. The GCP Essential Quest is the most popular Quest of all time. Practice with GCP basics like starting a Virtual Machine and working with key infrastructure tools like Stackdriver and Kubernetes. Complete the Quest and you’ll earn this badge:

2. Need more specialized practice with the Google Cloud? Tackle the Baseline: Infrastructure Quest and you will learn to use Cloud Storage, deploy a containerized application with Google Kubernetes Engine, build a Docker image, create and deploy a Cloud Function, publish and consume messages, create a Cloud IoT Core device registry and use Cloud Spanner. Here’s the badge you’ll earn:

3. Hoping to become a certified Google Cloud Architect? Next attendees who get certified will have exclusive access to the certification lounge (and snacks!). Complete the Cloud Architecture Quest to help you practice exam topics. Get in-depth experience with Identity and Access Management (IAM), infrastructure scenarios, Cloud Security and Privacy APIs, breaking an application into microservices, debugging, API call tracing and using Deployment Manager to establish alerts to trigger incident response. You’ll earn another badge, too!

4. Google’s Data Engineering certification is unique. Set yourself apart by earning this certification. Practice key exam concepts with the Data Engineering Quest (designed by Google’s training team). You’ll get experience with TensorFlow, an IoT pipeline, BigQuery and Datalab, and even learn how to correspond to your sales data with the weather! Here’s the badge you’ll earn:

See you at Next ’18!