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 (:
Interested in self-driving cars? Learn the technology behind the magic – then sit back, relax, and let the car do it for you.
- How do autonomous cars recognize speed limit signs? “See” for yourself with the Detect Labels, Faces, and Landmarks in Images with the Cloud Vision API lab (bonus, follow that link and get the lab free of charge). You’ll build a model that recognizes landmarks and items in photos with a simple REST API.
- Then, how do cars know the speed limit? The Extract, Analyze, and Translate Text from Images with the Cloud ML APIs lab shows you how to translate signs – not just read them – which means machine learning can improve your commute no matter what side of the road you drive on.
- Some cars know what’s around you – trucks, cars, motorcycles, even reindeer. Learn how to use Google’s Machine Learning tools to Classify Images of Clouds in the Cloud with AutoML Vision.
- Even when conditions aren’t perfect, cars can predict what’s next. Start making predictions with the Cloud ML Engine: Qwik Start lab.
With these labs, you’re well on your way to your next badge, Machine Learning APIs. Enroll here, and you’ll get 55 Qwiklabs credits to start your next Quest (limited offer, ends Friday, Sept. 21).
Good luck, buckle up!
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!
Jobs in the tech industry (machine learning, AI, Cloud) will grow between 12%–37% through 2022. Your computer science curriculum can unlock possibilities for students’ career advancement. Take advantage of free Google Cloud Platform training resources to help your students grow computer science skills:
- If you’re associated with a non-profit university, complete this form to request free training on Qwiklabs and Coursera.
Next, use your benefit to have your students enroll in a few machine learning Quests:
- Baseline: Data, ML, AI Quest: Since machine learning is growing rapidly in the tech industry, help your students get started with data tools like Cloud SQL, BigQuery, APIs, Bigtable, Dataproc, Dataprep, and Cloud ML Engine. If your students are interactive learners, they can follow along Mark as he guides their path.
- Machine Learning APIs Quest: Give your students the opportunity to work with a handful of machine learning APIs. For example, they’ll work with Translation API and Natural Language API to translate text into other languages. They’ll also work with Cloud Vision API to capture text from images and Google Cloud Dialogflow to build a responsive chat bot.
- Data Science on GCP Quest. Challenge your students to use Tensorflow, Dataflow and Data Studio to practice all aspects of datasets, such as ingestion, exploration, visualization, etc.
Fun fact: This Quest is derived from the book, Data Science on Google Cloud Platform by Valliappa Lakshmanan. Lak is on a mission to democratize machine learning. If your students were to read the book, they will learn how to apply statistical and machine learning methods to real-world problems.
If your class is interested in learning about the fundamentals of Google Cloud in-person, register for a study jam. Your students will get free access to the GCP Essentials Quest during the session and you’ll get two days of free lesson plans. If they complete the Quest within 1 month of their session, they’ll get a 30-day pass to Qwiklabs (free of charge, no CC required). They can use the pass to tackle any of the machine learning Quests mentioned above.
Why wait? Take advantage of these programs and set your students up for success by helping them add these badges to their resumes:
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!
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.
Infrastructure Architect is the fourth highest-paying job in the tech industry. Add the Cloud Architecture Quest badge to your resume and set your sights on the Cloud ACE certification (and maybe one of the 1,097 open architect jobs). The Quest maps to the topics covered in the new ACE certification exam guide and puts your GCP knowledge to test. Here’s how:
- In the Cloud IAM: Qwik Start lab you’ll assign a role to a second user and remove assigned roles associated with Identity and Access Management (IAM). This maps to section 5 from the exam guide, Configuring Access and Security.
Explore the IAM console in the lab and you’ll see:
- Practice creating Google Compute Engine VM instance in the Stackdriver: Qwik Start lab. It will help you with section 3.1 from the exam guide, deploying and implementing Compute Engine resources.
- Tackle the Orchestrating the Cloud with Kubernetes lab to provision a Kubernetes cluster and deploy and manage Docker containers using kubectl. This helps you practice for section 3.2, Deploying and implementing Kubernetes Engine resources.
Here’s a brain teaser! Nginx container is running, expose it using kubectl expose command in the lab.
What happened? Share your results @Qwiklabs
- Conquer the Deployment Manager – Full Production lab to set up black box monitoring with Stackdriver Dashboard and establish uptime check alerts to trigger incident responses. This maps to section 3.7 from the exam guide, Deploying an Application using Deployment Manager.
Why wait? Enroll in the Cloud Architecture Quest by Friday, August 24th and get a 1-month pass to help you prepare for the Associate Cloud Engineer Certification exam.
What kind of cloud is this?
I don’t know either. Can you think of other types of images that would be useful to classify? For example, if you have an online tire shop, wouldn’t it be cool if your customers could upload a photo of their current tire to find a matching replacement?
AutoML can help your tire shop decrease the number of returns and increase customer delight. And it’s easier than you think – learn how to take advantage of this powerful new tool with a new lab, AutoML Vision API.
Here’s some of what you’ll do:
- You’ll be prompted to log into the AutoML UI. Open the link in a new tab to make it easy to hop between AutoML and your lab manual. Then, you’ll log into AutoML with your Qwiklabs-provided credentials.
- In the AutoML UI, you will see a button for “Billing”. You do not need to worry about billing for this lab, as Qwiklabs covers the cost of this lab for you.
- When you load data into your storage bucket, you’ll set your project name with one of the first commands you run. Find your project name on the left of your lab manual, just below your GCP credentials:
AutoML is currently in beta, so we expect to see constant changes to the user interface. Send any questions to Support@Qwiklabs.com and we’ll be happy to help. Plus you’ll help us keep the lab up to date as the product continues to improve!
Curious about what type of clouds were spotted during our trip to Muir Woods? Here are our model’s predictions:
The model is 99% certain these are cumulus clouds! Prediction certainty and accuracy would be better if we trained our model with more than 20 images per category. When you’re helping customers order tires, you will probably want to use 100+ photos per category.
Big things are happening in Google Cloud. BigQuery ML, for example, just announced at Next ‘18. Even if you weren’t there, you can still take advantage of 33+ new labs released at the conference. And if you haven’t yet seen the new BigQuery interface, you can check it out with a lab.
Here’s what’s new on Qwiklabs:
- Predict Visitor Purchases with a Classification Model in BQML: Use the latest and greatest technology to answer the top question in online retail. Click here to take the lab free of charge, first 25 readers only.
- Classify Images of Clouds in the Cloud with AutoML Vision: AutoML Vision helps developers with limited ML expertise train high quality image recognition models. Take AutoML on a test drive with this lab.
- Managing Cloud Infrastructure with Terraform: #MakeGoogleDoIt – launch your cloud resources, that is. Learn how Terraform can boost your team’s efficiency, by creating configuration files that can be shared, treated as code, edited, reviewed, and versioned.
- Kubernetes Solutions: Work hard, play harder. Use Kubernetes to run dedicated gaming servers, plus 7 more advanced Kubernetes use cases in this Quest.
- Network Performance and Optimization: If you’re the one they call when the network is down, these labs are for you. Learn how GCP can help you sleep at night with better network speed, performance, and reliability.
- Challenge Quest: 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. This and six other scenarios make up the Challenge Quest, to test your skills in a simulated crisis. Good luck!
If you have an Advantage subscription, all of this new content is included in your subscription, no extra charge. Not a subscriber yet? Use promo code NEW33 for 33% off your first month. Promo code is valid through August 1o (Friday).
Good luck on your next Quest!