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.
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.
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.
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).
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!
Qwiklabs has big news – Google labs are available now! Just in time for Next ’17. Even better news: all Google Cloud labs are available free of charge (for a limited time).
Click here to see all Google Cloud labs.
If you are already a Qwiklabs user, you can use your Qwiklabs credentials to log in (even though the URL is slightly different than what you’re used to seeing). You will find Google Cloud labs for all experience levels. Want to learn the basics? Try one of these introductory labs:
Or, expand your skillset with a more advanced lab:
Questers, we’ve got something for you too! Be one of the first to add a Google Cloud badge to your resume. Enroll now, and complete your quest while all the labs are available free!
Got questions I didn’t answer? I’m here to help. Just post a comment here and we’ll get back to you right away.