The move to Google® Cloud Platform (GCP™) public cloud services is underway, and requirements for cloud security are real. Palo Alto Networks® offers innovative and comprehensive protection as you adopt public cloud services. The Palo Alto Networks solutions complement the native GCP security toolset, including network, host and cloud-native security delivered through APIs for comprehensive protection. In this Quest, you will get hands-on practice with the Palo Alto Networks virtual next-generation firewall running in GCP. You will gain practical experience that you can apply to improve visibility and security for your applications and workloads.
Security is an uncompromising feature of Google Cloud Platform services, and GCP has developed specific tools for ensuring safety and identity across your projects. In this fundamental-level quest, you will get hands-on practice with GCP’s Identity and Access Management (IAM) service, which is the go-to for managing user and virtual machine accounts. You will get experience with network security by provisioning VPCs and VPNs, and learn what tools are available for security threat and data loss protections.
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.
In this Quest, the experienced user of Google Cloud will learn how to describe and launch cloud resources with Terraform, an open source tool that codifies APIs into declarative configuration files that can be shared amongst team members, treated as code, edited, reviewed, and versioned. In these nine hands-on labs, you will work with example templates and understand how to launch a range of configurations, from simple servers, through full load-balanced applications.
In this advanced-level quest, you will learn how you to harness serious GCP power and infrastructure. The hands-on labs will give you use cases, and you will be tasked with implementing scaling practices utilized by Google’s very own Solutions Architecture team. From developing enterprise grade load balancing and autoscaling, to building continuous delivery pipelines, Google Cloud Solutions I: Scaling your Infrastructure will teach you best practices for taking your GCP projects to the next level.
In this advanced-level quest, you will learn how to harness serious GCP computing power to run big data and machine learning jobs. The hands-on labs will give you use cases, and you will be tasked with implementing big data and machine learning practices utilized by Google’s very own Solutions Architecture team. From running Big Query analytics on tens of thousands of basketball games, to training TensorFlow image classifiers, you will quickly see why GCP is the go-to platform for running big data and machine learning jobs.
In this fundamental-level quest, you will learn the ins and outs of Stackdriver: an important GCP service for generating insights into applications’ health. Stackdriver provides a wealth of information in application monitoring, report logging, and diagnoses. The labs in this quest will give you hands-on practice with Stackdriver, and will teach you how to monitor virtual machines, generate logs and alerts, and create custom metrics for application data.
It’s no secret that machine learning is one of the fastest growing fields in tech, and the Google Cloud Platform has been instrumental in furthering it’s development. With a host of APIs, GCP has a tool for just about any machine learning job. In this advanced-level quest, you will get hands-on practice with machine learning APIs by taking labs like Implementing an AI Chatbot with Dialogflow and Detect Labels, Faces, and Landmarks in Images with the Cloud Vision API.
Cloud SQL is a fully managed database service that stands out from its peers due to high performance, seamless integration, and impressive scalability. In this fundamental-level quest, you will receive hands-on practice with the basics of Cloud SQL and quickly progress to advanced features, which you will apply to production frameworks and application environments. From creating instances and querying data with SQL, to building Deployment Manager scripts and highly available databases that run on GKE containers, Cloud SQL will give you the knowledge and experience needed so you can start integrating this service right away.
In this advanced-level quest, you will learn the ins and outs of developing GCP applications in Python. The first labs will walk you through the basics of environment setup and application data storage with Cloud Datastore. Once you have a handle on the fundamentals, you will get hands-on practice deploying Python applications on Kubernetes and App Engine (the latter is the same framework that powers Snapchat!) With specialized bonus labs that teach user authentication and backend service development, this quest will give you practical experience so you can start developing robust Python applications straight away.