We deploy the real environment, you take the scenario-based labs on us. Hands-on, from anywhere, at any time.
This course provides a basic introduction to the concept of DevOps. It seeks to give the student a working knowledge of what DevOps is and how it impacts IT in the real world. This course explains the culture of DevOps as well as some of the main practices and tools associated with DevOps. It also introduces the student to the close relationship between DevOps and the cloud.
Serverless Concepts will teach you the basics of this hot new technology. You'll learn about what constitutes a serverless application. You'll watch how-to videos that show off services like AWS Lambda, Google Firebase, and more. You'll be able to review note cards to remember key elements from the sessions. Finally, connect with us in the community and share how you're adopting this technology and your experiences.
YAML Essentials gives even the absolute YAML beginner the skills they need to craft documents using this popular data serialization language. Used across a variety of programs and languages for a vast array of reasons, YAML is a popular choice for data storage, configuration files, configurations management, and more. This course explores how to write a properly structured YAML file in both the human-readable block style and the JSON-compatible flow style.
This course covers the fundamentals of cloud migrations. The student is guided through lessons covering legacy infrastructure and applications architectures, as well as advanced cloud computing architectures. This course provides best-practice for governance and frameworks for accelerating the adoption of public, private and hybrid cloud.
Download Interactive Diagram here: https://interactive.linuxacademy.com/diagrams/CloudMigrationsFundamentals.html
This course is for the absolute beginner to Google Cloud Platform. Have you ever wanted to know, in very simple terms, the answer to the following questions?: What is the cloud? What is Google Cloud? What are Google Cloud's core services? Why do we use Google Cloud? If you answered yes to any of these, then this course is for you. Our goal with this course is to provide a simple, conceptual introduction to the concepts of Cloud Computing, Google Cloud Platform, and it's core services. There are no technical explanations or definitions to memorize — this course is visual, and strictly conceptual. When you are done with this course, you will have the conceptual foundation to move forward onto more advanced GCP courses. By having the frame-of-reference understanding from this course, you will be more prepared to tackle the more complex technical concepts and terminology.
Linux Academy has many innovative tools and services, like your own cloud lab, that cannot be found anywhere else. The robust offering we have developed, which is focused around student success, and how to use that offering can be found here within this course. Anybody looking to maximize their learning and to maximize the value they receive from a Linux Academy membership should go through this course.
Linux Academy provides more content, hands-on labs, your own cloud lab, and more value per dollar than any other training provider.
This course is a replacement for the older "Introduction To Linux Academy" course.
This course will teach the core fundamentals necessary to properly secure your Google Cloud environment, and manage who has access to what resources. The concepts introduced in this course are necessary for any security considerations on Google Cloud.
This course is designed to not only help you pass the Google Cloud Certified - Associate Cloud Engineer exam but also to learn the real-world skills you'll need to be a cloud engineer. This course loosely follows the domain objectives outlined in the certification info. However, instead of just walking you through each bullet point and showing how that particular item works, without any context, we’ve chosen to use a scenario.
In this scenario, you’ve been hired by a startup called Find Seller. They're working on an app that allows users to post a picture of an item and tag it as something they want to buy or sell. They’re having trouble getting funded because currently all of their technology resides on the developers' laptops, and they don’t have any idea how to move to the cloud. That’s where you and I enter the scenario. You’ve been hired as a junior cloud operations engineer, and I’ll be working as a senior cloud engineer. I’ll be mentoring you as we’re assigned tasks from our boss, and we’ll go through the process of deploying and maintaining the application.
Here are some of the areas of focus:
By the end of this course, you should be ready to pass the Google Cloud Certified- Associate Cloud Engineer Exam
In this course, you will develop the skills that you need to write effective and powerful scripts and tools using Python 3. We will go through the necessary features of the Python language to be able to leverage its additional benefits in writing scripts and creating command line tools (data types, loops, conditionals, functions, error handling, and more). Beyond the language itself, you will go through the full development process including project set up, planning, and automated testing to build two different command line tools.
Google Cloud Functions is a serverless, event-driven, managed platform for building and connecting cloud services. It’s a code-centric service where the functions you write can be triggered by an HTTP request or any number of cloud events—both on and off Google Cloud.
At the start of the course, I’ll thoroughly explain what a serverless, event-driven, managed platform for building and connecting cloud services actually means—and what it’s capable of. We’ll cover Cloud Functions’ primary features and benefits - one of the most compelling of which is its flexibility. A fact attested to by the wide spectrum of use cases we’ll discuss. Then, we’ll dig a little deeper to reveal what makes a Cloud Function function, including a full discussion of the different types of Cloud Functions along with their component aspects: events and triggers. I’ll even go over the pricing of Cloud Functions, something everyone involved in related projects should be aware of.
After you’re thoroughly familiar with the overall structure of Cloud Functions, we’ll begin exploring working with them. I’ll show you how to set up a proper development environment – whether you’re on a Mac, Windows, or Linux system – and get your first function deployed right out of the gate. Then, we’ll dive into the particulars of coding functions, specifically in Python: how to code for specific scenarios, like working with JSON variables, or particular situations, such as responding to a trigger from an app in another domain.
I’ll give you all the command line code you’ll need for deploying your Cloud Functions, complete with full coverage of the available parameters. We’ll also discuss deploying Cloud Functions from a variety of sources, including repositories like Github.
Cloud Functions can be triggered through a variety of methods and one of the most common is to use another Google Cloud service. We’ll discuss how to handle those most frequently relied on, among them Cloud Pub/Sub and Cloud Storage – as well as some of the more targeted services like Cloud SQL and Stackdriver.
Testing is also critical in any app development and Cloud Functions is no different. We’ll examine several relevant testing strategies along with a look at implementing a CI/CD workflow with Cloud Functions.
The final section of the course really takes off with an in-depth look at a number of different real-world scenarios. These use cases range from retrieving queried data from Cloud SQL, tying together four different Google Cloud services to extract and translate text from images, and integrating with a third-party service to send a text message anywhere in the world – all triggered by your Cloud Functions.
I’m really excited to show you all of what Cloud Functions can do and exactly how to do it. It’s a really solid solution for an ever-increasing number of use cases and an excellent tool to have in your cloud computing tool chest.
So, come on, let’s get started with our Google Cloud Functions Deep Dive.
Download The Function Flow here: https://interactive.linuxacademy.com/diagrams/TheFunctionFlow.html
Kubernetes, the open-source system for deploying, managing, and scaling containerized apps, is at the heart of Google Kubernetes Engine. This integration is totally natural. Google developed Kubernetes in-house, and uses it to run its own most popular, global apps. Gmail, YouTube, and even Search run in Kubernetes Engine. It is a fully-managed service and, in this course, you’ll learn it from the ground up.
During this course, I’ll explain the concepts behind Kubernetes and explain its architecture in detail. You’ll learn what comprises a cluster, how to spin one up, deploy an application on one, and then scale out as needed. Such power needs to be handled properly. We’ll cover multiple levels of access control, from integration with Cloud IAM to Kubernetes-specific Role-Based Access Control. With any cloud computing system, networking is key. I’ll show you how Kubernetes Engine works with load balancers (both internal and external), as well as how to set up a private cluster, and declare a network policy.
Throughout the course, a fictitious company, LA Containers, is used to provide real-world scenarios in an interactive chart, which can be viewed here: https://interactive.linuxacademy.com/diagrams/LAContainers.html.
Additionally, the course describes how to convert the normally stateless Kubernetes Engine so that it handles stateful applications, with the addition of a persistent disk. We’ll also explore the techniques used for integrating Kubernetes Engine with other services on the Google Cloud platform, such as Cloud Pub/Sub, Cloud Storage, and Cloud SQL.
Kubernetes is the de facto standard for orchestrating containerized apps, and Google Kubernetes Engine is its most fully-realized implementation. Join me in the comprehensive exploration of this much in-demand technology in Google Kubernetes Engine Deep Dive.
In this class, we will look at various issues of migrating databases and virtual machines to the Google Cloud platform. We will address general techniques that are best practices for migrating to the cloud as well as specific features of the Google Cloud platform that will support migrating databases and virtual machines to the cloud.
In the first section of this class, we will discuss general cloud migration techniques. We will begin with the importance of establishing a solid performance baseline before migration as well as the importance of documenting your candidate system. We will also look at planning a good time frame for your migration and some of the factors that you need to consider when scheduling your migration window. In addition, we will look at some post-migration steps that are necessary to ensure that your system is operating correctly after the migration has taken place. These include running necessary smoke test contacting the right personnel and preparing to establish a new baseline once the system has gone into full production.
In the next section of the class, we will look at database migration and some of the issues that are involved when migrating an on-premise database to the cloud. We will also look at the two major types of migrations homogeneous and heterogeneous and some of the issues that are unique to both of these types of migrations. In addition to the mechanics of performing the migration, we will look at some of the performance considerations when migrating an on-premise database system to the cloud.
Following the section on database-migration, we will begin to discuss the mechanics of migrating virtual machines to the Google Cloud platform. We will examine some of the pre-migration issues that you must consider as well as some compatibility issues when migrating an on-premise virtual machine to the cloud. In addition to the general steps of migration, we will look at the features that the Google Cloud platform offers to support virtual machine migration. Following this discussion, we will walk through two different migration examples of on-premise virtual machines to the Google Cloud platform.
In the last section of this class, we will look at some of the services that are offered by cloud service providers that you will be able to take advantage of to extend the functionality of your system after you have migrated to the cloud. Many of these services are easy to configure and will provide your system with many new capabilities
Download the Interactive Guide here: https://interactive.linuxacademy.com/diagrams/CloudMigrationwithGoogleCloud.html
You learn faster and better when you learn by doing. With that in mind, this course has been designed to teach you core Google Cloud services and features through a 100% hands-on experience. To accomplish this, Linux Academy's Training Architects have hand selected a set of the best Google Cloud Hands-on Labs we have to offer.
Everything you do in this course will be inside of a real Google Cloud environment that is provided to you through our Hands-on Lab and Cloud Playground platform.
No reason to wait - Learn by Doing today!!
The Google Cloud Professional Data Engineer is able to harness the power of Google's big data capabilities and make data-driven decisions by collecting, transforming, and visualizing data. Through designing, building, maintaining, and troubleshooting data processing systems with a particular emphasis on the security, reliability, fault-tolerance, scalability, fidelity, and efficiency of such systems, a Google Cloud data engineer is able to put these systems to work.
This course will prepare you for the Google Cloud Professional Data Engineer exam by diving into all of Google Cloud's data services. With interactive demonstrations and an emphasis on hands-on work, you will learn how to master each of Google's big data and machine learning services and become a certified data engineer on Google Cloud.
Download the Data Dossier: https://interactive.linuxacademy.com/diagrams/TheDataDossier.html
The purpose of this course is twofold:
Skills that will be covered include:
These will be a high-level overview of the above concepts, which we will build on in more advanced courses.
The Google Cloud Platform Architect Part 1 course laid down a beginner's level of understanding as a foundation for learning more advanced concepts. In this course, we will take a deeper look at many of GCP's services and start to put many concepts together to mimic most real-life business scenarios. Advanced familiarity with these services will be crucial to prepare for the GCP Architect exam.
It is time to focus on the Cloud Architect exam. In this course, we will be filling in the rest of the gaps over what the exam covers, building directly on what we've already learned in the GCP Architect Parts 1 and 2. We will also re-frame previous skills we've learned in the context of using them to solve complicated business and technical problems.
This course will prepare you for the Google Professional Cloud Developer certification, and all sections are based on the outlined objectives Google published for preparation for the exam. We've also included detailed walkthroughs and hands-on labs to help reinforce the concepts we cover throughout the course.
In Section 1, we discuss best practices for designing highly scalable cloud-ready systems. We will explain best practices for designing performant application interfaces as well as designing secure applications. Following that, we will briefly describe how to best manage application data when migrating to the cloud as well as best practices to follow when re-architecting on-premises applications for migration to the cloud.
Section 2 covers best practices for building and testing applications. The first part of the section covers setting up our development environment for Google Cloud Platform applications. Next, we will look at building a continuous integration pipeline and its benefits. After that, we will get a high-level overview of testing code and major types of testing involved with software development. In the last lesson of the section, we will briefly look at considerations for writing code for cloud-based applications.
Section 3 covers best practices for deploying applications to the Google Cloud Platform. We will first discuss implementing the appropriate deployment model for our particular application. In the next lesson, we will look at considerations for deploying applications to compute engine. Then, we will explain the primary benefits of Google Kubernetes Engine and how to create our first cluster and deploy software to it. In lesson four, we will describe the benefits of using Google App Engine and the basic process for deploying software to App Engine as well as the support for software versions within App Engine. Lesson five provides a high-level overview of cloud functions and how to deploy one. In lesson six, we will look at the wide variety of cloud storage resources supported by the Google Cloud Platform and use cases they support for applications. In the last lessons of this section, we will cover high-level networking issues, automating resource provisioning, and implementing service accounts.
In Section 4, we will discuss products and techniques we can use to integrate an application with Google Cloud Platform services. In the first lesson, we will cover methods to integrate our application with Google Cloud Storage services. Next, we will exlain the options to integrate applications with various Compute Services offered by the Google Cloud Platform. In the last part of this section, we will go over examples of integration with Google Cloud API services.
Finally, we will discuss managing application performance using tools provided by Google Cloud Platform. In the first lesson, we will look at the process to install the logging and monitoring agent for virtual machines. Following that, we will go over troubleshooting techniques we can use to manage virtual machines. Then, we will discuss many of the features of Stackdriver and how we can use them to monitor and manage an application's performance. In the last lesson of this section, we will look at some tips and techniques to diagnose and resolve application performance issues.
Interactive Diagram: https://interactive.linuxacademy.com/diagrams/TheProDevCircuit.html
Google Cloud Platform is one of the fastest growing cloud service platforms offered today that lets you run your applications and data workflows at 'Google-sized' scale.
The Google Cloud Certified Professional Cloud Architect certification is one of the most highly desired IT certifications out today. It is also one of the most challenging exams offered by any cloud vendor today. Passing this exam will take many hours of study, hands on experience, and understanding of a very wide range of GCP topics
Luckily, we're here to help you out! This course is designed to be your best single resource to prepare for and pass the exam to become a certified Googel Cloud Architect.
So let's get started!
Interactive Diagram: https://interactive.linuxacademy.com/diagrams/MasterBuildersGuide.html