A Cloud Guru | Go Serverless with a Graph Database [FCO]

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By : Steve Roberts
Publisher : ACloud.Guru
Released : 2020
Course Source : https://acloud.guru/learn/aws-go-serverless-graph-database

Leverage the power of graph databases for your next serverless project

Description

Hello Cloud Gurus,

Graph Databases like Amazon Neptune are incredibly powerful but relatively underappreciated. In this course, we will dive in to Neptune to see how and why it might be right for your Serverless applications. At the end of this course you will be able to spin up a Graph Database stack and a simple web application to leverage your graph data. We’ll achieve this with serverless framework and cloudformation, meaning you learn a lot more than just one AWS service in this course!

The app we build is also great fun and very practical. It’s a face categorisation app using family photographs (you can use your own if you like, or use the supplied images), leveraging data that we will generate from the Amazon Rekognition service. With this tool we might just be able to finally sort out those hundreds of thousands of family photos that we all have lying around. Now you can easily find all those photos of your Grand Aunt quickly and accurately!

This is a beginner to intermediate-level course. We will be writing a bit of code and setting up (and removing) quite a lot of infrastructure in AWS. Prior coding experience is nice to have. The course will definitely be easier to follow if you have a bit of an understanding of JavaScript (Node) and CloudFormation. For those who don’t have this experience, don’t worry – at key points in the course when we write code or modify CloudFormation templates, we will point out relevant chapters in other A Cloud Guru courses that will help you learn these areas in more detail.

In this course, you’ll learn:

• What graph databases are, and how they differ from other data storage and why/when to use them.
• How to set up and run an AWS Neptune instance.
• How to use the Gremlin and SPARQL query languages.
• How to bulk upload data into AWS Neptune.
• How to use Amazon Rekognition to analyze photos for faces.
• How to create a simple Node.js API and UI endpoint for interacting with your graph data in a web interface.

So what are you waiting for, Cloud Gurus! If you work in a software development team, you are a tech manager or a business person who is technically minded, join me in this course to discover what graph databases are and what they can do for you and your serverless project.

EXPECTED OUTCOMES

• You will be able to identify use cases where graph data is an appropriate data storage solution
• You will be able to demonstrate and understanding of how to work with graph data using popular query languages
• You will be able to demonstrate a familiarity with why complex AWS infrastructure is often needed, particularly with secure managed services like Neptune.
• You will be able to create an API and user interface to make graph data analysis accessible to you and your stakeholders.

INTENDED AUDIENCE

• Developers wanting to orient themselves around the cloud application development landscape.
• Technical managers whose teams are moving to cloud technology.
• Those involved with technical teams, including quality assurance, operations, production management and project management.

PREREQUISITES

• An AWS account
• Around 100 to 200 family photos, where similar people appear in many photos (Optional, a sample set with be provided)

About Author

Steve Roberts

Hi I'm Steve. I've had pretty much any job possible to do with creating software products, but have finally settled down as a manager so I can sneakily continue to get involved in everything and anything. More recently I have taken to exploring in AWS in my spare time (primarily through my open source photo archive project - fotopia: https://github.com/mbudm/fotopia-serverless). I find projects are the best way to really deep dive into all the new cloud toys that I then apply to client projects in my day job. Having lived through the dark days of software development where we FTP'd things to servers in the broom closet and version control was optional I'm amazed and excited at how powerful and relatively idiot proof the technologies of today have become.



Files:

[FreeCoursesOnline.Me] A Cloud Guru - Go Serverless with a Graph Database 0. Websites you may like
  • 0. (1Hack.Us) Premium Tutorials-Guides-Articles & Community based Forum.url (0.4 KB)
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  • 3. (FTUApps.com) Download Cracked Developers Applications For Free.url (0.2 KB)
  • How you can help our Group!.txt (0.2 KB)
01 Introduction and Overview of Graph Data Theory
  • 001 Welcome.mp4 (24.3 MB)
  • 002 AWS Cost Control (A Cloud Guru course).txt (0.0 KB)
  • 002 Advanced AWS CloudFormation (A Cloud Guru course).txt (0.1 KB)
  • 002 Course Overview.mp4 (46.5 MB)
  • 002 Course Repo.txt (0.1 KB)
  • 002 Introduction to AWS CloudFormation (A Cloud Guru course).txt (0.0 KB)
  • 002 Introduction to Amazon RDS (A Cloud Guru Course).txt (0.0 KB)
  • 002 S3 Masterclass (A Cloud Guru course).txt (0.0 KB)
  • 002 The Serverless Framework with GraphQL (A Cloud Guru course).txt (0.0 KB)
  • 003 Graph Databases and the Face Categorising Project.mp4 (17.6 MB)
  • 003 Supplied Photos (for Project).txt (0.1 KB)
  • 004 AWS Neptune FAQs (AWS site).txt (0.0 KB)
  • 004 Amazon Neptune 10000 Feet View.mp4 (10.4 MB)
  • 005 Amazon Neptune Graph Models.mp4 (14.3 MB)
  • 006 Property Graph Model.mp4 (8.4 MB)
  • 007 Resource Description Framework (RDF) Graph Model.mp4 (22.6 MB)
  • 008 Chapter 1 Resources.md (0.1 KB)
  • 008 Course GitHub Repo.txt (0.1 KB)
  • 008 Lab Getting Set Up for this Course.mp4 (35.5 MB)
02 Playing with Amazon Neptune Query Languages
  • 001 Chapter Introduction.mp4 (13.3 MB)
  • 002 Apache Tinkerpop and the Console.mp4 (43.4 MB)
  • 003 Introducing the Gremlin Query Language.mp4 (18.2 MB)
  • 004 Chapter 2 Resources.txt (0.1 KB)
  • 004 LAB Using the Apache Tinkerpop Console.mp4 (45.1 MB)
  • 005 An Alternate Query Language - SPARQL.mp4 (23.3 MB)
03 Setting Up an App that will Interact with Neptune
  • 001 Chapter 3 Resources.txt (0.1 KB)
  • 001 Chapter Introduction.mp4 (12.9 MB)
  • 002 Understanding the Neptune and API Stacks.mp4 (15.8 MB)
  • 003 Understanding the Neptune CloudFormation.mp4 (31.3 MB)
  • 004 Understanding the API CloudFormation.mp4 (34.8 MB)
  • 005 LAB Spin Up the Neptune Stack.mp4 (10.5 MB)
  • 006 LAB Spin Up the API Stack.mp4 (7.9 MB)
  • 007 Cleaning Up to Save.mp4 (2.2 MB)
  • 008 LAB Removing the Stacks.mp4 (7.6 MB)
04 Creating a Useful Dataset
  • 001 Chapter 4 Resources.txt (0.1 KB)
  • 001 Chapter Introduction.mp4 (4.6 MB)
  • 002 Creating Graph Data with Rekognition.mp4 (16.8 MB)
  • 003 Understanding the Rekognition Stack.mp4 (28.2 MB)
  • 004 LAB Creating Graph Data from Rekognition.mp4 (15.3 MB)
  • 005 Updates to the Neptune and API Stacks for Loading Data.mp4 (16.7 MB)
  • 006 LAB Loading Data into Neptune.mp4 (26.3 MB)
  • 007 Rekognition Data that Suits RDF.mp4 (12.3 MB)
05 Working with our Data via the App
  • 001 Chapter 5 Resources.txt (0.1 KB)
  • 001 Neptune Web UI Overview.mp4 (12.1 MB)
  • 002 LAB Modifying the Query Lambda.mp4 (27.6 MB)
  • 003 LAB Running the Neptune Web UI.mp4 (59.4 MB)
06 Conclusion
  • 001 Building on our Serverless Graph Database Solution.mp4 (97.0 MB)
  • 001 Chapter 6 Resources.txt (0.1 KB)
  • 002 Thank You and Goodbye.mp4 (16.5 MB)

Code:

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