English | MP4 | AVC 1920×1080 | AAC 48KHz 2ch | 4h 41m | 906 MB
Implement a reliable application architecture using the patterns and best practices recommended by AWS.
Reliability in AWS includes the ability of a system to recover from infrastructure or service disruptions. It’s essential to acquire computing resources to meet the demand, and mitigate disruptions such as configuration issues or transient network problems.
In this course, you will first explore the key concepts and core services of AWS and Site Reliability Engineering (SRE). We show you step-by-step how to implement a real-world application that is built via the reliability principles defined within the AWS Well-Architected Framework using the SRE approach. So you can increase the reliability of application architectures on AWS by implementing resilience infrastructure and application resilience.
You will be covering some common architectural patterns used every day by real-world AWS solution architects to build reliable systems and implement fault tolerance into an application architecture running on AWS. While learning how to further increase the reliability of application architectures on AWS by implementing multi-region solutions for disaster recovery on a global scale.
By the end of this course, you will have gained a variety of AWS architecture skills that you can then apply to the real world.
Learn
- Understand the core principles of Site Reliability Engineering, and how cloud computing enables this
- Design applications for fault tolerance, auto-healing, resilience, and reliability
- Examine a simple python microservice ecosystem and understand its limitations
- Identify critical stack components, and redesign them so they’re resilient and reliable
- Map design changes to native AWS services with ease
- Deploy redesigned applications in a globally accessible, resilient, and reliable way
Table of Contents
The Basics of Site Reliability Engineering
1 Course Overview
2 Reliability in Modern Applications
3 The Impact of Failure and Determining Your Reliability Objectives
4 Accepting Failure and Making It Part of the Design Process
5 SRE is a Mindset
Gaining Resilience and Reliability On AWS
6 AWS Global, Regional, and Zonal Architecture Design
7 Amazon’s Global Storage Services – S3
8 Running Resilient Databases On AWS – RDS and DynamoDB
9 Fault Tolerant Computation On AWS – Lambda and EC2
10 Core Resilience Principles for AWS – Load Balancing and Auto Scaling
11 Using Kubernetes and ECS On AWS
Accepting Failure In Multi-Tier Applications
12 Typical Three-Tier Application Resilience and Why It Fails in Cloud
13 Designing In Resilience With Microservices
14 Managing State
15 Typical Application Reliability Patterns
16 The Architecture of Our Example Microservices
Deploying Py-Simple On AWS
17 Optimizing and Migrating Our Code
18 Creating Our Container with CodeBuild
19 Deploying ECS and RDS
20 Deploying and Testing Our Py-Simple Application
21 The Problem with What We’ve Just Built
Designing Py-Global
22 The Architecture of Py-Global and Failure Mode Analysis
23 Multi-Regional Support
24 Microservices Design
25 Authentication and Authorization
26 Code Deployment with CodePipeline
27 Application Telemetry and Tracing
28 Application Analytics
29 Aurora and its Advantages Over MySQL
Deploying a Resilient, Fault Tolerant Py-Global Application
30 Running Scaling Our Application On EKS
31 Creating a Resilient and Reliable Data Store for Python with Amazon Aurora
32 Deploying App-Mesh
Surviving Failure of a Global Scale
33 Review – AWS Global Architecture and What We Have Just Built
34 Global Tools – Route 53, CloudFront
35 Going Global – What Does This Mean For Your Users Developers
36 Operational Changes Required For a Global Application
37 Course Summary
Resolve the captcha to access the links!