Amazon Web Services in Action, Third Edition Version 7

✍ Scribed by Andreas Wittig; Michael Wittig

• Publisher: Manning Publications
• Year: 2022
• Tongue: English
• Leaves: 407
• Edition: MEAP Edition
• Category: Library

✦ Table of Contents

Amazon Web Services in Action, Third Edition MEAP V07
Copyright
Welcome
Brief contents
Chapter 1: What is Amazon Web Services?
1.1 What is Amazon Web Services (AWS)?
1.2 What can you do with AWS?
1.2.1 Hosting a web shop
1.2.2 Running a Java EE application in your private network
1.2.3 Implementing a highly available system
1.2.4 Profiting from low costs for batch processing infrastructure
1.3 How you can benefit from using AWS
1.3.1 Innovative and fast-growing platform
1.3.2 Services solve common problems
1.3.3 Enabling automation
1.3.4 Flexible capacity (scalability)
1.3.5 Built for failure (reliability)
1.3.6 Reducing time to market
1.3.7 Benefiting from economies of scale
1.3.8 Global infrastructure
1.3.9 Professional partner
1.4 How much does it cost?
1.4.1 Free Tier
1.4.2 Billing example
1.4.3 Pay-per-use opportunities
1.5 Comparing alternatives
1.6 Exploring AWS services
1.7 Interacting with AWS
1.7.1 Management Console
1.7.2 Command-line interface
1.7.3 SDKs
1.7.4 Blueprints
1.8 Creating an AWS account
1.8.1 Signing up
1.8.2 Signing In
1.9 Create a budget alert to keep track of your AWS bill
1.10 Summary
Chapter 2: A simple example: WordPress in fifteen minutes
2.1 Creating your infrastructure
2.2 Exploring your infrastructure
2.2.1 Virtual machines
2.2.2 Load balancer
2.2.3 MySQL database
2.2.4 Network filesystem
2.3 How much does it cost?
2.4 Deleting your infrastructure
2.5 Summary
Chapter 3: Using virtual machines: EC2
3.1 Exploring a virtual machine
3.1.1 Launching a virtual machine
3.1.2 Connecting to your virtual machine
3.1.3 Installing and running software manually
3.2 Monitoring and debugging a virtual machine
3.2.1 Showing logs from a virtual machine
3.2.2 Monitoring the load of a virtual machine
3.3 Shutting down a virtual machine
3.4 Changing the size of a virtual machine
3.5 1.5 Starting a virtual machine in another data center
3.6 Allocating a public IP address
3.7 Adding an additional network interface to a virtual machine
3.8 Optimizing costs for virtual machines
3.8.1 Commit to usage, get discount
3.8.2 Leveraging spare compute capacity
3.9 Summary
Chapter 4: Programming your infrastructure: The command-line, SDKs, and CloudFormation
4.1 Automation and the DevOps movement
4.2 Why should you automate?
4.3 Using the command-line interface
4.3.1 Installing the CLI
4.3.2 Configuring the CLI
4.3.3 Using the CLI
4.3.4 Automating with the CLI
4.4 Programming with the SDK
4.4.1 Controlling virtual machines with SDK: nodecc
4.4.2 How nodecc creates a virtual machine
4.4.3 How nodecc lists virtual machines and shows virtual machine details
4.4.4 How nodecc terminates a virtual machine
4.5 Infrastructure as Code
4.5.1 Inventing an infrastructure language: JIML
4.6 Using AWS CloudFormation to start a virtual machine
4.6.1 Anatomy of a CloudFormation template
4.6.2 Creating your first template
4.6.3 Updating infrastructure using CloudFormation
4.7 Summary
Chapter 5: Securing your system: IAM, security groups, and VPC
5.1 Who’s responsible for security?
5.2 Keeping the operating system up to date
5.3 Securing your AWS account
5.3.1 Securing your AWS account’s root user
5.3.2 AWS Identity and Access Management (IAM)
5.3.3 Defining permissions with an IAM identity policy
5.3.4 Users for authentication, and groups to organize users
5.3.5 Authenticating AWS resources with roles
5.4 Controlling network traffic to and from your virtual machine
5.4.1 Controlling traffic to virtual machines with security groups
5.4.2 Allowing ICMP traffic
5.4.3 Allowing HTTP traffic
5.4.4 Allowing HTTP traffic from a specific source IP address
5.4.5 Allowing HTTP traffic from a source security group
5.5 Creating a private network in the cloud: Amazon Virtual Private Cloud (VPC)
5.5.1 Creating the VPC and an internet gateway (IGW)
5.5.2 Defining the public proxy subnet
5.5.3 Adding the private backend subnet
5.5.4 Launching virtual machines in the subnets
5.5.5 Accessing the internet from private subnets via a NAT gateway
5.6 Summary
Chapter 6: Automating operational tasks with Lambda
6.1 Executing your code with AWS Lambda
6.1.1 What is serverless?
6.1.2 Running your code on AWS Lambda
6.1.3 Comparing AWS Lambda with virtual machines (Amazon EC2)
6.2 Building a website health check with AWS Lambda
6.2.1 Creating a Lambda function
6.2.2 Use CloudWatch to search through your Lambda function’s logs
6.2.3 Monitoring a Lambda function with CloudWatch metrics and alarms
6.2.4 Accessing endpoints within a VPC
6.3 Adding a tag containing the owner of an EC2 instance automatically
6.3.1 Event-driven: Subscribing to EventBridge events
6.3.2 Implementing the Lambda function in Python
6.3.3 Setting up a Lambda function with the Serverless Application Model (SAM)
6.3.4 Authorizing a Lambda function to use other AWS services with an IAM role
6.3.5 Deploying a Lambda function with SAM
6.4 What else can you do with AWS Lambda?
6.4.1 What are the limitations of AWS Lambda?
6.4.2 Impacts of the serverless pricing model
6.4.3 Use case: Web application
6.4.4 Use case: Data processing
6.4.5 Use case: IoT back end
6.5 Summary
Chapter 7: Storing your objects: S3
7.1 What is an object store?
7.2 Amazon S3
7.3 Backing up your data on S3 with AWS CLI
7.4 Archiving objects to optimize costs
7.5 Storing objects programmatically
7.5.1 Setting up an S3 bucket
7.5.2 Installing a web application that uses S3
7.5.3 Reviewing code access S3 with SDK
7.6 Using S3 for static web hosting
7.6.1 Creating a bucket and uploading a static website
7.6.2 Configuring a bucket for static web hosting
7.6.3 Accessing a website hosted on S3
7.7 Protecting data from unauthorized access
7.8 Optimizing performance
7.9 Summary
Chapter 13: Achieving high availability: Availability zones, auto-scaling, and CloudWatch
13.1 Recovering from EC2 instance failure with CloudWatch
13.1.1 How does a CloudWatch alarm recover an EC2 instance?
13.2 Recovering from a data center outage with Auto Scaling Group
13.2.1 Availability zones: groups of isolated data centers
13.2.2 Recovering a failed virtual machine to another availability zone with the help of auto-scaling
13.2.3 Pitfall: recovering network-attached storage
13.2.4 Pitfall: network interface recovery
13.2.5 Insights into availability zones
13.3 Architecting for high availability
13.3.1 RTO and RPO comparison for a single EC2 instance
13.3.2 AWS services come with different high availability guarantees
13.4 Summary
Chapter 14: Decoupling your infrastructure: Elastic load balancing and simple queue service
15.1 Synchronous decoupling with load balancers
15.1.1 Setting up a load balancer with virtual machines
15.2 Asynchronous decoupling with message queues
15.2.1 Turning a synchronous process into an asynchronous one
15.2.2 Architecture of the URL2PNG application
15.2.3 Setting up a message queue
15.2.4 Producing messages programmatically
15.2.5 Consuming messages programmatically
15.2.6 Limitations of messaging with SQS
15.3 Summary
Chapter 16: Designing for fault tolerance
16.1 Using redundant EC2 instances to increase availability
16.1.1 Redundancy can remove a single point of failure
16.1.2 Redundancy requires decoupling
16.2 Considerations for making your code fault-tolerant
16.2.1 Let it crash, but also retry
16.2.2 Idempotent retry makes fault tolerance possible
16.3 Building a fault-tolerant web application: Imagery
16.3.1 The idempotent state machine
16.3.2 Implementing a fault-tolerant web service
16.3.3 Implementing a fault-tolerant worker to consume SQS messages
16.3.4 Deploying the application
16.4 Summary
Chapter 17: Scaling up and down: auto-scaling and CloudWatch
17.1 Managing a dynamic EC2 instance pool
17.2 Using metrics or schedules to trigger scaling
17.2.1 Scaling based on a schedule
17.2.2 Scaling based on CloudWatch metrics
17.3 Decouple your dynamic EC2 instance pool
17.3.1 Scaling a dynamic EC2 instance pool synchronously decoupled by a load balancer
17.3.2 Scaling a dynamic EC2 instances pool asynchronously decoupled by a queue
17.4 Summary
Chapter 18: Building modern architectures for the cloud: ECS and Fargate
18.1 Why should you consider containers instead of virtual machines?
18.2 Comparing different options to run containers on AWS
18.3 The ECS basics: cluster, service, task, and task definition
18.4 AWS Fargate: running containers without managing a cluster of virtual machines
18.5 Walking through a cloud-native architecture: ECS, Fargate, and S3
18.6 Summary
Notes