book

Amazon Web Services in Action, Third Edition

by Andreas Wittig, Michael Wittig

May 2023

Intermediate to advanced

552 pages

16h 16m

English

Manning Publications

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AWS Services Explained in the Book
prefaceacknowledgmentsabout this bookAbout the third editionWho should read this bookHow this book is organized: A road mapAWS costsAbout the codeliveBook discussion forumabout the authorsabout the cover illustration
1.1 What is Amazon Web Services (AWS)?1.2 What can you do with AWS?1.2.1 Hosting a web shop1.2.2 Running a Java EE application in your private network1.2.3 Implementing a highly available system1.2.4 Profiting from low costs for batch processing infrastructure1.3 How you can benefit from using AWS1.3.1 Innovative and fast-growing platform1.3.2 Services solve common problems1.3.3 Enabling automation1.3.4 Flexible capacity (scalability)1.3.5 Built for failure (reliability)1.3.6 Reducing time to market1.3.7 Benefiting from economies of scale1.3.8 Global infrastructure1.3.9 Professional partner1.4 How much does it cost?1.4.1 Free Tier1.4.2 Billing example1.4.3 Pay-per-use opportunities1.5 Comparing alternatives1.6 Exploring AWS services1.7 Interacting with AWS1.7.1 Management Console1.7.2 Command-line interface1.7.3 SDKs1.7.4 Blueprints1.8 Creating an AWS account1.8.1 Signing up1.8.2 Signing in1.9 Creating a budget alert to keep track of your AWS billSummary
2.1 Creating your infrastructure2.2 Exploring your infrastructure2.2.1 Virtual machines2.2.2 Load balancer2.2.3 MySQL database2.2.4 Network filesystem2.3 How much does it cost?2.4 Deleting your infrastructureSummary

3.1 Exploring a virtual machine3.1.1 Launching a virtual machine3.1.2 Connecting to your virtual machine3.1.3 Installing and running software manually3.2 Monitoring and debugging a virtual machine3.2.1 Showing logs from a virtual machine3.2.2 Monitoring the load of a virtual machine3.3 Shutting down a virtual machine3.4 Changing the size of a virtual machine3.5 Starting a virtual machine in another data center3.6 Allocating a public IP address3.7 Adding an additional network interface to a virtual machine3.8 Optimizing costs for virtual machines3.8.1 Commit to usage, get a discount3.8.2 Taking advantage of spare compute capacitySummary
4.1 Automation and the DevOps movement4.1.1 Why should you automate?4.2 Using the command-line interface4.2.1 Installing the CLI4.2.2 Configuring the CLI4.2.3 Using the CLI4.2.4 Automating with the CLI4.3 Programming with the SDK4.3.1 Controlling virtual machines with SDK: nodecc4.3.2 How nodecc creates a virtual machine4.3.3 How nodecc lists virtual machines and shows virtual machine details4.3.4 How nodecc terminates a virtual machine4.4 Infrastructure as Code4.4.1 Inventing an infrastructure language: JIML4.5 Using AWS CloudFormation to start a virtual machine4.5.1 Anatomy of a CloudFormation template4.5.2 Creating your first template4.5.3 Updating infrastructure using CloudFormationSummary
5.1 Who’s responsible for security?5.2 Keeping the operating system up-to-date5.3 Securing your AWS account5.3.1 Securing your AWS account’s root user5.3.2 AWS Identity and Access Management (IAM)5.3.3 Defining permissions with an IAM identity policy5.3.4 Users for authentication and groups to organize users5.3.5 Authenticating AWS resources with roles5.4 Controlling network traffic to and from your virtual machine5.4.1 Controlling traffic to virtual machines with security groups5.4.2 Allowing ICMP traffic5.4.3 Allowing HTTP traffic5.4.4 Allowing HTTP traffic from a specific source IP address5.4.5 Allowing HTTP traffic from a source security group5.5 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 subnet5.5.3 Adding the private backend subnet5.5.4 Launching virtual machines in the subnets5.5.5 Accessing the internet from private subnets via a NAT gatewaySummary
6.1 Executing your code with AWS Lambda6.1.1 What is serverless?6.1.2 Running your code on AWS Lambda6.1.3 Comparing AWS Lambda with virtual machines (Amazon EC2)6.2 Building a website health check with AWS Lambda6.2.1 Creating a Lambda function6.2.2 Use CloudWatch to search through your Lambda function’s logs6.2.3 Monitoring a Lambda function with CloudWatch metrics and alarms6.2.4 Accessing endpoints within a VPC6.3 Adding a tag containing the owner of an EC2 instance automatically6.3.1 Event-driven: Subscribing to EventBridge events6.3.2 Implementing the Lambda function in Python6.3.3 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 role6.3.5 Deploying a Lambda function with SAM6.4 What else can you do with AWS Lambda?6.4.1 What are the limitations of AWS Lambda?6.4.2 Effects of the serverless pricing model6.4.3 Use case: Web application6.4.4 Use case: Data processing6.4.5 Use case: IoT backendSummary
7.1 What is an object store?7.2 Amazon S37.3 Backing up your data on S3 with AWS CLI7.4 Archiving objects to optimize costs7.5 Storing objects programmatically7.5.1 Setting up an S3 bucket7.5.2 Installing a web application that uses S37.5.3 Reviewing code access S3 with SDK7.6 Using S3 for static web hosting7.6.1 Creating a bucket and uploading a static website7.6.2 Configuring a bucket for static web hosting7.6.3 Accessing a website hosted on S37.7 Protecting data from unauthorized access7.8 Optimizing performanceSummary
8.1 Elastic Block Store (EBS): Persistent block-level storage attached over the network8.1.1 Creating an EBS volume and attaching it to your EC2 instance8.1.2 Using EBS8.1.3 Tweaking performance8.1.4 Backing up your data with EBS snapshots8.2 Instance store: Temporary block-level storage8.2.1 Using an instance store8.2.2 Testing performance8.2.3 Backing up your dataSummary
9.1 Creating a filesystem9.1.1 Using CloudFormation to describe a filesystem9.1.2 Pricing9.2 Creating a mount target9.3 Mounting the EFS filesystem on EC2 instances9.4 Sharing files between EC2 instances9.5 Tweaking performance9.5.1 Performance mode9.5.2 Throughput mode9.5.3 Storage class affects performance9.6 Backing up your dataSummary
10.1 Starting a MySQL database10.1.1 Launching a WordPress platform with an RDS database10.1.2 Exploring an RDS database instance with a MySQL engine10.1.3 Pricing for Amazon RDS10.2 Importing data into a database10.3 Backing up and restoring your database10.3.1 Configuring automated snapshots10.3.2 Creating snapshots manually10.3.3 Restoring a database10.3.4 Copying a database to another region10.3.5 Calculating the cost of snapshots10.4 Controlling access to a database10.4.1 Controlling access to the configuration of an RDS database10.4.2 Controlling network access to an RDS database10.4.3 Controlling data access10.5 Building on a highly available database10.5.1 Enabling high-availability deployment for an RDS database10.6 Tweaking database performance10.6.1 Increasing database resources10.6.2 Using read replication to increase read performance10.7 Monitoring a databaseSummary
11.1 Creating a cache cluster11.1.1 Minimal CloudFormation template11.1.2 Test the Redis cluster11.2 Cache deployment options11.2.1 Memcached: Cluster11.2.2 Redis: Single-node cluster11.2.3 Redis: Cluster with cluster mode disabled11.2.4 Redis: Cluster with cluster mode enabled11.2.5 MemoryDB: Redis with persistence11.3 Controlling cache access11.3.1 Controlling access to the configuration11.3.2 Controlling network access11.3.3 Controlling cluster and data access11.4 Installing the sample application Discourse with CloudFormation11.4.1 VPC: Network configuration11.4.2 Cache: Security group, subnet group, cache cluster11.4.3 Database: Security group, subnet group, database instance11.4.4 Virtual machine: Security group, EC2 instance11.4.5 Testing the CloudFormation template for Discourse11.5 Monitoring a cache11.5.1 Monitoring host-level metrics11.5.2 Is my memory sufficient?11.5.3 Is my Redis replication up-to-date?11.6 Tweaking cache performance11.6.1 Selecting the right cache node type11.6.2 Selecting the right deployment option11.6.3 Compressing your dataSummary
12.1 Programming a to-do application12.2 Creating tables12.2.1 Users are identified by a partition key12.2.2 Tasks are identified by a partition key and sort key12.3 Adding data12.3.1 Adding a user12.3.2 Adding a task12.4 Retrieving data12.4.1 Getting an item by key12.4.2 Querying items by key and filter12.4.3 Using global secondary indexes for more flexible queries12.4.4 Creating and querying a global secondary index12.4.5 Scanning and filtering all of your table’s data12.4.6 Eventually consistent data retrieval12.5 Removing data12.6 Modifying data12.7 Recap primary key12.7.1 Partition key12.7.2 Partition key and sort key12.8 SQL-like queries with PartiQL12.9 DynamoDB Local12.10 Operating DynamoDB12.11 Scaling capacity and pricing12.11.1 Capacity units12.12 Networking12.13 Comparing DynamoDB to RDS12.14 NoSQL alternativesSummary
13.1 Recovering from EC2 instance failure with CloudWatch13.1.1 How does a CloudWatch alarm recover an EC2 instance?13.2 Recovering from a data center outage with an Auto Scaling group13.2.1 Availability zones: Groups of isolated data centers13.2.2 Recovering a failed virtual machine to another availability zone with the help of autoscaling13.2.3 Pitfall: Recovering network-attached storage13.2.4 Pitfall: Network interface recovery13.2.5 Insights into availability zones13.3 Architecting for high availability13.3.1 RTO and RPO comparison for a single EC2 instance13.3.2 AWS services come with different high availability guaranteesSummary
14.1 Synchronous decoupling with load balancers14.1.1 Setting up a load balancer with virtual machines14.2 Asynchronous decoupling with message queues14.2.1 Turning a synchronous process into an asynchronous one14.2.2 Architecture of the URL2PNG application14.2.3 Setting up a message queue14.2.4 Producing messages programmatically14.2.5 Consuming messages programmatically14.2.6 Limitations of messaging with SQSSummary
15.1 In-place deployment with AWS CodeDeploy15.2 Rolling update with AWS CloudFormation and user data15.3 Deploying customized AMIs created by Packer15.3.1 Tips and tricks for Packer and CloudFormation15.4 Comparing approachesSummary
16.1 Using redundant EC2 instances to increase availability16.1.1 Redundancy can remove a single point of failure16.1.2 Redundancy requires decoupling16.2 Considerations for making your code fault tolerant16.2.1 Let it crash, but also retry16.2.2 Idempotent retry makes fault tolerance possible16.3 Building a fault-tolerant web application: Imagery16.3.1 The idempotent state machine16.3.2 Implementing a fault-tolerant web service16.3.3 Implementing a fault-tolerant worker to consume SQS messages16.3.4 Deploying the applicationSummary
17.1 Managing a dynamic EC2 instance pool17.2 Using metrics or schedules to trigger scaling17.2.1 Scaling based on a schedule17.2.2 Scaling based on CloudWatch metrics17.3 Decoupling your dynamic EC2 instance pool17.3.1 Scaling a dynamic EC2 instance pool synchronously decoupled by a load balancer17.3.2 Scaling a dynamic EC2 instances pool asynchronously decoupled by a queueSummary
18.1 Why should you consider containers instead of virtual machines?18.2 Comparing different options to run containers on AWS18.3 The ECS basics: Cluster, service, task, and task definition18.4 AWS Fargate: Running containers without managing a cluster of virtual machines18.5 Walking through a cloud-native architecture: ECS, Fargate, and S3Summary
AWS Services Explained in the Book