舉報(bào) 
會(huì)員
Learning AWS（Second Edition）
IfyouareanI.T.professionalorasystemarchitectwhowantstoimproveinfrastructureusingAWS,thenthisbookisforyou.ItisalsoforprogrammerswhoarenewtoAWSandwanttobuildhighlyefficient,scalableapplications.
目錄(277章)
倒序
- coverpage
- Title Page
- Packt Upsell
- Why subscribe?
- PacktPub.com
- Contributors
- About the authors
- About the reviewer
- Packt is searching for authors like you
- Preface
- Who this book is for
- What this book covers
- To get the most out of this book
- Download the color images
- Conventions used
- Get in touch
- Reviews
- Cloud 101 – Understanding the Basics
- Defining cloud computing
- Introducing public private and hybrid clouds
- Introducing cloud service models – IaaS PaaS and SaaS
- Introducing multi-tenancy models
- Understanding cloud-based workloads
- Migrating on-premise applications to the cloud
- Building cloud-native applications
- Setting up your AWS account
- Creating a new AWS account
- Exploring the AWS management console
- Summary
- Designing Cloud Applications
- Introducing cloud-based multitier architecture
- Designing for multi-tenancy
- Addressing data-at-rest security requirements
- Addressing data extensibility requirements
- Understanding cloud applications design principles
- Designing for scale
- Automating cloud infrastructure
- Designing for failure
- Designing for parallel processing
- Designing for performance
- Designing for eventual consistency
- Understanding emerging cloud-based application architectures
- Understanding polyglot persistence
- Understanding Lambda architecture
- Understanding Kappa architecture
- Deploying cloud-based machine learning pipelines
- Deploying cloud-based machine learning models
- Estimating your cloud computing costs
- A typical e-commerce web application
- Setting up your development environment
- Running the application
- Building a war file for deployment
- Application structure
- Summary
- Introducing AWS Components
- AWS components
- Amazon compute-related services
- Amazon EC2
- Amazon EC2 container service
- AWS Lambda
- Amazon storage-related services
- Amazon S3
- Amazon EBS
- Amazon Glacier
- Amazon database-related services
- Amazon Relational Database Service (RDS)
- Amazon DynamoDB
- Amazon Redshift
- Amazon ElastiCache
- Amazon messaging-related services
- Amazon SQS
- Amazon SNS
- Amazon SES
- Amazon Pinpoint
- Amazon networking and content delivery services
- Amazon VPC (Virtual Private Cloud)
- Amazon Elastic Load Balancing
- Amazon Route 53
- Amazon CloudFront
- AWS Direct Connect
- Amazon management tools
- AWS CloudFormation
- Amazon CloudWatch
- AWS CloudTrail
- Amazon security identity and compliance services
- AWS Identity and Access Management (IAM)
- AWS Directory Service
- Amazon Certificate Manager
- AWS Key Management Service
- AWS WAF
- Amazon analytics-related services
- Amazon EMR
- Amazon Kinesis
- Amazon machine learning/AI-related services
- Amazon Machine Learning
- Other Amazon AI-related services
- Other Amazon services
- Managing costs on AWS cloud
- Setting costs-related objectives
- Optimizing costs on the cloud
- Strategies to lower AWS costs
- Monitoring and analyzing costs
- Choosing the right EC2 Instance
- Turn-off unused instances
- Using Auto Scaling
- Using reserved instances
- Using spot instances
- Using Amazon S3 storage
- Optimizing database utilization and costs
- Using AWS services
- Using queues
- Application development environments
- Development environment
- QA/test environment
- Staging environment
- Production environment
- Setting up the AWS infrastructure
- AWS Cloud deployment architecture
- AWS cloud construction
- Creating security groups
- Creating EC2 instance key pairs
- Creating roles
- Creating an EC2 instance
- Creating and associating Elastic IPs (EIP)
- Configuring the Amazon Relational Database Service (RDS)
- Installing and verifying the software stack
- Summary
- Designing for and Implementing Scalability
- Defining scalability objectives
- Designing scalable application architectures
- Using AWS services for out-of-the-box scalability
- Using a scale-out approach
- Implementing loosely-coupled components
- Implementing asynchronous processing
- Leveraging AWS infrastructure services for scalability
- Using AWS CloudFront to distribute content
- Using AWS ELB to scale without service interruptions
- Using Amazon CloudWatch for Auto Scaling
- Scaling data services
- Scaling proactively
- Using the EC2 container service
- Evolving architecture against increasing loads
- Scaling from one to half a million users
- Scaling from half a million to a million users
- Scaling from a million to ten million users
- Event handling at scale
- Implementing a large-scale API-based architecture with AWS services
- Using Amazon API Gateway
- Using AWS Lambda
- Using Kinesis Streams
- Using Elasticsearch
- Analyzing streaming data in real time with Amazon Kinesis Analytics
- Using Amazon Kinesis Firehose
- Using Amazon Kinesis Analytics
- Building real-time applications with Amazon Kinesis Analytics
- Setting up Auto Scaling
- AWS Auto Scaling construction
- Creating an AMI
- Creating the Elastic Load Balancer
- Creating launch configuration
- Creating an Auto Scaling group
- Testing Auto Scaling groups
- Summary
- Designing for and Implementing High Availability
- Defining availability objectives
- Nature of failures
- Setting up VPC for high availability
- Using ELB and Route 53 for high availability
- Instance availability
- Auto Scaling for increased availability and reliability
- Zonal Availability or Availability Zone Redundancy
- Region availability or regional redundancy
- Setting up high availability for application and data layers
- Implementing high availability in the application
- Using AWS for disaster recovery
- Using a backup and restore DR strategy
- Using a Pilot Light architecture for DR
- Using a warm standby architecture for DR
- Using a Multi-Site architecture for DR
- Testing disaster recovery strategy
- Setting up high availability
- AWS high availability architecture
- HA support for Elastic Load Balancer
- HA support for the Relational Database Service
- Summary
- Designing for and Implementing Security
- Defining security objectives
- Understanding the security responsibilities
- Best practices in implementing AWS security
- Security considerations while using CloudFront
- CloudFront and ACM integration
- Understanding access control options
- Web Application Firewall
- Securing the application
- Implementing Identity Lifecycle Management
- Tracking AWS API activity using CloudTrail
- Logging for security analysis
- Using third-party security solutions
- Reviewing and auditing security configuration
- Setting up security
- Using AWS IAM to secure an infrastructure
- Understanding IAM roles
- Using the AWS Key Management Service
- Creating KMS keys
- Using the KMS key
- Application security
- Implementing transport security
- Generating self-signed certificates
- Configuring ELB for SSL
- Securing data at rest
- Securing data on S3
- Using the S3 console for server-side encryption
- Securing data on RDS
- Summary
- Deploying to Production and Going Live
- Managing infrastructure deployments and support at scale
- Creating and managing AWS environments using CloudFormation
- Creating CloudFormation templates
- Building a DevOps pipeline with CloudFormation
- Updating stacks
- Extending CloudFormation
- Using CloudWatch for monitoring
- Using AWS solutions for backup and archiving
- Planning for production go-live activities
- Setting up for production
- AWS production deployment architecture
- VPC subnets
- Private subnet
- Bastion subnet
- Bastion host
- Security groups
- Infrastructure as Code
- Setting up CloudFormation
- Centralized logging
- Setting up CloudWatch
- Summary
- Designing a Big Data Application
- Introducing big data applications
- AWS components used in big data applications
- Analyzing streaming data with Amazon Kinesis
- Best practices for serverless big data applications
- Best practices for using Amazon EMR
- Understanding common EMR use cases
- Lowering EMR costs
- Using Amazon EC2 Spot and Auto Scaling
- Best practices for distributed machine learning and predictive analytics
- Using Amazon SageMaker for machine learning
- Understanding Amazon SageMaker algorithms and features
- Security overview for big data applications
- Securing the EMR cluster
- Encryption
- Authentication
- Authorization
- Securing serverless applications
- Understanding serverless application authentication and authorization
- Configuring and using EMR-Spark clusters
- Summary
- Implementing a Big Data Application
- Setting up an Amazon Kinesis Stream
- Creating an AWS Lambda function
- Using Amazon Kinesis Firehose
- Using AWS Glue and Amazon Athena
- Using Amazon SageMaker
- Summary
- Deploying a Big Data System
- Using CloudFormation templates
- Creating a data lake using a CloudFormation template
- Authoring and deploying serverless applications
- Understanding AWS SAM
- Understanding the SAM template
- Introducing SAM Local
- Developing serverless applications using AWS Cloud9
- Automating serverless application deployments
- Using AWS Serverless Application Repository
- Summary
- Other Books You May Enjoy
- Leave a review - let other readers know what you think 更新時(shí)間：2021-06-30 18:53:51
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