Serverless design patterns and best practices build, secure, and deploy enterprise ready serverless applications with AWS to improve developer productivity
Get started with designing your serverless application using optimum design patterns and industry standard practices About This Book Learn the details of popular software patterns and how they are applied to serverless applications Understand key concepts and components in serverless designs Walk aw...
| Otros Autores: | |
|---|---|
| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
Birmingham ; Mumbai :
Packt
2018.
|
| Edición: | 1st edition |
| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009631476206719 |
Tabla de Contenidos:
- Cover
- Title Page
- Copyright and Credits
- Dedication
- Packt Upsell
- Contributors
- Table of Contents
- Preface
- Chapter 1: Introduction
- What is serverless computing?
- No servers to manage
- Pay-per-invocation billing model
- Ability to automatically scale with usage
- Built-in availability and fault tolerance
- Design patterns
- When to use serverless
- The sweet spot
- Classes of serverless pattern
- Three-tier web application patterns
- ETL patterns
- Big data patterns
- Automation and deployment patterns
- Serverless frameworks
- Summary
- Chapter 2: A Three-Tier Web Application Using REST
- Serverless tooling
- System architecture
- Presentation layer
- Logic layer
- Data layer
- Logic layer
- Application code and function layout
- Organization of the Lambda functions
- Organization of the application code
- Configuration with environment variables
- Code structure
- Function layout
- Presentation layer
- File storage with S3
- CDN with CloudFront
- Data layer
- Writing our logic layer
- Application entrypoint
- Application logic
- Wiring handler.py to Lambda via API Gateway
- Deploying the REST API
- Deploying the Postgres database
- Setting up static assets
- Viewing the deployed web application
- Running tests
- Iteration and deployment
- Deploying the entire stack
- Deploying the application code
- Summary
- Chapter 3: A Three-Tier Web Application Pattern with GraphQL
- Introduction to GraphQL
- System architecture
- Logic layer
- Organization of the Lambda functions
- Organization of the application code
- Function layout
- Presentation layer
- Writing the logic layer
- Implementing the entry point
- Implementing GraphQL queries
- Implementing GraphQL mutations
- Deployment
- Viewing the deployed application
- Iteration and deployment
- Summary.
- Chapter 4: Integrating Legacy APIs with the Proxy Pattern
- AWS API Gateway introduction
- Simple proxy to a legacy API
- Setting up a pass-through proxy
- Deploying a pass-through proxy
- Transforming responses from a modern API
- Method execution flow
- Setting up example
- Setting up a new resource and method
- Setting up Integration Request
- Setting up Integration Response
- Complex integration using a Lambda function
- Implementing the application code
- Setting up a new resource and method
- Migration techniques
- Staged migration
- Migrating URLs
- Summary
- Chapter 5: Scaling Out with the Fan-Out Pattern
- System architecture
- Synchronous versus asynchronous invocation
- Resizing images in parallel
- Setting up the project
- Setting up trigger and worker functions
- Setting up permissions
- Implementing the application code
- Testing our code
- Alternate Implementations
- Using notifications with subscriptions
- Using notifications with queues
- Summary
- Chapter 6: Asynchronous Processing with the Messaging Pattern
- Basics of queuing systems
- Choosing a queue service
- Queues versus streams
- Asynchronous processing of Twitter streams
- System architecture
- Data producer
- Mimicking daemon processes with serverless functions
- Data consumers
- Viewing results
- Alternate Implementations
- Using the Fan-out and Messaging Patterns together
- Using a queue as a rate-limiter
- Using a dead-letter queue
- Summary
- Chapter 7: Data Processing Using the Lambda Pattern
- Introducing the lambda architecture
- Batch layer
- Speed layer
- Lambda serverless architecture
- Streaming data producers
- Data storage
- Computation in the speed layer
- Computation in the batch layer
- Processing cryptocurrency prices using lambda architecture
- System architecture
- Data producer
- Speed layer.
- Batch layer
- AWS resources
- Data producer
- Speed layer
- Batch layer
- Results
- Summary
- Chapter 8: The MapReduce Pattern
- Introduction to MapReduce
- MapReduce example
- Role of the mapper
- Role of the reducer
- MapReduce architecture
- MapReduce serverless architecture
- Processing Enron emails with serverless MapReduce
- Driver function
- Mapper implementation
- Reducer implementation
- Understanding the limitations of serverless MapReduce
- Memory limits
- Storage limits
- Time limits
- Exploring alternate implementations
- AWS Athena
- Using a data store for results
- Using Elastic MapReduce
- Summary
- Chapter 9: Deployment and CI/CD Patterns
- Introduction to CI/CD
- CI
- CD
- Setting up unit tests
- Code organization
- Setting up unit tests
- Setting up CI with CircleCI
- Configuring CircleCI builds
- Setting up environment variables
- Setting up CD and deployments with CircleCI
- Setting up Slack notifications
- Setting up a CircleCI badge
- Setting up deployments
- Setting up AWS credentials
- Setting up environment variables
- Executing deployments
- Summary
- Chapter 10: Error Handling and Best Practices
- Error tracking
- Integrating Sentry for error tracking
- Integrating Rollbar
- Logging
- Structuring log messages
- Digesting structured logs
- Cold starts
- Keeping cloud functions warm
- AWS Lambda functions and VPCs
- Start-up times for different languages
- Allocating more memory
- Local development and testing
- Local development
- Learning about testing locally
- Managing different environments
- Securing sensitive configuration
- Encrypting variables
- Decrypting variables
- Trimming AWS Lambda versions
- Summary
- Other Books You May Enjoy
- Index.
