Book Image

JavaScript Cloud Native Development Cookbook

By : John Gilbert
Book Image

JavaScript Cloud Native Development Cookbook

By: John Gilbert

Overview of this book

Cloud-native development is a modern approach to building and running applications that leverages the merits of the cloud computing model. With cloud-native development, teams can deliver faster and in a more lean and agile manner as compared to traditional approaches. This recipe-based guide provides quick solutions for your cloud-native applications. Beginning with a brief introduction, JavaScript Cloud-Native Development Cookbook guides you in building and deploying serverless, event-driven, cloud-native microservices on AWS with Node.js. You'll then move on to the fundamental patterns of developing autonomous cloud-native services and understand the tools and techniques involved in creating globally scalable, highly available, and resilient cloud-native applications. The book also covers multi-regional deployments and leveraging the edge of the cloud to maximize responsiveness, resilience, and elasticity. In the latter chapters you'll explore techniques for building fully automated, continuous deployment pipelines and gain insights into polyglot cloud-native development on popular cloud platforms such as Azure and Google Cloud Platform (GCP). By the end of the book, you'll be able to apply these skills to build powerful cloud-native solutions.

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Table of Contents (13 chapters)
Preface
Preface
Who this book is for
What this book covers
To get the most out of this book
Sections
Get in touch
Free Chapter
1
Getting Started with Cloud-Native
Getting Started with Cloud-Native
Introduction
Creating a stack
Creating a function and working with metrics and logs
Creating an event stream and publishing an event
Creating a stream processor
Creating an API Gateway
Deploying a single-page application
2
Applying the Event Sourcing and CQRS Patterns
Applying the Event Sourcing and CQRS Patterns
Introduction
Creating a data lake
Applying the event-first variant of the Event Sourcing pattern
Creating a micro event store
Applying the database-first variant of the Event Sourcing pattern with DynamoDB
Applying the database-first variant of the Event Sourcing pattern with Cognito datasets
Creating a materialized view in DynamoDB
Creating a materialized view in S3
Creating a materialized view in Elasticsearch
Creating a materialized view in a Cognito dataset
Replaying events
Indexing the data lake
Implementing bi-directional synchronization
3
Implementing Autonomous Services
Implementing Autonomous Services
Introduction
Implementing a GraphQL CRUD BFF
Implementing a search BFF
Implementing an analytics BFF
Implementing an inbound External Service Gateway
Implementing an outbound External Service Gateway
Orchestrating collaboration between services
Implementing a Saga
4
Leveraging the Edge of the Cloud
Leveraging the Edge of the Cloud
Introduction
Serving a single-page application from a CDN
Associating a custom domain name with a CDN
Serving a website from the CDN
Deploying a service behind a CDN
Serving static JSON from a CDN
Triggering the invalidation of content in a CDN
Executing code at the edge of the cloud
5
Securing Cloud-Native Systems
Securing Cloud-Native Systems
Introduction
Securing your cloud account
Creating a federated identity pool
Implementing sign up, sign in, and sign out
Securing an API Gateway with OpenID Connect
Implementing a custom authorizer
Authorizing a GraphQL-based service
Implementing a JWT filter
Using envelope encryption
Creating an SSL certificate for encryption in transit
Configuring a web application firewall
Replicating the data lake for disaster recovery
6
Building a Continuous Deployment Pipeline
Building a Continuous Deployment Pipeline
Introduction
Creating the CI/CD pipeline
Writing unit tests
Writing integration tests
Writing contract tests for a synchronous API
Writing contract tests for an asynchronous API
Assembling transitive end-to-end tests
Leveraging feature flags
7
Optimizing Observability
Optimizing Observability
Introduction
Monitoring a cloud-native system
Implementing custom metrics
Monitoring domain events
Creating alerts
Creating synthetic transaction tests
8
Designing for Failure
Designing for Failure
Introduction
Employing proper timeouts and retries
Implementing backpressure and rate limiting
Handling faults
Resubmitting fault events
Implementing idempotence with an inverse OpLock
Implementing idempotence with Event Sourcing
9
Optimizing Performance
Optimizing Performance
Introduction
Tuning Function as a Service
Batching requests
Leveraging asynchronous non-blocking IO
Grouping events in stream processors
Autoscaling DynamoDB
Utilizing cache-control
Leveraging session consistency
10
Deploying to Multiple Regions
Deploying to Multiple Regions
Introduction
Implementing latency-based routing
Creating a regional health check
Triggering regional failover
Implementing regional replication with DynamoDB
Implementing round-robin replication
11
Welcoming Polycloud
Welcoming Polycloud
Introduction
Creating a service with Google Cloud Functions
Creating a service with Azure Functions
12
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Implementing idempotence with an inverse OpLock

From a business rule standpoint, it is important that events are processed exactly once; otherwise, problems may arise, such as double counting or not counting at all. However, our cloud-native systems must be resilient to failure and proactively retry to ensure no messages are dropped. Unfortunately, this means that messages may be delivered multiple times, for example when a producer re-publishes an event or a stream processor retries a batch that may have been partially processed. The solution to this problem is to implement all actions to be idempotent. This recipe implements idempotency with what I refer to as an inverse OpLock.

How to do it...

  1. Create the project from the...
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