Practical Spring Cloud Function

Unlike other resources that target only programming communities, this book targets both programming and business communities. With programming models shifting more towards no-code and low-code, citizen programmers from the business side will welcome this book as a guide for how to design and optimize their information pipeline while lowering costs for infrastructure. Programmers, on the other hand, will welcome this book's business-centric programming view, which will get them a step closer to fulfilling real business requirements.

Practical Spring Cloud Function touches on the themes of portability, scalability, high performance and high availability. Each theme is explored via a real enterprise use case and code. The use cases target industries including energy (oil pipeline sensors), automotive (event-driven connected vehicles), and retail (conversational AI).

After reading this book, you'll come away with the know-how to build and deploy cloud-native Java applications effectively and efficiently.

WHAT YOU WILL LEARN

* Write functions and deploy to Amazon Web Services, Microsoft Azure, Google Cloud, IBM Cloud, and on-prem clouds such as VMWare Tanzu and RedHat OpenShift
* Set up locally with KNative on Kubernetes, as well as on AWS, Azure, GCP, Tanzu, and others
* Build, test, and deploy a simple example with Spring Cloud Function
* Develop an event-driven data pipeline with Spring Cloud Function
* Integrate with AI and machine learning models
* Apply Spring Cloud Function to the Internet of Things (IoT)
* Get industry-specific examples of Spring Cloud Function in action

WHO THIS BOOK IS FOR

Software and cloud-native application developers with prior programming experience in the cloud and/or Spring Framework. DevOps professionals may find this book beneficial as well.

Banu Parasuraman is a Cloud Native Technologist with over 30 years of experience in the IT industry. He provides an advisory role to clients who are looking to move to cloud or implement cloud-native platforms such as Kubernetes, Cloud Foundry and the like. He has engaged over 25 select companies spread across different sectors (Retail, Healthcare, Logistics, Banking, Manufacturing, Automotive, Oil & Gas, Pharmaceuticals, Media & Entertainment ...) in USA, Europe and Asia have interacted at every level of an organization. Banu is a key evangelist for Cloud-Native computing encouraging client and architects to undertake this journey as soon as possible to avoid organizational inertia later. He is experienced in most of the popular cloud platforms such as VMWare-VCF, Pivotal-PCF, IBM-OCP, Google-GCP, Amazon-AWS, Microsoft-Azure. Banu has taken part in external speaking engagements targeted at CXOs and Engineers: VMworld, SpringOne, Spring Days, Spring Developer Forum Meetups. Internal speaking engagements: Developer Workshops on Cloud Native Architecture and Development, Customer Workshops on Pivotal Cloud Foundry, enabling Cloud Native sales plays and strategies for sales and teams. Lastly, Banu has numerous blogs on platforms such a Medium and Linkedin to promote adoption of Cloud Native architecture and development.

1. Why Spring Cloud Functions

This chapter takes the reader through the need for Spring Cloud Functions and KNative. The rationale for Spring Cloud Functions will be elucidated through example implementation on on-prem and cloud infrastructures. The chapter highlights the “code once deploy anywhere” characteristic of Spring Cloud Functions.

Subtitles

1. Writing functions and deploying to any hyperscaler2. Example code

3. Spring Cloud Functions on AWS (EKS, Fargate)

4. Spring Cloud Functions on Azure (AKS)

5. Spring Cloud Functions on Google (Cloud Run)

6. Spring Cloud Functions on VMWare Tanzu (TKG, PKS)

7. Spring Cloud Functions on RedHat OpenShift (OCP)

2. Getting Started with Spring Cloud Functions

This chapter walks the reader through the steps required to get started with Spring Serverless on their platform of choice, either locally, on-prem or on the cloud. Step by Step instructions take the reader through the process of getting the environment set up for coding.

Subtitles

1. Step by Step: Setup locally with Kubernetes and KNative with Spring Cloud Functions2. Step by Step: Setup on AWS with EKS and KNative with Spring Cloud Functions

3. Step by Step: Setup on GCP with Cloud Run/GKE and KNative with Spring Cloud Functions

4. Step by Step: Setup on Azure with AKS and KNative with Spring Cloud Functions

5. Step by Step: Setup on VMWare Tanzu TKG and KNative

6. Step by Step: Setup on RedHat Openshift and KNative

3. Coding, testing, and deploying with Spring Cloud Functions

This chapter covers the coding, testing, and deploying using your favorite IDE like Eclipse, Eclipse Che, Intelij IDEA, Redhat Code Ready Workspace. The reader will build an example and deploy to their favorite platform

a. Building a simple example with Spring Cloud Functions

b. Testing the example will sample data

c. Setting up a CI/CD pipeline for deploying to a target platformd. Deploying to the target platfom

i. AWS

ii. GCP

iii. Azure

iv. VMWare Tanzu

v. RedHat Openshift

4. Building Event Driven Data pipelines with Spring Cloud Functions

Event Driven data pipelines act as a conduit to flow of data based on a specific event. The event can be a purchase order triggered on the website that initiate a data flow chain that includes aggregation of data from various data sources and splitting the data to various consumers. This chapter will discuss the various ways that Spring Spring Serverless can be implemented in the various Cloud providers

Subtitles

1. Spring Cloud Functions and Spring Cloud Data Flow and Spring Cloud Streams

2. Spring Cloud Functions and AWS Glue

3. Spring Cloud Functions and Google Cloud Data Flow

4. Spring Cloud Functions and Azure Data Factory

5. AI/ML Trained Serverless Endpoints with Spring Cloud Functions

Conversational AI models are one of the complex implementations that may lead to heavy use of resources in the cloud. Leveraging Serverless infra and functions can help alleviate the costs by being invoked only when needed. This chapter will help layout the blueprint of how to leverage Spring Serverless with on-prem or cloud-based AI/ML environments

Subtitles

1. Spring Cloud Functions with Google Cloud Functions and Tensor Flow

2. Spring Cloud Functions with AWS Glue and AWS Sage or AI/ML

3. Spring Cloud Functions with Azure Data Factory and Azure ML

4. Spring Cloud Functions with Apache AI/ML on-prem VMWare Tanzu and Openshift

6. Spring Cloud Functions and IOT

This chapter will take the reader through blueprints and architect diagrams of how Spring serverless works in conjunction with IOT on various Hyperscalers (Cloud Providers) or SaaS IOT Gateway providers.

Subtitles

1. Spring Cloud Functions on the Cloud with AWS IOT

2. Spring Cloud Functions on the cloud with Azure IOT

3. Spring Cloud Functions on the cloud with GCP IOT

4. Spring Cloud Functions on-prem with IOT gateway on a SaaS provider (Eg, SmartSense)

7. Industry specific examples with Spring Cloud Functions

This chapter will provide industry specific examples and use cases that will help the reader understand how Spring Serverless can be leveraged within their specific business use case

1. Oil/ Natural gas pipeline tracking with Spring Cloud Functions, IOT and Spring Cloud Data Flow

2. Enabling ubiquitous health care with Spring Cloud Functions and Big Data Pipelines

3. Connected vehicles with Spring Cloud Functions

4. Conversational AI in Retail with Spring Cloud Functions